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Author SHA1 Message Date
Alexander Alekhin 83391ac59d release: OpenCV 3.4.19 2022-12-27 03:50:12 +00:00
Alexander Alekhin a8a93a57e7 Merge pull request #23029 from savuor:backport3_fix_fisheye_aspect_ratio 2022-12-27 03:47:01 +00:00
Rostislav Vasilikhin 93aa94e71e backported changes
no lambda

whitespace

fixing build Java tests
2022-12-27 00:54:39 +01:00
Alexander Alekhin 26f36f2ff9 Merge pull request #22971 from alalek:update_version_3.4.19-pre 2022-12-25 18:39:54 +00:00
Alexander Alekhin a494c75bfe pre: OpenCV 3.4.19 (version++) 2022-12-25 16:59:47 +00:00
Alexander Alekhin 139bd30247 Merge pull request #22962 from stopmosk:20465-dstchannels-does-not-cover-all-color-codes-1 2022-12-23 11:41:31 +00:00
Sergei Shutov 1339c7f30c Define the number of dstChannels for Lab, Luv, YCrCb and XYZ conversions 2022-12-23 12:04:30 +02:00
Alexander Smorkalov 44dfe62af0 Merge pull request #22914 from tozanski:tomoz/ransac-bugfix
Bugfix for solvePnPRansac with SOLVEPNP_ITERATIVE
2022-12-22 11:58:14 +03:00
Alexander Alekhin d44c58a1fb Merge pull request #22988 from vrabaud:mm_pause_fix 2022-12-19 17:06:50 +00:00
Vincent Rabaud 7463e9b8bb Even faster CV_PAUSE on SkyLake and above.
No need to loop as RDTSC is 3/4 times faster than _mm_pause.
2022-12-19 14:15:34 +01:00
Alexander Alekhin 07ed5e5346 Merge pull request #22980 from alalek:samples_python_3.11 2022-12-18 02:07:46 +00:00
Alexander Alekhin 5855eba9f3 samples: query for Python 3.11 setup 2022-12-18 00:14:41 +00:00
Alexander Alekhin eace6adb6d Merge pull request #22934 from alalek:fix_filestorage_binding 2022-12-17 03:28:13 +00:00
Alexander Smorkalov 6b50410336 Merge pull request #22966 from vrabaud:mm_pause_fix
Fix slower CV_PAUSE on SkyLake and above.
2022-12-16 12:19:24 +03:00
Alexander Alekhin 6e3700593f compatibility: keep Ptr<FileStorage> stubs till OpenCV 5.0 2022-12-16 00:47:44 +00:00
Alexander Alekhin 6a8c5a1d27 python: resolve Ptr<FileStorage> requirement issue 2022-12-16 00:47:44 +00:00
Vincent Rabaud b7b08fa0c3 Fix slower CV_PAUSE on SkyLake and above.
This is fixing https://github.com/opencv/opencv/issues/22852
2022-12-15 14:18:57 +01:00
Alexander Smorkalov 52709c7771 Merge pull request #22954 from VadimLevin:dev/vlevin/fix-merge-artifacts-in-python-misc-tests
fix: remove function duplicates in test_misc.py
2022-12-14 09:42:43 +03:00
Alexander Smorkalov aff375808d Merge pull request #22955 from VadimLevin:dev/vlevin/handle-properties-with-keyword-names
fix: add _ suffix to properties having reserved keyword names
2022-12-14 09:35:07 +03:00
Vadim Levin 3f5f09e730 fix: add _ suffix to properties having reserved keyword names 2022-12-13 20:56:39 +03:00
Vadim Levin 253a4c113e fix: remove function duplicates in test_misc.py 2022-12-13 19:14:52 +03:00
Alexander Smorkalov c2ecbc76ce Merge pull request #22946 from VadimLevin:dev/vlevin/avfoundation-stable-multicamera-index
fix: AVFoundation inconsistent camera indices
2022-12-13 10:34:42 +03:00
Vadim Levin 727feda935 fix: AVFoundation inconsistent camera indices 2022-12-12 17:15:46 +03:00
Alexander Alekhin ebaee3ea21 Merge pull request #22937 from asmorkalov:as/issue_22893 2022-12-09 17:11:51 +00:00
Alexander Smorkalov 423bc515e5 Integer underflow fix for morphologyEx in Carotene (arm). 2022-12-09 18:08:22 +03:00
Tomasz Ożański d1ff87d94d Bugfix for solvePnPRansac with SOLVEPNP_ITERATIVE
The current implementation overwrites the result rotation and translation in every iteration.
If SOLVEPNP_ITERATIVE was run as a refinement it will start from the incorrect initial
transformation thus  degrading the final outcome.
2022-12-03 16:46:03 +01:00
Christine Poerschke 4792837f2e Merge pull request #22865 from cpoerschke:3.4-issue-22860
ocl_minMaxIdx to call minmaxloc.cl for OpenCL 1.2+ only
2022-12-03 05:29:04 +00:00
Alexander Alekhin 416830fb59 Merge pull request #22888 from alalek:dnn_ov_fix_custom_layers 2022-12-03 05:24:28 +00:00
Alexander Alekhin 07b1bc2e88 Merge pull request #22910 from alalek:cmake_pkg_config_ignore_atomic 2022-12-03 05:22:04 +00:00
Alexander Alekhin d16b3b2487 dnn(test): restore openvino tests with 'Cannot get memory' message 2022-12-03 01:34:48 +00:00
Alexander Alekhin 74d0b4cc78 dnn(openvino): fix custom layers BlockingDesc 2022-12-03 01:34:10 +00:00
Alexander Alekhin 8832a9dbd5 cmake: ocv_check_modules: ignore -latomic and -lstdc++ 2022-12-02 22:49:46 +00:00
Alexander Smorkalov d4dc6b509b Merge pull request #22796 from ClayXrex:patch-1
fix: typo in opencv-python tutorials
2022-11-30 14:26:07 +03:00
ClayXrex 71a1150c95 fix: typo 2022-11-30 12:52:51 +03:00
Dan Mašek aba2167d9c Merge pull request #22838 from dan-masek:fix_issue_22837
Fix issue 22837: No more blank buttons on toolbar after resizing the window
2022-11-22 13:47:27 +03:00
Alexander Smorkalov 5db4f1f7df Merge pull request #22830 from alalek:issue_22752
imgcodecs: ensure parameters are key-value pairs, fix HDR encoder
2022-11-22 12:50:02 +03:00
Alexander Alekhin 2a5da50902 Merge pull request #22806 from dan-masek:fix_issue_22767 2022-11-21 19:53:34 +00:00
Alexander Smorkalov 51758b2dd6 Merge pull request #22842 from asmorkalov:as/pr_22737_backport
backport #22737: Cocoa/highgui: Set [NSApp activateIgnoringOtherApps] to spawn window on top
2022-11-21 13:41:44 +03:00
fwcd 90b144cf0a Cocoa/highgui: Set activateIgnoringOtherApps 2022-11-21 12:49:08 +03:00
Alexander Alekhin 6c36cd5d6e Merge pull request #22839 from zchrissirhcz:fix-typo-3.4 2022-11-21 07:48:04 +00:00
Zhuo Zhang c63a6c472d fix typo: Gausssian to Gaussian 2022-11-21 10:44:12 +08:00
Alexander Alekhin 5b3f721efa Merge pull request #22805 from dan-masek:fix_issue_22766 2022-11-20 22:28:24 +00:00
Dan Mašek e5bea2bde4 Fix #22766: Corrected off-by one error causing inconsistent row spacing. (rebased to 3.4) 2022-11-20 21:48:23 +01:00
Dan Mašek e9d64e0a8c Fix #22767: Ensure that the buttons are spaced to the size of the toolbar window, which is always visible. (rebased to 3.x) 2022-11-20 20:53:23 +01:00
Alexander Alekhin f0df78b7e7 imgcodecs: ensure parameters are key-value pairs, fix HDR encoder 2022-11-20 13:08:46 +00:00
Alexander Smorkalov 7592d58f0c Merge pull request #22771 from kallaballa:opencl_hls_and_hsv_conversions_bug
define the number of dstChannels for HLS and HSV conversion as well
2022-11-17 13:36:18 +03:00
Alexander Alekhin d9f66413ee Merge pull request #22811 from alalek:core_check_bool 2022-11-16 04:06:23 +00:00
Alexander Alekhin 1b1bbe4262 Merge pull request #22801 from alalek:update_zlib
* 3rdparty: zlib 1.2.12 => 1.2.13

https://github.com/madler/zlib/releases/tag/v1.2.13

- replace README -> LICENSE in install distribution

* 3rdparty(zlib): re-apply patch 20190330-ununitialized-use-state-check.diff
2022-11-16 04:05:08 +00:00
Alexander Alekhin 54531f8e3b core: support CV_Check*() macros with 'bool' parameters 2022-11-15 11:47:16 +00:00
Alexander Smorkalov b5a68f235a Merge pull request #22802 from zihaomu:fix_infinit_loop_in_tf_34
Fix infinit loop in tf 3.4 branch
2022-11-15 11:45:14 +03:00
zihaomu 5bf64e7dfe fix the infinite loop in tf importer of 3.4 branch 2022-11-15 11:42:10 +08:00
kallaballa f5e852cdf0 define the number of dstChannels for HLS and HSV conversion as well 2022-11-11 09:23:28 +01:00
Alexander Alekhin b418eb112c Merge pull request #22717 from alalek:issue_22716 2022-10-31 17:03:43 +00:00
Alexander Alekhin 028d4d83d3 imgproc: sigma2=sigma1 in top-level function of GaussianBlur 2022-10-28 17:04:53 +00:00
Maksim Shabunin c0a84dcc85 Merge pull request #22651 from mshabunin:script-doc
ts: basic documentation for utility scripts
2022-10-20 14:11:02 +03:00
Alexander Alekhin e309a06b47 Merge pull request #22661 from catree:fix_AKAZE_bib_pages 2022-10-19 15:48:38 +00:00
Alexander Alekhin 86dad3aebe Merge pull request #22662 from catree:fix_chessboard_img 2022-10-19 12:57:16 +00:00
catree 5a9fe9dedb Replace the chessboard.png image with the pattern.png image since the chessboard.png image does not have proper squares which is not good for camera calibration accuracy. 2022-10-19 14:11:01 +02:00
catree c7d24c0fb3 Fix AKAZE bib reference using dblp.org and bmva.org sources. 2022-10-19 13:55:33 +02:00
Alexander Alekhin ea5ca16036 Merge pull request #22617 from changh95:4.x 2022-10-14 09:17:16 +00:00
Alexander Smorkalov 2991717191 Merge pull request #22637 from alalek:docs_fix_links_generation_22572
docs: prefer # for links generation
2022-10-14 09:18:27 +03:00
Hyunggi Chang 085fb78e85 fix typo (portatibility -> portability) 2022-10-13 21:39:52 +00:00
Alexander Alekhin a565aa6db9 docs: prefer # for links generation
- avoid `@ref`
- align with 4.x branch (minimize merge conflicts)
2022-10-13 20:55:53 +00:00
Alexander Alekhin bbcc1752b1 Merge pull request #22600 from alalek:cmake_opt_force_targets 2022-10-06 05:05:40 +00:00
Alexander Alekhin d480e2e51b cmake(opt): force separate targets for dispatched code
- PCH may not pass compilation flags properly
2022-10-05 21:54:46 +03:00
Alexander Smorkalov 4a4b2a0ce6 Merge pull request #22539 from catree:feat_homography_tutorial_gif
Add a gif to the homography exercise
2022-10-04 15:59:40 +03:00
Alexander Smorkalov 4103567776 Merge pull request #22194 from heavyrain-lzy:fixbug_pyrup
Fix the pyramid bug when src*2 < dst
2022-10-04 15:37:01 +03:00
catree ab5279f4ad Add an image to illustrate camera poses interpolation for the small homography exercise. 2022-10-04 13:36:58 +02:00
Kumataro 2f79b1b087 Merge pull request #22404 from Kumataro:3.4-fix22388_2
* imgcodecs: tiff: Reduce memory usage to read 16bit image.

* imgcodecs: tiff: Reduce memory usage to read 8bit images

* imgcodecs: tiff: split basic test and full test.

* imgcodecs: tiff: fix to warning C4244

* imgcodecs: tiff: fix to warning C4244
2022-10-03 18:24:15 +03:00
Alexander Smorkalov 572d4f4491 Merge pull request #22584 from vrabaud:msan
Move marking memory as initialized earlier.
2022-10-03 15:48:38 +03:00
Vincent Rabaud 38c9c20a35 Move marking memory as initialized earlier. 2022-09-28 21:58:17 +02:00
Alexander Smorkalov 4dfbbabf8b Merge pull request #22572 from catree:feat_improve_doc_calib3d
[3.4] Add information about the disparity-to-depth mapping matrix
2022-09-27 10:19:17 +03:00
catree c34c4b50d0 Add information about the disparity-to-depth mapping matrix. Add more references about other related functions in the calib3d doc. 2022-09-26 18:40:18 +02:00
Alexander Smorkalov 0c238c9e72 Merge pull request #22568 from asmorkalov:as/webp_warning
Report that animated webp is not supported for now
2022-09-26 14:16:18 +03:00
Alexander Smorkalov 3d9f27b877 Report that animated webp is not supported for now. 2022-09-26 13:53:49 +03:00
Alexander Smorkalov bfeeb0ad70 Merge pull request #22285 from asenyaev:asen/disabled_compiling_warnings_3.4
Disabled compiling warnings in case of symbols in cmake for 3.4
2022-09-20 15:14:36 +03:00
Andrey Senyaev 3f4abcb228 Disabled compiling warnings in case of symbols in cmake for 3.4 2022-09-20 13:34:17 +03:00
Alexander Smorkalov f2ccce23f3 Merge pull request #22512 from alalek:build_warning_gcc12_uninitialized
build: eliminate uninitialized warnings from GCC12
2022-09-20 09:29:00 +03:00
Alexander Smorkalov 0ab4872032 Merge pull request #22511 from alalek:dnn_build_warning_gcc12
dnn: eliminate GCC12 warning in total() call
2022-09-19 16:22:54 +03:00
Alexander Smorkalov 377fdf5ae5 Merge pull request #22504 from hflemmen:fix-broken-link
Removes a broken link
2022-09-14 20:01:04 +03:00
Alexander Alekhin 2e15582799 build: eliminate uninitialized warnings from GCC12 2022-09-14 11:58:43 +00:00
Alexander Alekhin 65bdb3a544 dnn: eliminate GCC12 warning in total() call 2022-09-14 11:37:00 +00:00
Henrik Dobbe Flemmen 6481cfd048 Update the fourcc codes link 2022-09-14 09:25:57 +03:00
Alexander Smorkalov d885242b61 Merge pull request #22482 from Glutamat42:tutorial_generalized_hough_transform
Tutorial for Generalized Hough Ballard and Guil Transform
2022-09-12 10:45:18 +03:00
Markus Heck 619e038de9 move tutorial to imgproc and example to ImgTrans 2022-09-10 17:42:20 +02:00
Markus Heck 5408949951 fix typo and simplify example (grayscale template) 2022-09-09 15:27:11 +02:00
Markus Heck e2a9cff3dc Include code snippets with doxygen notation and small fix in table_of_content_objdetect.markdown 2022-09-08 13:03:33 +02:00
Markus Heck c3b83b8354 Tutorial for Generalized Hough Ballard and Guil Transform 2022-09-08 03:40:52 +02:00
Alexander Smorkalov e24382691f Merge pull request #21934 from Yulv-git:3.4-typos2
Fix some typos in platforms/, samples/.
2022-09-07 17:16:23 +03:00
Yulv-git 9074b3e980 Fix some typos in platforms/, samples/, 3rdparty/. 2022-09-07 16:09:23 +03:00
Alexander Smorkalov a72074b33f Merge pull request #22164 from lamm45:hough-angles
Fix angle discretization in Hough transforms
2022-08-31 12:23:52 +03:00
Alexander Smorkalov 7834a465d5 Merge pull request #22443 from catree:feat_calibrate_camera_exe_initial_guess 2022-08-31 07:48:32 +00:00
lamm45 1f0bfc8d83 Fix angle discretization in Hough transforms
In some situations the last value was missing from the discrete theta
values. Now, the last value is chosen such that it is close to the
user-provided maximum theta, while the distance to pi remains always
at least theta_step/2. This should avoid duplicate detections.

A better way would probably be to use max_theta as is and adjust the
resolution (theta_step) instead, such that the discretization would
always be uniform (in a circular sense) when full angle range is used.
2022-08-30 18:46:16 -04:00
catree 837e41f9a7 Add -ws flag for cornerSubPix params (backported from 4.x).
Add flags to set the camera intrinsic parameters as an initial guess (can allow converging to the correct camera intrinsic parameters).
Add -imshow-scale flag to resize the image when displaying the results.
Add -enable-k3 flag to enable or disable the estimation of the K3 distortion coefficient.
2022-08-29 23:55:00 +02:00
Alexander Smorkalov 8eb4f72531 Merge pull request #22425 from AleksandrPanov:qrcode_test_arm
QR code, change resize interpolation for Arm
2022-08-29 10:39:27 +03:00
Alexander Smorkalov 88115811a9 Merge pull request #22130 from catree:homography_tutorial_add_exercise
Update homography tutorial with a small exercise
2022-08-26 12:52:55 +03:00
Alexander Smorkalov eea05f5078 Merge pull request #22412 from asenyaev/asen/carotene_warnings_macos_arm64
Suppress warnings in carotene on macOS ARM64 for 3.4 branch
2022-08-26 09:40:30 +03:00
Andrey Senyaev e1305e8d05 Fixed a warning in case of typename on macOS ARM64 2022-08-25 18:17:03 +03:00
AleksandrPanov 2dd3408caa change resize interpolation to enable tests in arm, disable close_5 2022-08-25 14:27:18 +03:00
Andrey Senyaev ef570e4e13 Suppress warnings in carotene on macOS ARM64 for 3.4 branch 2022-08-22 17:42:22 +03:00
Alexander Smorkalov 56baf4ed87 Merge pull request #22382 from AleksandrPanov:qrcode_x86_arm_34 2022-08-16 13:48:48 +00:00
AleksandrPanov 7ffb103758 QRcode, change INTER_LINEAR to INTER_LINEAR_EXACT
fix python test_detect_and_decode_multi

fix python test_detect_and_decode_multi, sort QR in multiDetect/multiDecode

enable tests with "version_5_up.jpg", "version_5_top.jpg"

remove lambda
2022-08-16 10:24:54 +03:00
Alexander Smorkalov 27bfab4e6e Merge pull request #22371 from kianelbo:patch-1 2022-08-15 09:32:15 +00:00
Alexander Alekhin cc8add9f66 Merge pull request #22370 from catree:fix_22242_filter2d_float_double_doc 2022-08-14 15:04:12 +00:00
Alexander Alekhin d0d115321d Merge pull request #22350 from alalek:rework_psabi_warning 2022-08-13 15:05:41 +00:00
Kian Eliasi 99683e958a Fix the example in py_calib3d/py_calibration 2022-08-12 19:26:59 +04:30
catree 3d8614cb47 Fix documentation about depth combinations for imgproc functions. 2022-08-12 12:53:01 +02:00
Alexander Smorkalov 48afe1586a Merge pull request #22357 from jspricke:missing_header 2022-08-11 09:50:46 +00:00
Jochen Sprickerhof 496eed950f Add missing header for LIBAVCODEC_VERSION_INT 2022-08-08 23:33:28 +02:00
Alexander Alekhin 75bb6aa9a1 build: disable psabi warning with GCC 7.0 and ARM 2022-08-07 15:46:44 +03:00
Alexander Alekhin 44b2f9637a Revert "suppress warning on GCC 7 and later"
This reverts commit a630ad73cb.
2022-08-07 15:43:10 +03:00
Alexander Smorkalov 1893b37e23 Merge pull request #22057 from mohawk2:typos
Typos: cheirality vs chirality
2022-08-03 16:27:46 +03:00
Alexander Smorkalov 2ffa7ac0da Merge pull request #22217 from CSharperMantle:CSharperMantle-patch-steady-clock
Use `std::chrono::steady_clock` in `getTickCount`
2022-08-03 14:09:45 +03:00
Alexander Smorkalov 26ac81df3e Merge pull request #22324 from gmbows:typo_fix 2022-08-02 06:36:34 +00:00
Alexander Smorkalov 1ec10ca565 Merge pull request #22309 from asenyaev:asen/ubuntu14.04_workflow 2022-08-02 06:33:01 +00:00
Alexander Smorkalov 15f0e2e7cb Merge pull request #22317 from asenyaev:asen/docs_3.4 2022-08-02 06:22:25 +00:00
Andrey Senyaev 4c9364a803 Docs workflow in GHA for 3.4 2022-08-01 10:04:57 +03:00
gbowser3@gmail.com e7a787aa41 Imgproc: Fix doxygen typo 2022-07-31 19:22:10 -05:00
Andrey Senyaev 5bf3991f55 Workflow on Ubuntu 14.04 for 3.4 branch 2022-07-27 10:19:34 +03:00
Alexander Alekhin 0862d69a6e Merge pull request #22271 from tomoaki0705:dotprod_neon 2022-07-25 15:00:32 +00:00
Alexander Alekhin 6ce2f1316f Merge pull request #22293 from mshabunin:fix-buffer-area-uas 2022-07-24 10:20:59 +00:00
Alexander Alekhin 294348939b Merge pull request #22296 from alalek:fixup_22153 2022-07-24 10:20:13 +00:00
Alexander Alekhin e2db95184f Merge pull request #22295 from alalek:fixup_22246 2022-07-24 10:16:34 +00:00
Alexander Alekhin f8597fc150 imgproc: fixup leftovers of int->int64_t conversion 2022-07-24 12:39:25 +03:00
Alexander Alekhin 85b0b0cd77 build: add missing GCC condition for pragma 2022-07-24 12:19:37 +03:00
Maksim Shabunin f729202272 core: remove unnecessary pointer cleanup in BufferArea 2022-07-24 11:58:17 +03:00
Alexander Alekhin db53f4533e Merge pull request #22279 from asenyaev:asen/android_3.4 2022-07-22 09:57:44 +00:00
Andrey Senyaev a016f6022c Android GHA workflow for 3.4 branch 2022-07-21 17:47:55 +03:00
Tomoaki Teshima b3269b08a1 neon: add dotprod dispatch implementation
* read vector at runtime
     * add enum
2022-07-20 19:25:39 +09:00
@lizhiyu3 e59cff47d4 fix the right border 2022-07-20 17:03:09 +08:00
Alexander Alekhin 47912431e6 Merge pull request #22269 from asenyaev:asen/fix_python_recursion 2022-07-19 21:41:30 +00:00
Alexander Alekhin 701d0d9905 Merge pull request #22266 from asenyaev:asen/rename_lin_arm_pipelines 2022-07-19 14:23:52 +00:00
Andrey Senyaev 1feabf4275 Fixed an issue with a recursion of cv2 in python 2022-07-19 13:52:29 +03:00
Andrey Senyaev 697acf7f6a Linux ARM64 rename ubuntu version on 3.4 2022-07-19 13:10:12 +03:00
Alexander Alekhin c9e10e1d0b Merge pull request #22225 from scorpiozj:patch-1 2022-07-16 07:40:14 +00:00
scorpiozj bd54ba911d Update imgproc.hpp
fix Rect value of integral image example;
2022-07-15 16:35:12 +08:00
Alexander Alekhin a9354fc743 Merge pull request #22229 from zihaomu:bug_fix_22195_3_4 2022-07-14 20:27:25 +00:00
Alexander Alekhin 1377f0147e Merge pull request #22246 from asenyaev:asen/fix_warning_lnx_arm64_3.4 2022-07-14 11:09:04 +00:00
Andrey Senyaev d2b1e38207 Pragma to ignore -Waggressive-loop-optimizations on Linux ARM64 2022-07-14 11:17:38 +03:00
Alexander Alekhin afe1c70f2d Merge pull request #22228 from CSharperMantle:CSharperMantle-patch-std-shuffle 2022-07-13 06:23:16 +00:00
Zihao Mu 45fbb67aba fix scale layer can not handle 1x1 weight correctly. 2022-07-13 11:25:27 +08:00
Alexander Alekhin 914005174f Merge pull request #22153 from vrabaud:opencv_drawing 2022-07-12 22:23:35 +00:00
Alexander Alekhin 2a82467a6f Merge pull request #22232 from tomoaki0705:dryCmake 2022-07-12 18:46:57 +00:00
Alexander Alekhin a233232b7d Merge pull request #22234 from vrabaud:34_calib 2022-07-12 18:15:25 +00:00
Vincent Rabaud ed4bf13960 Fix cleanFoundConnectedQuads. 2022-07-12 16:24:44 +02:00
Rong Mantle Bao 3135063100 Make objdetect/test C++11-compliant and reproducible
- Add conditional compilation directives to replace deprecated std::random_shuffle with new std::shuffle when C++11 is available.

- Set random seed to a fixed value before shuffling containers to ensure reproducibility.

Resolves opencv/opencv#22209.
2022-07-12 20:18:54 +08:00
Tomoaki Teshima 87ef6a9cc1 build: suppress the warning
DRY
bump the version
2022-07-12 19:42:39 +09:00
Rong Mantle Bao fa613e393f Read CV_CXX11 for C++11 detection 2022-07-10 19:21:17 +08:00
Rong Mantle Bao db70676933 Use cross-platform std::chrono in getTickCount()
Add conditional compilation directives to enable uses of std::chrono on supported compilers. Use std::chrono::steady_clock as a source to retrieve current tick count and clock frequency.

Fixes opencv/opencv#6902.
2022-07-09 10:42:29 +08:00
Alexander Alekhin 70492c2127 Merge pull request #22202 from tomoaki0705:fixWarnings 2022-07-08 13:48:11 +00:00
Vincent Rabaud 0a88f84847 Merge pull request #22208 from vrabaud:34_calibinit
Add missing code.

* Add missing code.

This was removed in c7fc563dc0
The resize is also a side-effect.

* Use shorteer cv::Point2f *=
2022-07-08 01:24:01 +03:00
Tomoaki Teshima a630ad73cb suppress warning on GCC 7 and later 2022-07-06 23:31:31 +09:00
@lizhiyu3 366e8217c2 merge the fixbug 2022-07-06 01:09:46 +08:00
@lizhiyu3 01226cb8ac fix the bug when src*2 < dst 2022-07-06 01:01:16 +08:00
Alexander Alekhin 3891b72f33 Merge pull request #22189 from p12tic:document-calchist-overload 2022-07-05 16:16:20 +00:00
@lizhiyu3 c54ccaac31 change test number 2022-07-05 15:50:33 +08:00
@lizhiyu3 79731cb0ff fix the bug when src*2 < dst 2022-07-05 15:43:52 +08:00
Yuantao Feng 2920a8e0ec Merge pull request #22185 from fengyuentau:ci_job_rename_3.4
Rename jobs for better understanding for branch 3.4

* rename jobs

* remove dots from job names

* correct ubuntu version for linux arm64
2022-07-05 01:45:14 +03:00
Povilas Kanapickas 6a4c3b61e6 Improve doc of calcHist overload that accepts vectors
It's not clear how ranges argument should be used in the overload of
calcHist that accepts std::vector. The main overload uses array of
arrays there, while std::vector overload uses a plain array. The code
interprets the vector as a flattened array and rebuilds array of arrays
from it. This is not obvious interpretation, so documentation has been
added to explain the expected usage.
2022-07-04 12:19:16 +03:00
heavyrain-lzy 6360c3bf46 Merge pull request #22184 from heavyrain-lzy:fixbug_pyrUp
* fix the bug in pyrUp

* add test case for pyrUp

* coding style
2022-07-03 23:06:43 +03:00
Alexander Alekhin e313603aac Merge pull request #22182 from alalek:build_fix_warnings 2022-07-02 19:20:17 +00:00
Alexander Alekhin 0f3de805f4 build: fix warnings 2022-07-02 00:56:10 +03:00
Alexander Alekhin 56e19e3494 Merge pull request #22173 from ycs77:patch-2 2022-07-01 12:14:57 +00:00
Alexander Alekhin 8ae06b4648 Merge pull request #22111 from asenyaev:asen/ios_workflow_3.4 2022-07-01 10:06:15 +00:00
Alexander Alekhin eb7add1828 Merge pull request #22169 from tomoaki0705:OrinCC 2022-06-29 20:41:04 +00:00
Lucas Yang b152b8cbcd Fix missing CharVector for JavaScript bindings 2022-06-30 04:07:43 +08:00
Tomoaki Teshima 2336b0706d add support for Orin GPU 2022-06-29 20:35:27 +09:00
Andrey Senyaev 300b57dd70 Workflow for labeled iOS PRs in 3.4 branch 2022-06-27 21:34:15 +03:00
Alexander Alekhin 5e1c9099e8 Merge pull request #22158 from lamm45:intro-typos 2022-06-26 14:20:22 +00:00
Alexander Alekhin 397e9bc8d6 Merge pull request #22137 from danopdev:issues-22126 2022-06-25 15:21:55 +00:00
dan 2366f2cb2e issues-22126 2022-06-25 15:12:59 +02:00
lamm45 9faefa0c96 Fix minor errors in the first documentation page (Introduction)
This markdown file corresponds to the first link on the landing
page of OpenCV documentation.
2022-06-24 14:03:14 -04:00
Vincent Rabaud 82010bf5c1 Fix some overflows in drawing. 2022-06-24 11:38:20 +02:00
Alexander Alekhin 6234f01a6d Merge pull request #22148 from zihaomu:gemm_onnx_bug_fix_branch34 2022-06-23 22:35:36 +00:00
Zihao Mu ef94275eb6 bug fixed of GEMM node in ONNX_importer 2022-06-22 21:08:48 +08:00
Kumataro dd7b9000ad Merge pull request #22064 from Kumataro:3.4-fix22052
* imgcodecs: jpeg: add IMWRITE_JPEG_SAMPLING_FACTOR parameter

* fix compile error

* imgcodecs: jpeg: add CV_LOG_WARNING() and fix how to initilize Mat

* imgcodecs: jpeg: fix for C++98 mode.

* samples: imgcodec_jpeg: Remove license
2022-06-20 21:42:50 +03:00
catree f1328c7395 Add a small exercise to show the warping of the homography transformations step-by-step. 2022-06-19 22:59:50 +02:00
Alexander Alekhin 9d06e58c3c Merge pull request #22127 from catree:update_homography_tutorial 2022-06-19 10:52:52 +00:00
Alexander Alekhin 711b136191 Merge pull request #22124 from vrabaud:3.4_sanitizer 2022-06-19 10:51:36 +00:00
catree a04f9e7a59 Add more references. Update missing references with webarchive. Use mathbf for matrices. Check that the determinant of the rotation matrix is not negative (reflection), and correct it if it is the case. 2022-06-19 01:27:32 +02:00
Christine Poerschke db5b22e895 Merge pull request #22065 from cpoerschke:3.4-apps-visualisation-configurable-codec
* apps/opencv_visualisation: configurable video codec

* Update apps/visualisation/opencv_visualisation.cpp
2022-06-17 14:48:30 +03:00
Vincent Rabaud 0d52c37e11 Fix typo that prevents compilation with sanitizer. 2022-06-17 11:40:22 +02:00
Alexander Alekhin 3efc645975 Merge pull request #22103 from fengyuentau:macOS_workflows_for_3.4 2022-06-15 18:32:26 +00:00
fengyuentau 572812217b re-commit: add workflows for macOS for 3.4 2022-06-15 18:25:35 +08:00
Alexander Alekhin ff41fbc5c1 Merge pull request #22091 from mukai1011:3.4 2022-06-14 21:35:08 +00:00
Alexander Alekhin cac864192c Merge pull request #22080 from vrabaud:fix_arm 2022-06-13 18:17:24 +00:00
Vincent Rabaud 7a46d7efde Fix compilation on some ARM architecture.
This condition is the same as the line above.
2022-06-13 17:39:24 +02:00
Kôtaro Mukai ed9524e125 Missing import 2022-06-11 18:42:30 +09:00
Alexander Alekhin c103b63fe1 Merge tag '3.4.18' 2022-06-05 15:16:54 +00:00
Alexander Alekhin a3d0882317 release: OpenCV 3.4.18 2022-06-05 07:52:44 +00:00
Ed J f28e191d70 cheirality -> chirality 2022-06-01 00:54:44 +01:00
Ed J 38b6c44b4c for then given -> for the given 2022-06-01 00:54:44 +01:00
182 changed files with 2998 additions and 945 deletions
+22 -4
View File
@@ -6,11 +6,29 @@ on:
- 3.4
jobs:
ARM64:
Ubuntu2004-ARM64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-ARM64.yaml@main
U20:
Ubuntu1404-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-U14.yaml@main
Ubuntu2004-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-U20.yaml@main
W10:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-W10.yaml@main
Windows10-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-W10.yaml@main
macOS-ARM64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-macOS-ARM64.yaml@main
macOS-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-macOS-x86_64.yaml@main
iOS:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-iOS.yaml@main
Android:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-Android.yaml@main
docs:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-3.4-docs.yaml@main
+5 -1
View File
@@ -1,4 +1,4 @@
cmake_minimum_required(VERSION 2.8.11 FATAL_ERROR)
cmake_minimum_required(VERSION ${MIN_VER_CMAKE} FATAL_ERROR)
project(Carotene)
@@ -27,6 +27,10 @@ if(CMAKE_COMPILER_IS_GNUCC)
endif()
endif()
if(APPLE AND CV_CLANG AND WITH_NEON)
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wno-unused-function)
endif()
add_library(carotene_objs OBJECT EXCLUDE_FROM_ALL
${carotene_headers}
${carotene_sources}
+1 -1
View File
@@ -1,4 +1,4 @@
cmake_minimum_required(VERSION 2.8.8 FATAL_ERROR)
cmake_minimum_required(VERSION ${MIN_VER_CMAKE} FATAL_ERROR)
include(CheckCCompilerFlag)
include(CheckCXXCompilerFlag)
+2 -2
View File
@@ -1296,13 +1296,13 @@ struct MorphCtx
CAROTENE_NS::BORDER_MODE border;
uchar borderValues[4];
};
inline int TEGRA_MORPHINIT(cvhalFilter2D **context, int operation, int src_type, int dst_type, int, int,
inline int TEGRA_MORPHINIT(cvhalFilter2D **context, int operation, int src_type, int dst_type, int width, int height,
int kernel_type, uchar *kernel_data, size_t kernel_step, int kernel_width, int kernel_height, int anchor_x, int anchor_y,
int borderType, const double borderValue[4], int iterations, bool allowSubmatrix, bool allowInplace)
{
if(!context || !kernel_data || src_type != dst_type ||
CV_MAT_DEPTH(src_type) != CV_8U || src_type < 0 || (src_type >> CV_CN_SHIFT) > 3 ||
width < kernel_width || height < kernel_height ||
allowSubmatrix || allowInplace || iterations != 1 ||
!CAROTENE_NS::isSupportedConfiguration())
return CV_HAL_ERROR_NOT_IMPLEMENTED;
+18 -18
View File
@@ -109,9 +109,9 @@ template <> struct wAdd<s32>
vgamma = vdupq_n_f32(_gamma + 0.5);
}
void operator() (const typename VecTraits<s32>::vec128 & v_src0,
const typename VecTraits<s32>::vec128 & v_src1,
typename VecTraits<s32>::vec128 & v_dst) const
void operator() (const VecTraits<s32>::vec128 & v_src0,
const VecTraits<s32>::vec128 & v_src1,
VecTraits<s32>::vec128 & v_dst) const
{
float32x4_t vs1 = vcvtq_f32_s32(v_src0);
float32x4_t vs2 = vcvtq_f32_s32(v_src1);
@@ -121,9 +121,9 @@ template <> struct wAdd<s32>
v_dst = vcvtq_s32_f32(vs1);
}
void operator() (const typename VecTraits<s32>::vec64 & v_src0,
const typename VecTraits<s32>::vec64 & v_src1,
typename VecTraits<s32>::vec64 & v_dst) const
void operator() (const VecTraits<s32>::vec64 & v_src0,
const VecTraits<s32>::vec64 & v_src1,
VecTraits<s32>::vec64 & v_dst) const
{
float32x2_t vs1 = vcvt_f32_s32(v_src0);
float32x2_t vs2 = vcvt_f32_s32(v_src1);
@@ -153,9 +153,9 @@ template <> struct wAdd<u32>
vgamma = vdupq_n_f32(_gamma + 0.5);
}
void operator() (const typename VecTraits<u32>::vec128 & v_src0,
const typename VecTraits<u32>::vec128 & v_src1,
typename VecTraits<u32>::vec128 & v_dst) const
void operator() (const VecTraits<u32>::vec128 & v_src0,
const VecTraits<u32>::vec128 & v_src1,
VecTraits<u32>::vec128 & v_dst) const
{
float32x4_t vs1 = vcvtq_f32_u32(v_src0);
float32x4_t vs2 = vcvtq_f32_u32(v_src1);
@@ -165,9 +165,9 @@ template <> struct wAdd<u32>
v_dst = vcvtq_u32_f32(vs1);
}
void operator() (const typename VecTraits<u32>::vec64 & v_src0,
const typename VecTraits<u32>::vec64 & v_src1,
typename VecTraits<u32>::vec64 & v_dst) const
void operator() (const VecTraits<u32>::vec64 & v_src0,
const VecTraits<u32>::vec64 & v_src1,
VecTraits<u32>::vec64 & v_dst) const
{
float32x2_t vs1 = vcvt_f32_u32(v_src0);
float32x2_t vs2 = vcvt_f32_u32(v_src1);
@@ -197,17 +197,17 @@ template <> struct wAdd<f32>
vgamma = vdupq_n_f32(_gamma + 0.5);
}
void operator() (const typename VecTraits<f32>::vec128 & v_src0,
const typename VecTraits<f32>::vec128 & v_src1,
typename VecTraits<f32>::vec128 & v_dst) const
void operator() (const VecTraits<f32>::vec128 & v_src0,
const VecTraits<f32>::vec128 & v_src1,
VecTraits<f32>::vec128 & v_dst) const
{
float32x4_t vs1 = vmlaq_f32(vgamma, v_src0, valpha);
v_dst = vmlaq_f32(vs1, v_src1, vbeta);
}
void operator() (const typename VecTraits<f32>::vec64 & v_src0,
const typename VecTraits<f32>::vec64 & v_src1,
typename VecTraits<f32>::vec64 & v_dst) const
void operator() (const VecTraits<f32>::vec64 & v_src0,
const VecTraits<f32>::vec64 & v_src1,
VecTraits<f32>::vec64 & v_dst) const
{
float32x2_t vs1 = vmla_f32(vget_low(vgamma), v_src0, vget_low(valpha));
v_dst = vmla_f32(vs1, v_src1, vget_low(vbeta));
+1
View File
@@ -119,6 +119,7 @@ ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4334) # vs2005 Win64
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4244) # vs2008
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4267) # vs2008 Win64
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4456) # vs2015
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4819) # vs2019 Win64
if(MSVC AND CV_ICC)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /Qrestrict")
+1 -1
View File
@@ -102,4 +102,4 @@ if(NOT BUILD_SHARED_LIBS)
ocv_install_target(${ZLIB_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
endif()
ocv_install_3rdparty_licenses(zlib README)
ocv_install_3rdparty_licenses(zlib LICENSE)
+18 -6
View File
@@ -1,6 +1,18 @@
ChangeLog file for zlib
Changes in 1.2.13 (13 Oct 2022)
- Fix configure issue that discarded provided CC definition
- Correct incorrect inputs provided to the CRC functions
- Repair prototypes and exporting of new CRC functions
- Fix inflateBack to detect invalid input with distances too far
- Have infback() deliver all of the available output up to any error
- Fix a bug when getting a gzip header extra field with inflate()
- Fix bug in block type selection when Z_FIXED used
- Tighten deflateBound bounds
- Remove deleted assembler code references
- Various portability and appearance improvements
Changes in 1.2.12 (27 Mar 2022)
- Cygwin does not have _wopen(), so do not create gzopen_w() there
- Permit a deflateParams() parameter change as soon as possible
@@ -159,7 +171,7 @@ Changes in 1.2.7.1 (24 Mar 2013)
- Fix types in contrib/minizip to match result of get_crc_table()
- Simplify contrib/vstudio/vc10 with 'd' suffix
- Add TOP support to win32/Makefile.msc
- Suport i686 and amd64 assembler builds in CMakeLists.txt
- Support i686 and amd64 assembler builds in CMakeLists.txt
- Fix typos in the use of _LARGEFILE64_SOURCE in zconf.h
- Add vc11 and vc12 build files to contrib/vstudio
- Add gzvprintf() as an undocumented function in zlib
@@ -359,14 +371,14 @@ Changes in 1.2.5.1 (10 Sep 2011)
- Use u4 type for crc_table to avoid conversion warnings
- Apply casts in zlib.h to avoid conversion warnings
- Add OF to prototypes for adler32_combine_ and crc32_combine_ [Miller]
- Improve inflateSync() documentation to note indeterminancy
- Improve inflateSync() documentation to note indeterminacy
- Add deflatePending() function to return the amount of pending output
- Correct the spelling of "specification" in FAQ [Randers-Pehrson]
- Add a check in configure for stdarg.h, use for gzprintf()
- Check that pointers fit in ints when gzprint() compiled old style
- Add dummy name before $(SHAREDLIBV) in Makefile [Bar-Lev, Bowler]
- Delete line in configure that adds -L. libz.a to LDFLAGS [Weigelt]
- Add debug records in assmebler code [Londer]
- Add debug records in assembler code [Londer]
- Update RFC references to use http://tools.ietf.org/html/... [Li]
- Add --archs option, use of libtool to configure for Mac OS X [Borstel]
@@ -1033,7 +1045,7 @@ Changes in 1.2.0.1 (17 March 2003)
- Include additional header file on VMS for off_t typedef
- Try to use _vsnprintf where it supplants vsprintf [Vollant]
- Add some casts in inffast.c
- Enchance comments in zlib.h on what happens if gzprintf() tries to
- Enhance comments in zlib.h on what happens if gzprintf() tries to
write more than 4095 bytes before compression
- Remove unused state from inflateBackEnd()
- Remove exit(0) from minigzip.c, example.c
@@ -1211,7 +1223,7 @@ Changes in 1.0.9 (17 Feb 1998)
- Avoid gcc 2.8.0 comparison bug a little differently than zlib 1.0.8
- in inftrees.c, avoid cc -O bug on HP (Farshid Elahi)
- in zconf.h move the ZLIB_DLL stuff earlier to avoid problems with
the declaration of FAR (Gilles VOllant)
the declaration of FAR (Gilles Vollant)
- install libz.so* with mode 755 (executable) instead of 644 (Marc Lehmann)
- read_buf buf parameter of type Bytef* instead of charf*
- zmemcpy parameters are of type Bytef*, not charf* (Joseph Strout)
@@ -1567,7 +1579,7 @@ Changes in 0.4:
- renamed deflateOptions as deflateInit2, call one or the other but not both
- added the method parameter for deflateInit2
- added inflateInit2
- simplied considerably deflateInit and inflateInit by not supporting
- simplified considerably deflateInit and inflateInit by not supporting
user-provided history buffer. This is supported only in deflateInit2
and inflateInit2
+22
View File
@@ -0,0 +1,22 @@
Copyright notice:
(C) 1995-2022 Jean-loup Gailly and Mark Adler
This software is provided 'as-is', without any express or implied
warranty. In no event will the authors be held liable for any damages
arising from the use of this software.
Permission is granted to anyone to use this software for any purpose,
including commercial applications, and to alter it and redistribute it
freely, subject to the following restrictions:
1. The origin of this software must not be misrepresented; you must not
claim that you wrote the original software. If you use this software
in a product, an acknowledgment in the product documentation would be
appreciated but is not required.
2. Altered source versions must be plainly marked as such, and must not be
misrepresented as being the original software.
3. This notice may not be removed or altered from any source distribution.
Jean-loup Gailly Mark Adler
jloup@gzip.org madler@alumni.caltech.edu
+2 -2
View File
@@ -1,6 +1,6 @@
ZLIB DATA COMPRESSION LIBRARY
zlib 1.2.12 is a general purpose data compression library. All the code is
zlib 1.2.13 is a general purpose data compression library. All the code is
thread safe. The data format used by the zlib library is described by RFCs
(Request for Comments) 1950 to 1952 in the files
http://tools.ietf.org/html/rfc1950 (zlib format), rfc1951 (deflate format) and
@@ -31,7 +31,7 @@ Mark Nelson <markn@ieee.org> wrote an article about zlib for the Jan. 1997
issue of Dr. Dobb's Journal; a copy of the article is available at
http://marknelson.us/1997/01/01/zlib-engine/ .
The changes made in version 1.2.12 are documented in the file ChangeLog.
The changes made in version 1.2.13 are documented in the file ChangeLog.
Unsupported third party contributions are provided in directory contrib/ .
+3 -3
View File
@@ -19,7 +19,7 @@
memory, Z_BUF_ERROR if there was not enough room in the output buffer,
Z_STREAM_ERROR if the level parameter is invalid.
*/
int ZEXPORT compress2 (dest, destLen, source, sourceLen, level)
int ZEXPORT compress2(dest, destLen, source, sourceLen, level)
Bytef *dest;
uLongf *destLen;
const Bytef *source;
@@ -65,7 +65,7 @@ int ZEXPORT compress2 (dest, destLen, source, sourceLen, level)
/* ===========================================================================
*/
int ZEXPORT compress (dest, destLen, source, sourceLen)
int ZEXPORT compress(dest, destLen, source, sourceLen)
Bytef *dest;
uLongf *destLen;
const Bytef *source;
@@ -78,7 +78,7 @@ int ZEXPORT compress (dest, destLen, source, sourceLen)
If the default memLevel or windowBits for deflateInit() is changed, then
this function needs to be updated.
*/
uLong ZEXPORT compressBound (sourceLen)
uLong ZEXPORT compressBound(sourceLen)
uLong sourceLen;
{
return sourceLen + (sourceLen >> 12) + (sourceLen >> 14) +
+21 -12
View File
@@ -98,13 +98,22 @@
# endif
#endif
/* If available, use the ARM processor CRC32 instruction. */
#if defined(__aarch64__) && defined(__ARM_FEATURE_CRC32) && W == 8
# define ARMCRC32
#endif
/* Local functions. */
local z_crc_t multmodp OF((z_crc_t a, z_crc_t b));
local z_crc_t x2nmodp OF((z_off64_t n, unsigned k));
/* If available, use the ARM processor CRC32 instruction. */
#if defined(__aarch64__) && defined(__ARM_FEATURE_CRC32) && W == 8
# define ARMCRC32
#if defined(W) && (!defined(ARMCRC32) || defined(DYNAMIC_CRC_TABLE))
local z_word_t byte_swap OF((z_word_t word));
#endif
#if defined(W) && !defined(ARMCRC32)
local z_crc_t crc_word OF((z_word_t data));
local z_word_t crc_word_big OF((z_word_t data));
#endif
#if defined(W) && (!defined(ARMCRC32) || defined(DYNAMIC_CRC_TABLE))
@@ -630,7 +639,7 @@ unsigned long ZEXPORT crc32_z(crc, buf, len)
#endif /* DYNAMIC_CRC_TABLE */
/* Pre-condition the CRC */
crc ^= 0xffffffff;
crc = (~crc) & 0xffffffff;
/* Compute the CRC up to a word boundary. */
while (len && ((z_size_t)buf & 7) != 0) {
@@ -645,8 +654,8 @@ unsigned long ZEXPORT crc32_z(crc, buf, len)
len &= 7;
/* Do three interleaved CRCs to realize the throughput of one crc32x
instruction per cycle. Each CRC is calcuated on Z_BATCH words. The three
CRCs are combined into a single CRC after each set of batches. */
instruction per cycle. Each CRC is calculated on Z_BATCH words. The
three CRCs are combined into a single CRC after each set of batches. */
while (num >= 3 * Z_BATCH) {
crc1 = 0;
crc2 = 0;
@@ -749,7 +758,7 @@ unsigned long ZEXPORT crc32_z(crc, buf, len)
#endif /* DYNAMIC_CRC_TABLE */
/* Pre-condition the CRC */
crc ^= 0xffffffff;
crc = (~crc) & 0xffffffff;
#ifdef W
@@ -1077,7 +1086,7 @@ uLong ZEXPORT crc32_combine64(crc1, crc2, len2)
#ifdef DYNAMIC_CRC_TABLE
once(&made, make_crc_table);
#endif /* DYNAMIC_CRC_TABLE */
return multmodp(x2nmodp(len2, 3), crc1) ^ crc2;
return multmodp(x2nmodp(len2, 3), crc1) ^ (crc2 & 0xffffffff);
}
/* ========================================================================= */
@@ -1086,7 +1095,7 @@ uLong ZEXPORT crc32_combine(crc1, crc2, len2)
uLong crc2;
z_off_t len2;
{
return crc32_combine64(crc1, crc2, len2);
return crc32_combine64(crc1, crc2, (z_off64_t)len2);
}
/* ========================================================================= */
@@ -1103,14 +1112,14 @@ uLong ZEXPORT crc32_combine_gen64(len2)
uLong ZEXPORT crc32_combine_gen(len2)
z_off_t len2;
{
return crc32_combine_gen64(len2);
return crc32_combine_gen64((z_off64_t)len2);
}
/* ========================================================================= */
uLong crc32_combine_op(crc1, crc2, op)
uLong ZEXPORT crc32_combine_op(crc1, crc2, op)
uLong crc1;
uLong crc2;
uLong op;
{
return multmodp(op, crc1) ^ crc2;
return multmodp(op, crc1) ^ (crc2 & 0xffffffff);
}
+112 -106
View File
@@ -52,7 +52,7 @@
#include "deflate.h"
const char deflate_copyright[] =
" deflate 1.2.12 Copyright 1995-2022 Jean-loup Gailly and Mark Adler ";
" deflate 1.2.13 Copyright 1995-2022 Jean-loup Gailly and Mark Adler ";
/*
If you use the zlib library in a product, an acknowledgment is welcome
in the documentation of your product. If for some reason you cannot
@@ -87,13 +87,7 @@ local void lm_init OF((deflate_state *s));
local void putShortMSB OF((deflate_state *s, uInt b));
local void flush_pending OF((z_streamp strm));
local unsigned read_buf OF((z_streamp strm, Bytef *buf, unsigned size));
#ifdef ASMV
# pragma message("Assembler code may have bugs -- use at your own risk")
void match_init OF((void)); /* asm code initialization */
uInt longest_match OF((deflate_state *s, IPos cur_match));
#else
local uInt longest_match OF((deflate_state *s, IPos cur_match));
#endif
#ifdef ZLIB_DEBUG
local void check_match OF((deflate_state *s, IPos start, IPos match,
@@ -160,7 +154,7 @@ local const config configuration_table[10] = {
* characters, so that a running hash key can be computed from the previous
* key instead of complete recalculation each time.
*/
#define UPDATE_HASH(s,h,c) (h = (((h)<<s->hash_shift) ^ (c)) & s->hash_mask)
#define UPDATE_HASH(s,h,c) (h = (((h) << s->hash_shift) ^ (c)) & s->hash_mask)
/* ===========================================================================
@@ -191,9 +185,9 @@ local const config configuration_table[10] = {
*/
#define CLEAR_HASH(s) \
do { \
s->head[s->hash_size-1] = NIL; \
s->head[s->hash_size - 1] = NIL; \
zmemzero((Bytef *)s->head, \
(unsigned)(s->hash_size-1)*sizeof(*s->head)); \
(unsigned)(s->hash_size - 1)*sizeof(*s->head)); \
} while (0)
/* ===========================================================================
@@ -285,6 +279,8 @@ int ZEXPORT deflateInit2_(strm, level, method, windowBits, memLevel, strategy,
if (windowBits < 0) { /* suppress zlib wrapper */
wrap = 0;
if (windowBits < -15)
return Z_STREAM_ERROR;
windowBits = -windowBits;
}
#ifdef GZIP
@@ -314,7 +310,7 @@ int ZEXPORT deflateInit2_(strm, level, method, windowBits, memLevel, strategy,
s->hash_bits = (uInt)memLevel + 7;
s->hash_size = 1 << s->hash_bits;
s->hash_mask = s->hash_size - 1;
s->hash_shift = ((s->hash_bits+MIN_MATCH-1)/MIN_MATCH);
s->hash_shift = ((s->hash_bits + MIN_MATCH-1) / MIN_MATCH);
s->window = (Bytef *) ZALLOC(strm, s->w_size, 2*sizeof(Byte));
s->prev = (Posf *) ZALLOC(strm, s->w_size, sizeof(Pos));
@@ -340,11 +336,11 @@ int ZEXPORT deflateInit2_(strm, level, method, windowBits, memLevel, strategy,
* sym_buf value to read moves forward three bytes. From that symbol, up to
* 31 bits are written to pending_buf. The closest the written pending_buf
* bits gets to the next sym_buf symbol to read is just before the last
* code is written. At that time, 31*(n-2) bits have been written, just
* after 24*(n-2) bits have been consumed from sym_buf. sym_buf starts at
* 8*n bits into pending_buf. (Note that the symbol buffer fills when n-1
* code is written. At that time, 31*(n - 2) bits have been written, just
* after 24*(n - 2) bits have been consumed from sym_buf. sym_buf starts at
* 8*n bits into pending_buf. (Note that the symbol buffer fills when n - 1
* symbols are written.) The closest the writing gets to what is unread is
* then n+14 bits. Here n is lit_bufsize, which is 16384 by default, and
* then n + 14 bits. Here n is lit_bufsize, which is 16384 by default, and
* can range from 128 to 32768.
*
* Therefore, at a minimum, there are 142 bits of space between what is
@@ -390,7 +386,7 @@ int ZEXPORT deflateInit2_(strm, level, method, windowBits, memLevel, strategy,
/* =========================================================================
* Check for a valid deflate stream state. Return 0 if ok, 1 if not.
*/
local int deflateStateCheck (strm)
local int deflateStateCheck(strm)
z_streamp strm;
{
deflate_state *s;
@@ -413,7 +409,7 @@ local int deflateStateCheck (strm)
}
/* ========================================================================= */
int ZEXPORT deflateSetDictionary (strm, dictionary, dictLength)
int ZEXPORT deflateSetDictionary(strm, dictionary, dictLength)
z_streamp strm;
const Bytef *dictionary;
uInt dictLength;
@@ -482,7 +478,7 @@ int ZEXPORT deflateSetDictionary (strm, dictionary, dictLength)
}
/* ========================================================================= */
int ZEXPORT deflateGetDictionary (strm, dictionary, dictLength)
int ZEXPORT deflateGetDictionary(strm, dictionary, dictLength)
z_streamp strm;
Bytef *dictionary;
uInt *dictLength;
@@ -504,7 +500,7 @@ int ZEXPORT deflateGetDictionary (strm, dictionary, dictLength)
}
/* ========================================================================= */
int ZEXPORT deflateResetKeep (strm)
int ZEXPORT deflateResetKeep(strm)
z_streamp strm;
{
deflate_state *s;
@@ -542,7 +538,7 @@ int ZEXPORT deflateResetKeep (strm)
}
/* ========================================================================= */
int ZEXPORT deflateReset (strm)
int ZEXPORT deflateReset(strm)
z_streamp strm;
{
int ret;
@@ -554,7 +550,7 @@ int ZEXPORT deflateReset (strm)
}
/* ========================================================================= */
int ZEXPORT deflateSetHeader (strm, head)
int ZEXPORT deflateSetHeader(strm, head)
z_streamp strm;
gz_headerp head;
{
@@ -565,7 +561,7 @@ int ZEXPORT deflateSetHeader (strm, head)
}
/* ========================================================================= */
int ZEXPORT deflatePending (strm, pending, bits)
int ZEXPORT deflatePending(strm, pending, bits)
unsigned *pending;
int *bits;
z_streamp strm;
@@ -579,7 +575,7 @@ int ZEXPORT deflatePending (strm, pending, bits)
}
/* ========================================================================= */
int ZEXPORT deflatePrime (strm, bits, value)
int ZEXPORT deflatePrime(strm, bits, value)
z_streamp strm;
int bits;
int value;
@@ -674,36 +670,50 @@ int ZEXPORT deflateTune(strm, good_length, max_lazy, nice_length, max_chain)
}
/* =========================================================================
* For the default windowBits of 15 and memLevel of 8, this function returns
* a close to exact, as well as small, upper bound on the compressed size.
* They are coded as constants here for a reason--if the #define's are
* changed, then this function needs to be changed as well. The return
* value for 15 and 8 only works for those exact settings.
* For the default windowBits of 15 and memLevel of 8, this function returns a
* close to exact, as well as small, upper bound on the compressed size. This
* is an expansion of ~0.03%, plus a small constant.
*
* For any setting other than those defaults for windowBits and memLevel,
* the value returned is a conservative worst case for the maximum expansion
* resulting from using fixed blocks instead of stored blocks, which deflate
* can emit on compressed data for some combinations of the parameters.
* For any setting other than those defaults for windowBits and memLevel, one
* of two worst case bounds is returned. This is at most an expansion of ~4% or
* ~13%, plus a small constant.
*
* This function could be more sophisticated to provide closer upper bounds for
* every combination of windowBits and memLevel. But even the conservative
* upper bound of about 14% expansion does not seem onerous for output buffer
* allocation.
* Both the 0.03% and 4% derive from the overhead of stored blocks. The first
* one is for stored blocks of 16383 bytes (memLevel == 8), whereas the second
* is for stored blocks of 127 bytes (the worst case memLevel == 1). The
* expansion results from five bytes of header for each stored block.
*
* The larger expansion of 13% results from a window size less than or equal to
* the symbols buffer size (windowBits <= memLevel + 7). In that case some of
* the data being compressed may have slid out of the sliding window, impeding
* a stored block from being emitted. Then the only choice is a fixed or
* dynamic block, where a fixed block limits the maximum expansion to 9 bits
* per 8-bit byte, plus 10 bits for every block. The smallest block size for
* which this can occur is 255 (memLevel == 2).
*
* Shifts are used to approximate divisions, for speed.
*/
uLong ZEXPORT deflateBound(strm, sourceLen)
z_streamp strm;
uLong sourceLen;
{
deflate_state *s;
uLong complen, wraplen;
uLong fixedlen, storelen, wraplen;
/* conservative upper bound for compressed data */
complen = sourceLen +
((sourceLen + 7) >> 3) + ((sourceLen + 63) >> 6) + 5;
/* upper bound for fixed blocks with 9-bit literals and length 255
(memLevel == 2, which is the lowest that may not use stored blocks) --
~13% overhead plus a small constant */
fixedlen = sourceLen + (sourceLen >> 3) + (sourceLen >> 8) +
(sourceLen >> 9) + 4;
/* if can't get parameters, return conservative bound plus zlib wrapper */
/* upper bound for stored blocks with length 127 (memLevel == 1) --
~4% overhead plus a small constant */
storelen = sourceLen + (sourceLen >> 5) + (sourceLen >> 7) +
(sourceLen >> 11) + 7;
/* if can't get parameters, return larger bound plus a zlib wrapper */
if (deflateStateCheck(strm))
return complen + 6;
return (fixedlen > storelen ? fixedlen : storelen) + 6;
/* compute wrapper length */
s = strm->state;
@@ -740,11 +750,12 @@ uLong ZEXPORT deflateBound(strm, sourceLen)
wraplen = 6;
}
/* if not default parameters, return conservative bound */
/* if not default parameters, return one of the conservative bounds */
if (s->w_bits != 15 || s->hash_bits != 8 + 7)
return complen + wraplen;
return (s->w_bits <= s->hash_bits ? fixedlen : storelen) + wraplen;
/* default settings: return tight bound for that case */
/* default settings: return tight bound for that case -- ~0.03% overhead
plus a small constant */
return sourceLen + (sourceLen >> 12) + (sourceLen >> 14) +
(sourceLen >> 25) + 13 - 6 + wraplen;
}
@@ -754,7 +765,7 @@ uLong ZEXPORT deflateBound(strm, sourceLen)
* IN assertion: the stream state is correct and there is enough room in
* pending_buf.
*/
local void putShortMSB (s, b)
local void putShortMSB(s, b)
deflate_state *s;
uInt b;
{
@@ -801,7 +812,7 @@ local void flush_pending(strm)
} while (0)
/* ========================================================================= */
int ZEXPORT deflate (strm, flush)
int ZEXPORT deflate(strm, flush)
z_streamp strm;
int flush;
{
@@ -856,7 +867,7 @@ int ZEXPORT deflate (strm, flush)
s->status = BUSY_STATE;
if (s->status == INIT_STATE) {
/* zlib header */
uInt header = (Z_DEFLATED + ((s->w_bits-8)<<4)) << 8;
uInt header = (Z_DEFLATED + ((s->w_bits - 8) << 4)) << 8;
uInt level_flags;
if (s->strategy >= Z_HUFFMAN_ONLY || s->level < 2)
@@ -1116,7 +1127,7 @@ int ZEXPORT deflate (strm, flush)
}
/* ========================================================================= */
int ZEXPORT deflateEnd (strm)
int ZEXPORT deflateEnd(strm)
z_streamp strm;
{
int status;
@@ -1142,7 +1153,7 @@ int ZEXPORT deflateEnd (strm)
* To simplify the source, this is not supported for 16-bit MSDOS (which
* doesn't have enough memory anyway to duplicate compression states).
*/
int ZEXPORT deflateCopy (dest, source)
int ZEXPORT deflateCopy(dest, source)
z_streamp dest;
z_streamp source;
{
@@ -1231,7 +1242,7 @@ local unsigned read_buf(strm, buf, size)
/* ===========================================================================
* Initialize the "longest match" routines for a new zlib stream
*/
local void lm_init (s)
local void lm_init(s)
deflate_state *s;
{
s->window_size = (ulg)2L*s->w_size;
@@ -1252,11 +1263,6 @@ local void lm_init (s)
s->match_length = s->prev_length = MIN_MATCH-1;
s->match_available = 0;
s->ins_h = 0;
#ifndef FASTEST
#ifdef ASMV
match_init(); /* initialize the asm code */
#endif
#endif
}
#ifndef FASTEST
@@ -1269,10 +1275,6 @@ local void lm_init (s)
* string (strstart) and its distance is <= MAX_DIST, and prev_length >= 1
* OUT assertion: the match length is not greater than s->lookahead.
*/
#ifndef ASMV
/* For 80x86 and 680x0, an optimized version will be provided in match.asm or
* match.S. The code will be functionally equivalent.
*/
local uInt longest_match(s, cur_match)
deflate_state *s;
IPos cur_match; /* current match */
@@ -1297,10 +1299,10 @@ local uInt longest_match(s, cur_match)
*/
register Bytef *strend = s->window + s->strstart + MAX_MATCH - 1;
register ush scan_start = *(ushf*)scan;
register ush scan_end = *(ushf*)(scan+best_len-1);
register ush scan_end = *(ushf*)(scan + best_len - 1);
#else
register Bytef *strend = s->window + s->strstart + MAX_MATCH;
register Byte scan_end1 = scan[best_len-1];
register Byte scan_end1 = scan[best_len - 1];
register Byte scan_end = scan[best_len];
#endif
@@ -1318,7 +1320,8 @@ local uInt longest_match(s, cur_match)
*/
if ((uInt)nice_match > s->lookahead) nice_match = (int)s->lookahead;
Assert((ulg)s->strstart <= s->window_size-MIN_LOOKAHEAD, "need lookahead");
Assert((ulg)s->strstart <= s->window_size - MIN_LOOKAHEAD,
"need lookahead");
do {
Assert(cur_match < s->strstart, "no future");
@@ -1336,43 +1339,44 @@ local uInt longest_match(s, cur_match)
/* This code assumes sizeof(unsigned short) == 2. Do not use
* UNALIGNED_OK if your compiler uses a different size.
*/
if (*(ushf*)(match+best_len-1) != scan_end ||
if (*(ushf*)(match + best_len - 1) != scan_end ||
*(ushf*)match != scan_start) continue;
/* It is not necessary to compare scan[2] and match[2] since they are
* always equal when the other bytes match, given that the hash keys
* are equal and that HASH_BITS >= 8. Compare 2 bytes at a time at
* strstart+3, +5, ... up to strstart+257. We check for insufficient
* strstart + 3, + 5, up to strstart + 257. We check for insufficient
* lookahead only every 4th comparison; the 128th check will be made
* at strstart+257. If MAX_MATCH-2 is not a multiple of 8, it is
* at strstart + 257. If MAX_MATCH-2 is not a multiple of 8, it is
* necessary to put more guard bytes at the end of the window, or
* to check more often for insufficient lookahead.
*/
Assert(scan[2] == match[2], "scan[2]?");
scan++, match++;
do {
} while (*(ushf*)(scan+=2) == *(ushf*)(match+=2) &&
*(ushf*)(scan+=2) == *(ushf*)(match+=2) &&
*(ushf*)(scan+=2) == *(ushf*)(match+=2) &&
*(ushf*)(scan+=2) == *(ushf*)(match+=2) &&
} while (*(ushf*)(scan += 2) == *(ushf*)(match += 2) &&
*(ushf*)(scan += 2) == *(ushf*)(match += 2) &&
*(ushf*)(scan += 2) == *(ushf*)(match += 2) &&
*(ushf*)(scan += 2) == *(ushf*)(match += 2) &&
scan < strend);
/* The funny "do {}" generates better code on most compilers */
/* Here, scan <= window+strstart+257 */
Assert(scan <= s->window+(unsigned)(s->window_size-1), "wild scan");
/* Here, scan <= window + strstart + 257 */
Assert(scan <= s->window + (unsigned)(s->window_size - 1),
"wild scan");
if (*scan == *match) scan++;
len = (MAX_MATCH - 1) - (int)(strend-scan);
len = (MAX_MATCH - 1) - (int)(strend - scan);
scan = strend - (MAX_MATCH-1);
#else /* UNALIGNED_OK */
if (match[best_len] != scan_end ||
match[best_len-1] != scan_end1 ||
*match != *scan ||
*++match != scan[1]) continue;
if (match[best_len] != scan_end ||
match[best_len - 1] != scan_end1 ||
*match != *scan ||
*++match != scan[1]) continue;
/* The check at best_len-1 can be removed because it will be made
/* The check at best_len - 1 can be removed because it will be made
* again later. (This heuristic is not always a win.)
* It is not necessary to compare scan[2] and match[2] since they
* are always equal when the other bytes match, given that
@@ -1382,7 +1386,7 @@ local uInt longest_match(s, cur_match)
Assert(*scan == *match, "match[2]?");
/* We check for insufficient lookahead only every 8th comparison;
* the 256th check will be made at strstart+258.
* the 256th check will be made at strstart + 258.
*/
do {
} while (*++scan == *++match && *++scan == *++match &&
@@ -1391,7 +1395,8 @@ local uInt longest_match(s, cur_match)
*++scan == *++match && *++scan == *++match &&
scan < strend);
Assert(scan <= s->window+(unsigned)(s->window_size-1), "wild scan");
Assert(scan <= s->window + (unsigned)(s->window_size - 1),
"wild scan");
len = MAX_MATCH - (int)(strend - scan);
scan = strend - MAX_MATCH;
@@ -1403,9 +1408,9 @@ local uInt longest_match(s, cur_match)
best_len = len;
if (len >= nice_match) break;
#ifdef UNALIGNED_OK
scan_end = *(ushf*)(scan+best_len-1);
scan_end = *(ushf*)(scan + best_len - 1);
#else
scan_end1 = scan[best_len-1];
scan_end1 = scan[best_len - 1];
scan_end = scan[best_len];
#endif
}
@@ -1415,7 +1420,6 @@ local uInt longest_match(s, cur_match)
if ((uInt)best_len <= s->lookahead) return (uInt)best_len;
return s->lookahead;
}
#endif /* ASMV */
#else /* FASTEST */
@@ -1436,7 +1440,8 @@ local uInt longest_match(s, cur_match)
*/
Assert(s->hash_bits >= 8 && MAX_MATCH == 258, "Code too clever");
Assert((ulg)s->strstart <= s->window_size-MIN_LOOKAHEAD, "need lookahead");
Assert((ulg)s->strstart <= s->window_size - MIN_LOOKAHEAD,
"need lookahead");
Assert(cur_match < s->strstart, "no future");
@@ -1446,7 +1451,7 @@ local uInt longest_match(s, cur_match)
*/
if (match[0] != scan[0] || match[1] != scan[1]) return MIN_MATCH-1;
/* The check at best_len-1 can be removed because it will be made
/* The check at best_len - 1 can be removed because it will be made
* again later. (This heuristic is not always a win.)
* It is not necessary to compare scan[2] and match[2] since they
* are always equal when the other bytes match, given that
@@ -1456,7 +1461,7 @@ local uInt longest_match(s, cur_match)
Assert(*scan == *match, "match[2]?");
/* We check for insufficient lookahead only every 8th comparison;
* the 256th check will be made at strstart+258.
* the 256th check will be made at strstart + 258.
*/
do {
} while (*++scan == *++match && *++scan == *++match &&
@@ -1465,7 +1470,7 @@ local uInt longest_match(s, cur_match)
*++scan == *++match && *++scan == *++match &&
scan < strend);
Assert(scan <= s->window+(unsigned)(s->window_size-1), "wild scan");
Assert(scan <= s->window + (unsigned)(s->window_size - 1), "wild scan");
len = MAX_MATCH - (int)(strend - scan);
@@ -1501,7 +1506,7 @@ local void check_match(s, start, match, length)
z_error("invalid match");
}
if (z_verbose > 1) {
fprintf(stderr,"\\[%d,%d]", start-match, length);
fprintf(stderr,"\\[%d,%d]", start - match, length);
do { putc(s->window[start++], stderr); } while (--length != 0);
}
}
@@ -1547,9 +1552,9 @@ local void fill_window(s)
/* If the window is almost full and there is insufficient lookahead,
* move the upper half to the lower one to make room in the upper half.
*/
if (s->strstart >= wsize+MAX_DIST(s)) {
if (s->strstart >= wsize + MAX_DIST(s)) {
zmemcpy(s->window, s->window+wsize, (unsigned)wsize - more);
zmemcpy(s->window, s->window + wsize, (unsigned)wsize - more);
s->match_start -= wsize;
s->strstart -= wsize; /* we now have strstart >= MAX_DIST */
s->block_start -= (long) wsize;
@@ -1680,7 +1685,7 @@ local void fill_window(s)
*
* deflate_stored() is written to minimize the number of times an input byte is
* copied. It is most efficient with large input and output buffers, which
* maximizes the opportunites to have a single copy from next_in to next_out.
* maximizes the opportunities to have a single copy from next_in to next_out.
*/
local block_state deflate_stored(s, flush)
deflate_state *s;
@@ -1890,7 +1895,7 @@ local block_state deflate_fast(s, flush)
if (s->lookahead == 0) break; /* flush the current block */
}
/* Insert the string window[strstart .. strstart+2] in the
/* Insert the string window[strstart .. strstart + 2] in the
* dictionary, and set hash_head to the head of the hash chain:
*/
hash_head = NIL;
@@ -1938,7 +1943,7 @@ local block_state deflate_fast(s, flush)
s->strstart += s->match_length;
s->match_length = 0;
s->ins_h = s->window[s->strstart];
UPDATE_HASH(s, s->ins_h, s->window[s->strstart+1]);
UPDATE_HASH(s, s->ins_h, s->window[s->strstart + 1]);
#if MIN_MATCH != 3
Call UPDATE_HASH() MIN_MATCH-3 more times
#endif
@@ -1949,7 +1954,7 @@ local block_state deflate_fast(s, flush)
} else {
/* No match, output a literal byte */
Tracevv((stderr,"%c", s->window[s->strstart]));
_tr_tally_lit (s, s->window[s->strstart], bflush);
_tr_tally_lit(s, s->window[s->strstart], bflush);
s->lookahead--;
s->strstart++;
}
@@ -1993,7 +1998,7 @@ local block_state deflate_slow(s, flush)
if (s->lookahead == 0) break; /* flush the current block */
}
/* Insert the string window[strstart .. strstart+2] in the
/* Insert the string window[strstart .. strstart + 2] in the
* dictionary, and set hash_head to the head of the hash chain:
*/
hash_head = NIL;
@@ -2035,17 +2040,17 @@ local block_state deflate_slow(s, flush)
uInt max_insert = s->strstart + s->lookahead - MIN_MATCH;
/* Do not insert strings in hash table beyond this. */
check_match(s, s->strstart-1, s->prev_match, s->prev_length);
check_match(s, s->strstart - 1, s->prev_match, s->prev_length);
_tr_tally_dist(s, s->strstart -1 - s->prev_match,
_tr_tally_dist(s, s->strstart - 1 - s->prev_match,
s->prev_length - MIN_MATCH, bflush);
/* Insert in hash table all strings up to the end of the match.
* strstart-1 and strstart are already inserted. If there is not
* strstart - 1 and strstart are already inserted. If there is not
* enough lookahead, the last two strings are not inserted in
* the hash table.
*/
s->lookahead -= s->prev_length-1;
s->lookahead -= s->prev_length - 1;
s->prev_length -= 2;
do {
if (++s->strstart <= max_insert) {
@@ -2063,8 +2068,8 @@ local block_state deflate_slow(s, flush)
* single literal. If there was a match but the current match
* is longer, truncate the previous match to a single literal.
*/
Tracevv((stderr,"%c", s->window[s->strstart-1]));
_tr_tally_lit(s, s->window[s->strstart-1], bflush);
Tracevv((stderr,"%c", s->window[s->strstart - 1]));
_tr_tally_lit(s, s->window[s->strstart - 1], bflush);
if (bflush) {
FLUSH_BLOCK_ONLY(s, 0);
}
@@ -2082,8 +2087,8 @@ local block_state deflate_slow(s, flush)
}
Assert (flush != Z_NO_FLUSH, "no flush?");
if (s->match_available) {
Tracevv((stderr,"%c", s->window[s->strstart-1]));
_tr_tally_lit(s, s->window[s->strstart-1], bflush);
Tracevv((stderr,"%c", s->window[s->strstart - 1]));
_tr_tally_lit(s, s->window[s->strstart - 1], bflush);
s->match_available = 0;
}
s->insert = s->strstart < MIN_MATCH-1 ? s->strstart : MIN_MATCH-1;
@@ -2140,7 +2145,8 @@ local block_state deflate_rle(s, flush)
if (s->match_length > s->lookahead)
s->match_length = s->lookahead;
}
Assert(scan <= s->window+(uInt)(s->window_size-1), "wild scan");
Assert(scan <= s->window + (uInt)(s->window_size - 1),
"wild scan");
}
/* Emit match if have run of MIN_MATCH or longer, else emit literal */
@@ -2155,7 +2161,7 @@ local block_state deflate_rle(s, flush)
} else {
/* No match, output a literal byte */
Tracevv((stderr,"%c", s->window[s->strstart]));
_tr_tally_lit (s, s->window[s->strstart], bflush);
_tr_tally_lit(s, s->window[s->strstart], bflush);
s->lookahead--;
s->strstart++;
}
@@ -2195,7 +2201,7 @@ local block_state deflate_huff(s, flush)
/* Output a literal byte */
s->match_length = 0;
Tracevv((stderr,"%c", s->window[s->strstart]));
_tr_tally_lit (s, s->window[s->strstart], bflush);
_tr_tally_lit(s, s->window[s->strstart], bflush);
s->lookahead--;
s->strstart++;
if (bflush) FLUSH_BLOCK(s, 0);
+2 -2
View File
@@ -329,8 +329,8 @@ void ZLIB_INTERNAL _tr_stored_block OF((deflate_state *s, charf *buf,
# define _tr_tally_dist(s, distance, length, flush) \
{ uch len = (uch)(length); \
ush dist = (ush)(distance); \
s->sym_buf[s->sym_next++] = dist; \
s->sym_buf[s->sym_next++] = dist >> 8; \
s->sym_buf[s->sym_next++] = (uch)dist; \
s->sym_buf[s->sym_next++] = (uch)(dist >> 8); \
s->sym_buf[s->sym_next++] = len; \
dist--; \
s->dyn_ltree[_length_code[len]+LITERALS+1].Freq++; \
+1 -1
View File
@@ -30,7 +30,7 @@ local gzFile gz_open OF((const void *, int, const char *));
The gz_strwinerror function does not change the current setting of
GetLastError. */
char ZLIB_INTERNAL *gz_strwinerror (error)
char ZLIB_INTERNAL *gz_strwinerror(error)
DWORD error;
{
static char buf[1024];
+3 -5
View File
@@ -157,11 +157,9 @@ local int gz_look(state)
the output buffer is larger than the input buffer, which also assures
space for gzungetc() */
state->x.next = state->out;
if (strm->avail_in) {
memcpy(state->x.next, strm->next_in, strm->avail_in);
state->x.have = strm->avail_in;
strm->avail_in = 0;
}
memcpy(state->x.next, strm->next_in, strm->avail_in);
state->x.have = strm->avail_in;
strm->avail_in = 0;
state->how = COPY;
state->direct = 1;
return 0;
+1 -1
View File
@@ -474,7 +474,7 @@ int ZEXPORTVA gzprintf(gzFile file, const char *format, ...)
#else /* !STDC && !Z_HAVE_STDARG_H */
/* -- see zlib.h -- */
int ZEXPORTVA gzprintf (file, format, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10,
int ZEXPORTVA gzprintf(file, format, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10,
a11, a12, a13, a14, a15, a16, a17, a18, a19, a20)
gzFile file;
const char *format;
+10 -7
View File
@@ -66,6 +66,7 @@ int stream_size;
state->window = window;
state->wnext = 0;
state->whave = 0;
state->sane = 1;
return Z_OK;
}
@@ -605,25 +606,27 @@ void FAR *out_desc;
break;
case DONE:
/* inflate stream terminated properly -- write leftover output */
/* inflate stream terminated properly */
ret = Z_STREAM_END;
if (left < state->wsize) {
if (out(out_desc, state->window, state->wsize - left))
ret = Z_BUF_ERROR;
}
goto inf_leave;
case BAD:
ret = Z_DATA_ERROR;
goto inf_leave;
default: /* can't happen, but makes compilers happy */
default:
/* can't happen, but makes compilers happy */
ret = Z_STREAM_ERROR;
goto inf_leave;
}
/* Return unused input */
/* Write leftover output and return unused input */
inf_leave:
if (left < state->wsize) {
if (out(out_desc, state->window, state->wsize - left) &&
ret == Z_STREAM_END)
ret = Z_BUF_ERROR;
}
strm->next_in = next;
strm->avail_in = have;
return ret;
+5 -2
View File
@@ -168,6 +168,8 @@ int windowBits;
/* extract wrap request from windowBits parameter */
if (windowBits < 0) {
if (windowBits < -15)
return Z_STREAM_ERROR;
wrap = 0;
windowBits = -windowBits;
}
@@ -765,8 +767,9 @@ int flush;
if (copy > have) copy = have;
if (copy) {
if (state->head != Z_NULL &&
state->head->extra != Z_NULL) {
len = state->head->extra_len - state->length;
state->head->extra != Z_NULL &&
(len = state->head->extra_len - state->length) <
state->head->extra_max) {
zmemcpy(state->head->extra + len, next,
len + copy > state->head->extra_max ?
state->head->extra_max - len : copy);
+2 -2
View File
@@ -9,7 +9,7 @@
#define MAXBITS 15
const char inflate_copyright[] =
" inflate 1.2.12 Copyright 1995-2022 Mark Adler ";
" inflate 1.2.13 Copyright 1995-2022 Mark Adler ";
/*
If you use the zlib library in a product, an acknowledgment is welcome
in the documentation of your product. If for some reason you cannot
@@ -62,7 +62,7 @@ unsigned short FAR *work;
35, 43, 51, 59, 67, 83, 99, 115, 131, 163, 195, 227, 258, 0, 0};
static const unsigned short lext[31] = { /* Length codes 257..285 extra */
16, 16, 16, 16, 16, 16, 16, 16, 17, 17, 17, 17, 18, 18, 18, 18,
19, 19, 19, 19, 20, 20, 20, 20, 21, 21, 21, 21, 16, 199, 202};
19, 19, 19, 19, 20, 20, 20, 20, 21, 21, 21, 21, 16, 194, 65};
static const unsigned short dbase[32] = { /* Distance codes 0..29 base */
1, 2, 3, 4, 5, 7, 9, 13, 17, 25, 33, 49, 65, 97, 129, 193,
257, 385, 513, 769, 1025, 1537, 2049, 3073, 4097, 6145,
+1 -1
View File
@@ -38,7 +38,7 @@ typedef struct {
/* Maximum size of the dynamic table. The maximum number of code structures is
1444, which is the sum of 852 for literal/length codes and 592 for distance
codes. These values were found by exhaustive searches using the program
examples/enough.c found in the zlib distribtution. The arguments to that
examples/enough.c found in the zlib distribution. The arguments to that
program are the number of symbols, the initial root table size, and the
maximum bit length of a code. "enough 286 9 15" for literal/length codes
returns returns 852, and "enough 30 6 15" for distance codes returns 592.
+61 -62
View File
@@ -193,7 +193,7 @@ local void send_bits(s, value, length)
s->bits_sent += (ulg)length;
/* If not enough room in bi_buf, use (valid) bits from bi_buf and
* (16 - bi_valid) bits from value, leaving (width - (16-bi_valid))
* (16 - bi_valid) bits from value, leaving (width - (16 - bi_valid))
* unused bits in value.
*/
if (s->bi_valid > (int)Buf_size - length) {
@@ -256,7 +256,7 @@ local void tr_static_init()
length = 0;
for (code = 0; code < LENGTH_CODES-1; code++) {
base_length[code] = length;
for (n = 0; n < (1<<extra_lbits[code]); n++) {
for (n = 0; n < (1 << extra_lbits[code]); n++) {
_length_code[length++] = (uch)code;
}
}
@@ -265,13 +265,13 @@ local void tr_static_init()
* in two different ways: code 284 + 5 bits or code 285, so we
* overwrite length_code[255] to use the best encoding:
*/
_length_code[length-1] = (uch)code;
_length_code[length - 1] = (uch)code;
/* Initialize the mapping dist (0..32K) -> dist code (0..29) */
dist = 0;
for (code = 0 ; code < 16; code++) {
base_dist[code] = dist;
for (n = 0; n < (1<<extra_dbits[code]); n++) {
for (n = 0; n < (1 << extra_dbits[code]); n++) {
_dist_code[dist++] = (uch)code;
}
}
@@ -279,11 +279,11 @@ local void tr_static_init()
dist >>= 7; /* from now on, all distances are divided by 128 */
for ( ; code < D_CODES; code++) {
base_dist[code] = dist << 7;
for (n = 0; n < (1<<(extra_dbits[code]-7)); n++) {
for (n = 0; n < (1 << (extra_dbits[code] - 7)); n++) {
_dist_code[256 + dist++] = (uch)code;
}
}
Assert (dist == 256, "tr_static_init: 256+dist != 512");
Assert (dist == 256, "tr_static_init: 256 + dist != 512");
/* Construct the codes of the static literal tree */
for (bits = 0; bits <= MAX_BITS; bits++) bl_count[bits] = 0;
@@ -312,7 +312,7 @@ local void tr_static_init()
}
/* ===========================================================================
* Genererate the file trees.h describing the static trees.
* Generate the file trees.h describing the static trees.
*/
#ifdef GEN_TREES_H
# ifndef ZLIB_DEBUG
@@ -321,7 +321,7 @@ local void tr_static_init()
# define SEPARATOR(i, last, width) \
((i) == (last)? "\n};\n\n" : \
((i) % (width) == (width)-1 ? ",\n" : ", "))
((i) % (width) == (width) - 1 ? ",\n" : ", "))
void gen_trees_header()
{
@@ -458,7 +458,7 @@ local void pqdownheap(s, tree, k)
while (j <= s->heap_len) {
/* Set j to the smallest of the two sons: */
if (j < s->heap_len &&
smaller(tree, s->heap[j+1], s->heap[j], s->depth)) {
smaller(tree, s->heap[j + 1], s->heap[j], s->depth)) {
j++;
}
/* Exit if v is smaller than both sons */
@@ -507,7 +507,7 @@ local void gen_bitlen(s, desc)
*/
tree[s->heap[s->heap_max]].Len = 0; /* root of the heap */
for (h = s->heap_max+1; h < HEAP_SIZE; h++) {
for (h = s->heap_max + 1; h < HEAP_SIZE; h++) {
n = s->heap[h];
bits = tree[tree[n].Dad].Len + 1;
if (bits > max_length) bits = max_length, overflow++;
@@ -518,7 +518,7 @@ local void gen_bitlen(s, desc)
s->bl_count[bits]++;
xbits = 0;
if (n >= base) xbits = extra[n-base];
if (n >= base) xbits = extra[n - base];
f = tree[n].Freq;
s->opt_len += (ulg)f * (unsigned)(bits + xbits);
if (stree) s->static_len += (ulg)f * (unsigned)(stree[n].Len + xbits);
@@ -530,10 +530,10 @@ local void gen_bitlen(s, desc)
/* Find the first bit length which could increase: */
do {
bits = max_length-1;
bits = max_length - 1;
while (s->bl_count[bits] == 0) bits--;
s->bl_count[bits]--; /* move one leaf down the tree */
s->bl_count[bits+1] += 2; /* move one overflow item as its brother */
s->bl_count[bits]--; /* move one leaf down the tree */
s->bl_count[bits + 1] += 2; /* move one overflow item as its brother */
s->bl_count[max_length]--;
/* The brother of the overflow item also moves one step up,
* but this does not affect bl_count[max_length]
@@ -569,7 +569,7 @@ local void gen_bitlen(s, desc)
* OUT assertion: the field code is set for all tree elements of non
* zero code length.
*/
local void gen_codes (tree, max_code, bl_count)
local void gen_codes(tree, max_code, bl_count)
ct_data *tree; /* the tree to decorate */
int max_code; /* largest code with non zero frequency */
ushf *bl_count; /* number of codes at each bit length */
@@ -583,13 +583,13 @@ local void gen_codes (tree, max_code, bl_count)
* without bit reversal.
*/
for (bits = 1; bits <= MAX_BITS; bits++) {
code = (code + bl_count[bits-1]) << 1;
code = (code + bl_count[bits - 1]) << 1;
next_code[bits] = (ush)code;
}
/* Check that the bit counts in bl_count are consistent. The last code
* must be all ones.
*/
Assert (code + bl_count[MAX_BITS]-1 == (1<<MAX_BITS)-1,
Assert (code + bl_count[MAX_BITS] - 1 == (1 << MAX_BITS) - 1,
"inconsistent bit counts");
Tracev((stderr,"\ngen_codes: max_code %d ", max_code));
@@ -600,7 +600,7 @@ local void gen_codes (tree, max_code, bl_count)
tree[n].Code = (ush)bi_reverse(next_code[len]++, len);
Tracecv(tree != static_ltree, (stderr,"\nn %3d %c l %2d c %4x (%x) ",
n, (isgraph(n) ? n : ' '), len, tree[n].Code, next_code[len]-1));
n, (isgraph(n) ? n : ' '), len, tree[n].Code, next_code[len] - 1));
}
}
@@ -624,7 +624,7 @@ local void build_tree(s, desc)
int node; /* new node being created */
/* Construct the initial heap, with least frequent element in
* heap[SMALLEST]. The sons of heap[n] are heap[2*n] and heap[2*n+1].
* heap[SMALLEST]. The sons of heap[n] are heap[2*n] and heap[2*n + 1].
* heap[0] is not used.
*/
s->heap_len = 0, s->heap_max = HEAP_SIZE;
@@ -652,7 +652,7 @@ local void build_tree(s, desc)
}
desc->max_code = max_code;
/* The elements heap[heap_len/2+1 .. heap_len] are leaves of the tree,
/* The elements heap[heap_len/2 + 1 .. heap_len] are leaves of the tree,
* establish sub-heaps of increasing lengths:
*/
for (n = s->heap_len/2; n >= 1; n--) pqdownheap(s, tree, n);
@@ -700,7 +700,7 @@ local void build_tree(s, desc)
* Scan a literal or distance tree to determine the frequencies of the codes
* in the bit length tree.
*/
local void scan_tree (s, tree, max_code)
local void scan_tree(s, tree, max_code)
deflate_state *s;
ct_data *tree; /* the tree to be scanned */
int max_code; /* and its largest code of non zero frequency */
@@ -714,10 +714,10 @@ local void scan_tree (s, tree, max_code)
int min_count = 4; /* min repeat count */
if (nextlen == 0) max_count = 138, min_count = 3;
tree[max_code+1].Len = (ush)0xffff; /* guard */
tree[max_code + 1].Len = (ush)0xffff; /* guard */
for (n = 0; n <= max_code; n++) {
curlen = nextlen; nextlen = tree[n+1].Len;
curlen = nextlen; nextlen = tree[n + 1].Len;
if (++count < max_count && curlen == nextlen) {
continue;
} else if (count < min_count) {
@@ -745,7 +745,7 @@ local void scan_tree (s, tree, max_code)
* Send a literal or distance tree in compressed form, using the codes in
* bl_tree.
*/
local void send_tree (s, tree, max_code)
local void send_tree(s, tree, max_code)
deflate_state *s;
ct_data *tree; /* the tree to be scanned */
int max_code; /* and its largest code of non zero frequency */
@@ -758,11 +758,11 @@ local void send_tree (s, tree, max_code)
int max_count = 7; /* max repeat count */
int min_count = 4; /* min repeat count */
/* tree[max_code+1].Len = -1; */ /* guard already set */
/* tree[max_code + 1].Len = -1; */ /* guard already set */
if (nextlen == 0) max_count = 138, min_count = 3;
for (n = 0; n <= max_code; n++) {
curlen = nextlen; nextlen = tree[n+1].Len;
curlen = nextlen; nextlen = tree[n + 1].Len;
if (++count < max_count && curlen == nextlen) {
continue;
} else if (count < min_count) {
@@ -773,13 +773,13 @@ local void send_tree (s, tree, max_code)
send_code(s, curlen, s->bl_tree); count--;
}
Assert(count >= 3 && count <= 6, " 3_6?");
send_code(s, REP_3_6, s->bl_tree); send_bits(s, count-3, 2);
send_code(s, REP_3_6, s->bl_tree); send_bits(s, count - 3, 2);
} else if (count <= 10) {
send_code(s, REPZ_3_10, s->bl_tree); send_bits(s, count-3, 3);
send_code(s, REPZ_3_10, s->bl_tree); send_bits(s, count - 3, 3);
} else {
send_code(s, REPZ_11_138, s->bl_tree); send_bits(s, count-11, 7);
send_code(s, REPZ_11_138, s->bl_tree); send_bits(s, count - 11, 7);
}
count = 0; prevlen = curlen;
if (nextlen == 0) {
@@ -807,8 +807,8 @@ local int build_bl_tree(s)
/* Build the bit length tree: */
build_tree(s, (tree_desc *)(&(s->bl_desc)));
/* opt_len now includes the length of the tree representations, except
* the lengths of the bit lengths codes and the 5+5+4 bits for the counts.
/* opt_len now includes the length of the tree representations, except the
* lengths of the bit lengths codes and the 5 + 5 + 4 bits for the counts.
*/
/* Determine the number of bit length codes to send. The pkzip format
@@ -819,7 +819,7 @@ local int build_bl_tree(s)
if (s->bl_tree[bl_order[max_blindex]].Len != 0) break;
}
/* Update opt_len to include the bit length tree and counts */
s->opt_len += 3*((ulg)max_blindex+1) + 5+5+4;
s->opt_len += 3*((ulg)max_blindex + 1) + 5 + 5 + 4;
Tracev((stderr, "\ndyn trees: dyn %ld, stat %ld",
s->opt_len, s->static_len));
@@ -841,19 +841,19 @@ local void send_all_trees(s, lcodes, dcodes, blcodes)
Assert (lcodes <= L_CODES && dcodes <= D_CODES && blcodes <= BL_CODES,
"too many codes");
Tracev((stderr, "\nbl counts: "));
send_bits(s, lcodes-257, 5); /* not +255 as stated in appnote.txt */
send_bits(s, dcodes-1, 5);
send_bits(s, blcodes-4, 4); /* not -3 as stated in appnote.txt */
send_bits(s, lcodes - 257, 5); /* not +255 as stated in appnote.txt */
send_bits(s, dcodes - 1, 5);
send_bits(s, blcodes - 4, 4); /* not -3 as stated in appnote.txt */
for (rank = 0; rank < blcodes; rank++) {
Tracev((stderr, "\nbl code %2d ", bl_order[rank]));
send_bits(s, s->bl_tree[bl_order[rank]].Len, 3);
}
Tracev((stderr, "\nbl tree: sent %ld", s->bits_sent));
send_tree(s, (ct_data *)s->dyn_ltree, lcodes-1); /* literal tree */
send_tree(s, (ct_data *)s->dyn_ltree, lcodes - 1); /* literal tree */
Tracev((stderr, "\nlit tree: sent %ld", s->bits_sent));
send_tree(s, (ct_data *)s->dyn_dtree, dcodes-1); /* distance tree */
send_tree(s, (ct_data *)s->dyn_dtree, dcodes - 1); /* distance tree */
Tracev((stderr, "\ndist tree: sent %ld", s->bits_sent));
}
@@ -866,7 +866,7 @@ void ZLIB_INTERNAL _tr_stored_block(s, buf, stored_len, last)
ulg stored_len; /* length of input block */
int last; /* one if this is the last block for a file */
{
send_bits(s, (STORED_BLOCK<<1)+last, 3); /* send block type */
send_bits(s, (STORED_BLOCK<<1) + last, 3); /* send block type */
bi_windup(s); /* align on byte boundary */
put_short(s, (ush)stored_len);
put_short(s, (ush)~stored_len);
@@ -877,7 +877,7 @@ void ZLIB_INTERNAL _tr_stored_block(s, buf, stored_len, last)
s->compressed_len = (s->compressed_len + 3 + 7) & (ulg)~7L;
s->compressed_len += (stored_len + 4) << 3;
s->bits_sent += 2*16;
s->bits_sent += stored_len<<3;
s->bits_sent += stored_len << 3;
#endif
}
@@ -943,14 +943,17 @@ void ZLIB_INTERNAL _tr_flush_block(s, buf, stored_len, last)
max_blindex = build_bl_tree(s);
/* Determine the best encoding. Compute the block lengths in bytes. */
opt_lenb = (s->opt_len+3+7)>>3;
static_lenb = (s->static_len+3+7)>>3;
opt_lenb = (s->opt_len + 3 + 7) >> 3;
static_lenb = (s->static_len + 3 + 7) >> 3;
Tracev((stderr, "\nopt %lu(%lu) stat %lu(%lu) stored %lu lit %u ",
opt_lenb, s->opt_len, static_lenb, s->static_len, stored_len,
s->sym_next / 3));
if (static_lenb <= opt_lenb) opt_lenb = static_lenb;
#ifndef FORCE_STATIC
if (static_lenb <= opt_lenb || s->strategy == Z_FIXED)
#endif
opt_lenb = static_lenb;
} else {
Assert(buf != (char*)0, "lost buf");
@@ -960,7 +963,7 @@ void ZLIB_INTERNAL _tr_flush_block(s, buf, stored_len, last)
#ifdef FORCE_STORED
if (buf != (char*)0) { /* force stored block */
#else
if (stored_len+4 <= opt_lenb && buf != (char*)0) {
if (stored_len + 4 <= opt_lenb && buf != (char*)0) {
/* 4: two words for the lengths */
#endif
/* The test buf != NULL is only necessary if LIT_BUFSIZE > WSIZE.
@@ -971,21 +974,17 @@ void ZLIB_INTERNAL _tr_flush_block(s, buf, stored_len, last)
*/
_tr_stored_block(s, buf, stored_len, last);
#ifdef FORCE_STATIC
} else if (static_lenb >= 0) { /* force static trees */
#else
} else if (s->strategy == Z_FIXED || static_lenb == opt_lenb) {
#endif
send_bits(s, (STATIC_TREES<<1)+last, 3);
} else if (static_lenb == opt_lenb) {
send_bits(s, (STATIC_TREES<<1) + last, 3);
compress_block(s, (const ct_data *)static_ltree,
(const ct_data *)static_dtree);
#ifdef ZLIB_DEBUG
s->compressed_len += 3 + s->static_len;
#endif
} else {
send_bits(s, (DYN_TREES<<1)+last, 3);
send_all_trees(s, s->l_desc.max_code+1, s->d_desc.max_code+1,
max_blindex+1);
send_bits(s, (DYN_TREES<<1) + last, 3);
send_all_trees(s, s->l_desc.max_code + 1, s->d_desc.max_code + 1,
max_blindex + 1);
compress_block(s, (const ct_data *)s->dyn_ltree,
(const ct_data *)s->dyn_dtree);
#ifdef ZLIB_DEBUG
@@ -1004,22 +1003,22 @@ void ZLIB_INTERNAL _tr_flush_block(s, buf, stored_len, last)
s->compressed_len += 7; /* align on byte boundary */
#endif
}
Tracev((stderr,"\ncomprlen %lu(%lu) ", s->compressed_len>>3,
s->compressed_len-7*last));
Tracev((stderr,"\ncomprlen %lu(%lu) ", s->compressed_len >> 3,
s->compressed_len - 7*last));
}
/* ===========================================================================
* Save the match info and tally the frequency counts. Return true if
* the current block must be flushed.
*/
int ZLIB_INTERNAL _tr_tally (s, dist, lc)
int ZLIB_INTERNAL _tr_tally(s, dist, lc)
deflate_state *s;
unsigned dist; /* distance of matched string */
unsigned lc; /* match length-MIN_MATCH or unmatched char (if dist==0) */
unsigned lc; /* match length - MIN_MATCH or unmatched char (dist==0) */
{
s->sym_buf[s->sym_next++] = dist;
s->sym_buf[s->sym_next++] = dist >> 8;
s->sym_buf[s->sym_next++] = lc;
s->sym_buf[s->sym_next++] = (uch)dist;
s->sym_buf[s->sym_next++] = (uch)(dist >> 8);
s->sym_buf[s->sym_next++] = (uch)lc;
if (dist == 0) {
/* lc is the unmatched char */
s->dyn_ltree[lc].Freq++;
@@ -1031,7 +1030,7 @@ int ZLIB_INTERNAL _tr_tally (s, dist, lc)
(ush)lc <= (ush)(MAX_MATCH-MIN_MATCH) &&
(ush)d_code(dist) < (ush)D_CODES, "_tr_tally: bad match");
s->dyn_ltree[_length_code[lc]+LITERALS+1].Freq++;
s->dyn_ltree[_length_code[lc] + LITERALS + 1].Freq++;
s->dyn_dtree[d_code(dist)].Freq++;
}
return (s->sym_next == s->sym_end);
@@ -1061,7 +1060,7 @@ local void compress_block(s, ltree, dtree)
} else {
/* Here, lc is the match length - MIN_MATCH */
code = _length_code[lc];
send_code(s, code+LITERALS+1, ltree); /* send the length code */
send_code(s, code + LITERALS + 1, ltree); /* send length code */
extra = extra_lbits[code];
if (extra != 0) {
lc -= base_length[code];
@@ -1177,6 +1176,6 @@ local void bi_windup(s)
s->bi_buf = 0;
s->bi_valid = 0;
#ifdef ZLIB_DEBUG
s->bits_sent = (s->bits_sent+7) & ~7;
s->bits_sent = (s->bits_sent + 7) & ~7;
#endif
}
+2 -2
View File
@@ -24,7 +24,7 @@
Z_DATA_ERROR if the input data was corrupted, including if the input data is
an incomplete zlib stream.
*/
int ZEXPORT uncompress2 (dest, destLen, source, sourceLen)
int ZEXPORT uncompress2(dest, destLen, source, sourceLen)
Bytef *dest;
uLongf *destLen;
const Bytef *source;
@@ -83,7 +83,7 @@ int ZEXPORT uncompress2 (dest, destLen, source, sourceLen)
err;
}
int ZEXPORT uncompress (dest, destLen, source, sourceLen)
int ZEXPORT uncompress(dest, destLen, source, sourceLen)
Bytef *dest;
uLongf *destLen;
const Bytef *source;
+16 -3
View File
@@ -38,6 +38,9 @@
# define crc32 z_crc32
# define crc32_combine z_crc32_combine
# define crc32_combine64 z_crc32_combine64
# define crc32_combine_gen z_crc32_combine_gen
# define crc32_combine_gen64 z_crc32_combine_gen64
# define crc32_combine_op z_crc32_combine_op
# define crc32_z z_crc32_z
# define deflate z_deflate
# define deflateBound z_deflateBound
@@ -349,6 +352,9 @@
# ifdef FAR
# undef FAR
# endif
# ifndef WIN32_LEAN_AND_MEAN
# define WIN32_LEAN_AND_MEAN
# endif
# include <windows.h>
/* No need for _export, use ZLIB.DEF instead. */
/* For complete Windows compatibility, use WINAPI, not __stdcall. */
@@ -467,11 +473,18 @@ typedef uLong FAR uLongf;
# undef _LARGEFILE64_SOURCE
#endif
#if defined(__WATCOMC__) && !defined(Z_HAVE_UNISTD_H)
# define Z_HAVE_UNISTD_H
#ifndef Z_HAVE_UNISTD_H
# ifdef __WATCOMC__
# define Z_HAVE_UNISTD_H
# endif
#endif
#ifndef Z_HAVE_UNISTD_H
# if defined(_LARGEFILE64_SOURCE) && !defined(_WIN32)
# define Z_HAVE_UNISTD_H
# endif
#endif
#ifndef Z_SOLO
# if defined(Z_HAVE_UNISTD_H) || defined(_LARGEFILE64_SOURCE)
# if defined(Z_HAVE_UNISTD_H)
# include <unistd.h> /* for SEEK_*, off_t, and _LFS64_LARGEFILE */
# ifdef VMS
# include <unixio.h> /* for off_t */
+10 -10
View File
@@ -1,5 +1,5 @@
/* zlib.h -- interface of the 'zlib' general purpose compression library
version 1.2.12, March 11th, 2022
version 1.2.13, October 13th, 2022
Copyright (C) 1995-2022 Jean-loup Gailly and Mark Adler
@@ -37,11 +37,11 @@
extern "C" {
#endif
#define ZLIB_VERSION "1.2.12"
#define ZLIB_VERNUM 0x12c0
#define ZLIB_VERSION "1.2.13"
#define ZLIB_VERNUM 0x12d0
#define ZLIB_VER_MAJOR 1
#define ZLIB_VER_MINOR 2
#define ZLIB_VER_REVISION 12
#define ZLIB_VER_REVISION 13
#define ZLIB_VER_SUBREVISION 0
/*
@@ -276,7 +276,7 @@ ZEXTERN int ZEXPORT deflate OF((z_streamp strm, int flush));
== 0), or after each call of deflate(). If deflate returns Z_OK and with
zero avail_out, it must be called again after making room in the output
buffer because there might be more output pending. See deflatePending(),
which can be used if desired to determine whether or not there is more ouput
which can be used if desired to determine whether or not there is more output
in that case.
Normally the parameter flush is set to Z_NO_FLUSH, which allows deflate to
@@ -660,7 +660,7 @@ ZEXTERN int ZEXPORT deflateGetDictionary OF((z_streamp strm,
to dictionary. dictionary must have enough space, where 32768 bytes is
always enough. If deflateGetDictionary() is called with dictionary equal to
Z_NULL, then only the dictionary length is returned, and nothing is copied.
Similary, if dictLength is Z_NULL, then it is not set.
Similarly, if dictLength is Z_NULL, then it is not set.
deflateGetDictionary() may return a length less than the window size, even
when more than the window size in input has been provided. It may return up
@@ -915,7 +915,7 @@ ZEXTERN int ZEXPORT inflateGetDictionary OF((z_streamp strm,
to dictionary. dictionary must have enough space, where 32768 bytes is
always enough. If inflateGetDictionary() is called with dictionary equal to
Z_NULL, then only the dictionary length is returned, and nothing is copied.
Similary, if dictLength is Z_NULL, then it is not set.
Similarly, if dictLength is Z_NULL, then it is not set.
inflateGetDictionary returns Z_OK on success, or Z_STREAM_ERROR if the
stream state is inconsistent.
@@ -1437,12 +1437,12 @@ ZEXTERN z_size_t ZEXPORT gzfread OF((voidp buf, z_size_t size, z_size_t nitems,
In the event that the end of file is reached and only a partial item is
available at the end, i.e. the remaining uncompressed data length is not a
multiple of size, then the final partial item is nevetheless read into buf
multiple of size, then the final partial item is nevertheless read into buf
and the end-of-file flag is set. The length of the partial item read is not
provided, but could be inferred from the result of gztell(). This behavior
is the same as the behavior of fread() implementations in common libraries,
but it prevents the direct use of gzfread() to read a concurrently written
file, reseting and retrying on end-of-file, when size is not 1.
file, resetting and retrying on end-of-file, when size is not 1.
*/
ZEXTERN int ZEXPORT gzwrite OF((gzFile file, voidpc buf, unsigned len));
@@ -1913,7 +1913,7 @@ ZEXTERN int ZEXPORT inflateSyncPoint OF((z_streamp));
ZEXTERN const z_crc_t FAR * ZEXPORT get_crc_table OF((void));
ZEXTERN int ZEXPORT inflateUndermine OF((z_streamp, int));
ZEXTERN int ZEXPORT inflateValidate OF((z_streamp, int));
ZEXTERN unsigned long ZEXPORT inflateCodesUsed OF ((z_streamp));
ZEXTERN unsigned long ZEXPORT inflateCodesUsed OF((z_streamp));
ZEXTERN int ZEXPORT inflateResetKeep OF((z_streamp));
ZEXTERN int ZEXPORT deflateResetKeep OF((z_streamp));
#if defined(_WIN32) && !defined(Z_SOLO)
+9 -7
View File
@@ -61,9 +61,11 @@ uLong ZEXPORT zlibCompileFlags()
#ifdef ZLIB_DEBUG
flags += 1 << 8;
#endif
/*
#if defined(ASMV) || defined(ASMINF)
flags += 1 << 9;
#endif
*/
#ifdef ZLIB_WINAPI
flags += 1 << 10;
#endif
@@ -119,7 +121,7 @@ uLong ZEXPORT zlibCompileFlags()
# endif
int ZLIB_INTERNAL z_verbose = verbose;
void ZLIB_INTERNAL z_error (m)
void ZLIB_INTERNAL z_error(m)
char *m;
{
fprintf(stderr, "%s\n", m);
@@ -214,7 +216,7 @@ local ptr_table table[MAX_PTR];
* a protected system like OS/2. Use Microsoft C instead.
*/
voidpf ZLIB_INTERNAL zcalloc (voidpf opaque, unsigned items, unsigned size)
voidpf ZLIB_INTERNAL zcalloc(voidpf opaque, unsigned items, unsigned size)
{
voidpf buf;
ulg bsize = (ulg)items*size;
@@ -240,7 +242,7 @@ voidpf ZLIB_INTERNAL zcalloc (voidpf opaque, unsigned items, unsigned size)
return buf;
}
void ZLIB_INTERNAL zcfree (voidpf opaque, voidpf ptr)
void ZLIB_INTERNAL zcfree(voidpf opaque, voidpf ptr)
{
int n;
@@ -277,13 +279,13 @@ void ZLIB_INTERNAL zcfree (voidpf opaque, voidpf ptr)
# define _hfree hfree
#endif
voidpf ZLIB_INTERNAL zcalloc (voidpf opaque, uInt items, uInt size)
voidpf ZLIB_INTERNAL zcalloc(voidpf opaque, uInt items, uInt size)
{
(void)opaque;
return _halloc((long)items, size);
}
void ZLIB_INTERNAL zcfree (voidpf opaque, voidpf ptr)
void ZLIB_INTERNAL zcfree(voidpf opaque, voidpf ptr)
{
(void)opaque;
_hfree(ptr);
@@ -302,7 +304,7 @@ extern voidp calloc OF((uInt items, uInt size));
extern void free OF((voidpf ptr));
#endif
voidpf ZLIB_INTERNAL zcalloc (opaque, items, size)
voidpf ZLIB_INTERNAL zcalloc(opaque, items, size)
voidpf opaque;
unsigned items;
unsigned size;
@@ -312,7 +314,7 @@ voidpf ZLIB_INTERNAL zcalloc (opaque, items, size)
(voidpf)calloc(items, size);
}
void ZLIB_INTERNAL zcfree (opaque, ptr)
void ZLIB_INTERNAL zcfree(opaque, ptr)
voidpf opaque;
voidpf ptr;
{
+1
View File
@@ -193,6 +193,7 @@ extern z_const char * const z_errmsg[10]; /* indexed by 2-zlib_error */
(!defined(_LARGEFILE64_SOURCE) || _LFS64_LARGEFILE-0 == 0)
ZEXTERN uLong ZEXPORT adler32_combine64 OF((uLong, uLong, z_off_t));
ZEXTERN uLong ZEXPORT crc32_combine64 OF((uLong, uLong, z_off_t));
ZEXTERN uLong ZEXPORT crc32_combine_gen64 OF((z_off_t));
#endif
/* common defaults */
+16 -3
View File
@@ -86,6 +86,9 @@ int main( int argc, const char** argv )
"{ image i | | (required) path to reference image }"
"{ model m | | (required) path to cascade xml file }"
"{ data d | | (optional) path to video output folder }"
"{ ext | avi | (optional) output video file extension e.g. avi (default) or mp4 }"
"{ fourcc | XVID | (optional) output video file's 4-character codec e.g. XVID (default) or H264 }"
"{ fps | 15 | (optional) output video file's frames-per-second rate }"
);
// Read in the input arguments
if (parser.has("help")){
@@ -96,7 +99,9 @@ int main( int argc, const char** argv )
string model(parser.get<string>("model"));
string output_folder(parser.get<string>("data"));
string image_ref = (parser.get<string>("image"));
if (model.empty() || image_ref.empty()){
string fourcc = (parser.get<string>("fourcc"));
int fps = parser.get<int>("fps");
if (model.empty() || image_ref.empty() || fourcc.size()!=4 || fps<1){
parser.printMessage();
printLimits();
return -1;
@@ -166,11 +171,19 @@ int main( int argc, const char** argv )
// each stage, containing all weak classifiers for that stage.
bool draw_planes = false;
stringstream output_video;
output_video << output_folder << "model_visualization.avi";
output_video << output_folder << "model_visualization." << parser.get<string>("ext");
VideoWriter result_video;
if( output_folder.compare("") != 0 ){
draw_planes = true;
result_video.open(output_video.str(), VideoWriter::fourcc('X','V','I','D'), 15, Size(reference_image.cols * resize_factor, reference_image.rows * resize_factor), false);
result_video.open(output_video.str(), VideoWriter::fourcc(fourcc[0],fourcc[1],fourcc[2],fourcc[3]), fps, visualization.size(), false);
if (!result_video.isOpened()){
cerr << "the output video '" << output_video.str() << "' could not be opened."
<< " fourcc=" << fourcc
<< " fps=" << fps
<< " frameSize=" << visualization.size()
<< endl;
return -1;
}
}
if(haar){
+7 -4
View File
@@ -46,7 +46,7 @@
set(CPU_ALL_OPTIMIZATIONS "SSE;SSE2;SSE3;SSSE3;SSE4_1;SSE4_2;POPCNT;AVX;FP16;AVX2;FMA3;AVX_512F")
list(APPEND CPU_ALL_OPTIMIZATIONS "AVX512_COMMON;AVX512_KNL;AVX512_KNM;AVX512_SKX;AVX512_CNL;AVX512_CLX;AVX512_ICL")
list(APPEND CPU_ALL_OPTIMIZATIONS NEON VFPV3 FP16)
list(APPEND CPU_ALL_OPTIMIZATIONS NEON VFPV3 FP16 NEON_DOTPROD)
list(APPEND CPU_ALL_OPTIMIZATIONS MSA)
list(APPEND CPU_ALL_OPTIMIZATIONS VSX VSX3)
list(REMOVE_DUPLICATES CPU_ALL_OPTIMIZATIONS)
@@ -326,6 +326,7 @@ if(X86 OR X86_64)
elseif(ARM OR AARCH64)
ocv_update(CPU_NEON_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_neon.cpp")
ocv_update(CPU_FP16_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_fp16.cpp")
ocv_update(CPU_NEON_DOTPROD_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_dotprod.cpp")
if(NOT AARCH64)
ocv_update(CPU_KNOWN_OPTIMIZATIONS "VFPV3;NEON;FP16")
if(NOT MSVC)
@@ -337,9 +338,11 @@ elseif(ARM OR AARCH64)
endif()
ocv_update(CPU_FP16_IMPLIES "NEON")
else()
ocv_update(CPU_KNOWN_OPTIMIZATIONS "NEON;FP16")
ocv_update(CPU_KNOWN_OPTIMIZATIONS "NEON;FP16;NEON_DOTPROD")
ocv_update(CPU_NEON_FLAGS_ON "")
ocv_update(CPU_FP16_IMPLIES "NEON")
ocv_update(CPU_NEON_DOTPROD_FLAGS_ON "-march=armv8.2-a+dotprod")
ocv_update(CPU_NEON_DOTPROD_IMPLIES "NEON")
set(CPU_BASELINE "NEON;FP16" CACHE STRING "${HELP_CPU_BASELINE}")
endif()
elseif(MIPS)
@@ -677,7 +680,7 @@ macro(ocv_compiler_optimization_process_sources SOURCES_VAR_NAME LIBS_VAR_NAME T
if(fname_LOWER MATCHES "\\.${OPT_LOWER}\\.cpp$")
#message("${fname} BASELINE-${OPT}")
set(__opt_found 1)
list(APPEND __result "${fname}")
list(APPEND __result_${OPT} "${fname}")
break()
endif()
endforeach()
@@ -711,7 +714,7 @@ macro(ocv_compiler_optimization_process_sources SOURCES_VAR_NAME LIBS_VAR_NAME T
endif()
endforeach()
foreach(OPT ${CPU_DISPATCH_FINAL})
foreach(OPT ${CPU_BASELINE_FINAL} ${CPU_DISPATCH_FINAL})
if(__result_${OPT})
#message("${OPT}: ${__result_${OPT}}")
if(CMAKE_GENERATOR MATCHES "^Visual"
+2 -1
View File
@@ -134,7 +134,7 @@ if(CV_GCC OR CV_CLANG)
add_extra_compiler_option(-Wshadow)
add_extra_compiler_option(-Wsign-promo)
add_extra_compiler_option(-Wuninitialized)
if(CV_GCC AND (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 6.0) AND (CMAKE_CXX_COMPILER_VERSION VERSION_LESS 7.0))
if(CV_GCC AND (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 6.0) AND (CMAKE_CXX_COMPILER_VERSION VERSION_LESS 7.0 OR ARM))
add_extra_compiler_option(-Wno-psabi)
endif()
if(HAVE_CXX11)
@@ -426,6 +426,7 @@ if(MSVC)
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4275) # non dll-interface class 'std::exception' used as base for dll-interface class 'cv::Exception'
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4512) # Assignment operator could not be generated
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4589) # Constructor of abstract class 'cv::ORB' ignores initializer for virtual base class 'cv::Algorithm'
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4819) # Symbols like delta or epsilon cannot be represented
endif()
if(CV_ICC AND NOT ENABLE_NOISY_WARNINGS)
+2 -1
View File
@@ -243,12 +243,13 @@ if(CUDA_FOUND)
endif()
if(NOT _nvcc_res EQUAL 0)
message(STATUS "Automatic detection of CUDA generation failed. Going to build for all known architectures.")
# TX1 (5.3) TX2 (6.2) Xavier (7.2) V100 (7.0)
# TX1 (5.3) TX2 (6.2) Xavier (7.2) V100 (7.0) Orin (8.7)
ocv_filter_available_architecture(__cuda_arch_bin
5.3
6.2
7.2
7.0
8.7
)
else()
set(__cuda_arch_bin "${_nvcc_out}")
+1 -1
View File
@@ -1,4 +1,4 @@
cmake_minimum_required(VERSION 3.1)
cmake_minimum_required(VERSION ${MIN_VER_CMAKE})
if(" ${HALIDE_ROOT_DIR}" STREQUAL " ")
unset(HALIDE_ROOT_DIR CACHE)
+4 -1
View File
@@ -866,7 +866,10 @@ macro(ocv_check_modules define)
foreach(flag ${${define}_LDFLAGS})
if(flag MATCHES "^-L(.*)")
list(APPEND _libs_paths ${CMAKE_MATCH_1})
elseif(IS_ABSOLUTE "${flag}")
elseif(IS_ABSOLUTE "${flag}"
OR flag STREQUAL "-lstdc++"
OR flag STREQUAL "-latomic"
)
list(APPEND _libs "${flag}")
elseif(flag MATCHES "^-l(.*)")
set(_lib "${CMAKE_MATCH_1}")
+24
View File
@@ -0,0 +1,24 @@
#include <stdio.h>
#if defined __GNUC__ && (defined __arm__ || defined __aarch64__)
#include "arm_neon.h"
int test()
{
const unsigned int src[] = { 0, 0, 0, 0 };
unsigned int dst[4];
uint32x4_t v_src = *(uint32x4_t*)src;
uint8x16_t v_m0 = *(uint8x16_t*)src;
uint8x16_t v_m1 = *(uint8x16_t*)src;
uint32x4_t v_dst = vdotq_u32(v_src, v_m0, v_m1);
*(uint32x4_t*)dst = v_dst;
return (int)dst[0];
}
#else
#error "DOTPROD is not supported"
#endif
int main()
{
printf("%d\n", test());
return 0;
}
@@ -15,7 +15,7 @@ We will see each one of them.
### 1. Sobel and Scharr Derivatives
Sobel operators is a joint Gausssian smoothing plus differentiation operation, so it is more
Sobel operators is a joint Gaussian smoothing plus differentiation operation, so it is more
resistant to noise. You can specify the direction of derivatives to be taken, vertical or horizontal
(by the arguments, yorder and xorder respectively). You can also specify the size of kernel by the
argument ksize. If ksize = -1, a 3x3 Scharr filter is used which gives better results than 3x3 Sobel
@@ -97,4 +97,4 @@ Try it
<iframe src="../../js_gradients_absSobel.html" width="100%"
onload="this.style.height=this.contentDocument.body.scrollHeight +'px';">
</iframe>
\endhtmlonly
\endhtmlonly
@@ -232,7 +232,7 @@ The following is an adaptation of @ref tutorial_js_face_detection.
@code{.js}
const { Canvas, createCanvas, Image, ImageData, loadImage } = require('canvas');
const { JSDOM } = require('jsdom');
const { writeFileSync, readFileSync } = require('fs');
const { writeFileSync, existsSync, mkdirSync } = require('fs');
(async () => {
await loadOpenCV();
+25 -13
View File
@@ -8,14 +8,18 @@
url = {https://www.doc.ic.ac.uk/~ajd/Publications/alcantarilla_etal_eccv2012.pdf}
}
@article{ANB13,
author = {Alcantarilla, Pablo F and Nuevo, Jes{\'u}s and Bartoli, Adrien},
author = {Pablo Fern{\'{a}}ndez Alcantarilla and Jes{\'{u}}s Nuevo and Adrien Bartoli},
editor = {Tilo Burghardt and Dima Damen and Walterio W. Mayol{-}Cuevas and Majid Mirmehdi},
title = {Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces},
year = {2011},
pages = {1281--1298},
journal = {Trans. Pattern Anal. Machine Intell},
volume = {34},
number = {7},
url = {http://www.bmva.org/bmvc/2013/Papers/paper0013/paper0013.pdf}
booktitle = {British Machine Vision Conference, {BMVC} 2013, Bristol, UK, September 9-13, 2013},
pages = {13.1--13.11},
publisher = {{BMVA} Press},
year = {2013},
url = {https://doi.org/10.5244/C.27.13},
doi = {10.5244/C.27.13},
timestamp = {Sat, 09 Apr 2022 12:44:13 +0200},
biburl = {https://dblp.org/rec/conf/bmvc/AlcantarillaNB13.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{Andreff99,
author = {Andreff, Nicolas and Horaud, Radu and Espiau, Bernard},
@@ -543,7 +547,7 @@
title = {Multiple view geometry in computer vision},
year = {2003},
publisher = {Cambridge university press},
url = {http://cds.cern.ch/record/1598612/files/0521540518_TOC.pdf}
url = {https://www.robots.ox.ac.uk/~vgg/hzbook/}
}
@article{Horaud95,
author = {Horaud, Radu and Dornaika, Fadi},
@@ -745,10 +749,17 @@
isbn = {0387008934},
publisher = {Springer}
}
@article{Malis,
author = {Malis, Ezio and Vargas, Manuel and others},
title = {Deeper understanding of the homography decomposition for vision-based control},
year = {2007}
@article{Malis2007,
author = {Malis, Ezio and Vargas, Manuel},
title = {{Deeper understanding of the homography decomposition for vision-based control}},
year = {2007},
url = {https://hal.inria.fr/inria-00174036},
type = {Research Report},
number = {RR-6303},
pages = {90},
institution = {{INRIA}},
keywords = {Visual servoing ; planar objects ; homography ; decomposition ; camera calibration errors ; structure from motion ; Euclidean},
pdf = {https://hal.inria.fr/inria-00174036v3/file/RR-6303.pdf},
}
@article{Marchand16,
author = {Marchand, Eric and Uchiyama, Hideaki and Spindler, Fabien},
@@ -905,7 +916,8 @@
author = {Szeliski, Richard},
title = {Computer vision: algorithms and applications},
year = {2010},
publisher = {Springer}
publisher = {Springer},
url = {https://szeliski.org/Book/}
}
@article{Rafael12,
author = {von Gioi, Rafael Grompone and Jakubowicz, J{\'e}r{\'e}mie and Morel, Jean-Michel and Randall, Gregory},
@@ -127,7 +127,7 @@ for fname in images:
objpoints.append(objp)
corners2 = cv.cornerSubPix(gray,corners, (11,11), (-1,-1), criteria)
imgpoints.append(corners)
imgpoints.append(corners2)
# Draw and display the corners
cv.drawChessboardCorners(img, (7,6), corners2, ret)
@@ -14,7 +14,7 @@ So in this chapter, you will learn:
Apart from OpenCV, Python also provides a module **time** which is helpful in measuring the time of
execution. Another module **profile** helps to get a detailed report on the code, like how much time
each function in the code took, how many times the function was called, etc. But, if you are using
IPython, all these features are integrated in an user-friendly manner. We will see some important
IPython, all these features are integrated in a user-friendly manner. We will see some important
ones, and for more details, check links in the **Additional Resources** section.
Measuring Performance with OpenCV
@@ -17,7 +17,7 @@ We will see each one of them.
### 1. Sobel and Scharr Derivatives
Sobel operators is a joint Gausssian smoothing plus differentiation operation, so it is more
Sobel operators is a joint Gaussian smoothing plus differentiation operation, so it is more
resistant to noise. You can specify the direction of derivatives to be taken, vertical or horizontal
(by the arguments, yorder and xorder respectively). You can also specify the size of kernel by the
argument ksize. If ksize = -1, a 3x3 Scharr filter is used which gives better results than 3x3 Sobel
@@ -10,9 +10,11 @@ Introduction {#tutorial_homography_Introduction}
This tutorial will demonstrate the basic concepts of the homography with some codes.
For detailed explanations about the theory, please refer to a computer vision course or a computer vision book, e.g.:
* Multiple View Geometry in Computer Vision, @cite HartleyZ00.
* An Invitation to 3-D Vision: From Images to Geometric Models, @cite Ma:2003:IVI
* Computer Vision: Algorithms and Applications, @cite RS10
* Multiple View Geometry in Computer Vision, Richard Hartley and Andrew Zisserman, @cite HartleyZ00 (some sample chapters are available [here](https://www.robots.ox.ac.uk/~vgg/hzbook/), CVPR Tutorials are available [here](https://www.robots.ox.ac.uk/~az/tutorials/))
* An Invitation to 3-D Vision: From Images to Geometric Models, Yi Ma, Stefano Soatto, Jana Kosecka, and S. Shankar Sastry, @cite Ma:2003:IVI (a computer vision book handout is available [here](https://cs.gmu.edu/%7Ekosecka/cs685/VisionBookHandout.pdf))
* Computer Vision: Algorithms and Applications, Richard Szeliski, @cite RS10 (an electronic version is available [here](https://szeliski.org/Book/))
* Deeper understanding of the homography decomposition for vision-based control, Ezio Malis, Manuel Vargas, @cite Malis2007 (open access [here](https://hal.inria.fr/inria-00174036))
* Pose Estimation for Augmented Reality: A Hands-On Survey, Eric Marchand, Hideaki Uchiyama, Fabien Spindler, @cite Marchand16 (open access [here](https://hal.inria.fr/hal-01246370))
The tutorial code can be found here [C++](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/features2D/Homography),
[Python](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/features2D/Homography),
@@ -32,7 +34,7 @@ Briefly, the planar homography relates the transformation between two planes (up
x^{'} \\
y^{'} \\
1
\end{bmatrix} = H
\end{bmatrix} = \mathbf{H}
\begin{bmatrix}
x \\
y \\
@@ -123,22 +125,22 @@ A quick solution to retrieve the pose from the homography matrix is (see \ref po
\f[
\begin{align*}
\boldsymbol{X} &= \left( X, Y, 0, 1 \right ) \\
\boldsymbol{x} &= \boldsymbol{P}\boldsymbol{X} \\
&= \boldsymbol{K} \left[ \boldsymbol{r_1} \hspace{0.5em} \boldsymbol{r_2} \hspace{0.5em} \boldsymbol{r_3} \hspace{0.5em} \boldsymbol{t} \right ]
\mathbf{X} &= \left( X, Y, 0, 1 \right ) \\
\mathbf{x} &= \mathbf{P}\mathbf{X} \\
&= \mathbf{K} \left[ \mathbf{r_1} \hspace{0.5em} \mathbf{r_2} \hspace{0.5em} \mathbf{r_3} \hspace{0.5em} \mathbf{t} \right ]
\begin{pmatrix}
X \\
Y \\
0 \\
1
\end{pmatrix} \\
&= \boldsymbol{K} \left[ \boldsymbol{r_1} \hspace{0.5em} \boldsymbol{r_2} \hspace{0.5em} \boldsymbol{t} \right ]
&= \mathbf{K} \left[ \mathbf{r_1} \hspace{0.5em} \mathbf{r_2} \hspace{0.5em} \mathbf{t} \right ]
\begin{pmatrix}
X \\
Y \\
1
\end{pmatrix} \\
&= \boldsymbol{H}
&= \mathbf{H}
\begin{pmatrix}
X \\
Y \\
@@ -149,16 +151,16 @@ A quick solution to retrieve the pose from the homography matrix is (see \ref po
\f[
\begin{align*}
\boldsymbol{H} &= \lambda \boldsymbol{K} \left[ \boldsymbol{r_1} \hspace{0.5em} \boldsymbol{r_2} \hspace{0.5em} \boldsymbol{t} \right ] \\
\boldsymbol{K}^{-1} \boldsymbol{H} &= \lambda \left[ \boldsymbol{r_1} \hspace{0.5em} \boldsymbol{r_2} \hspace{0.5em} \boldsymbol{t} \right ] \\
\boldsymbol{P} &= \boldsymbol{K} \left[ \boldsymbol{r_1} \hspace{0.5em} \boldsymbol{r_2} \hspace{0.5em} \left( \boldsymbol{r_1} \times \boldsymbol{r_2} \right ) \hspace{0.5em} \boldsymbol{t} \right ]
\mathbf{H} &= \lambda \mathbf{K} \left[ \mathbf{r_1} \hspace{0.5em} \mathbf{r_2} \hspace{0.5em} \mathbf{t} \right ] \\
\mathbf{K}^{-1} \mathbf{H} &= \lambda \left[ \mathbf{r_1} \hspace{0.5em} \mathbf{r_2} \hspace{0.5em} \mathbf{t} \right ] \\
\mathbf{P} &= \mathbf{K} \left[ \mathbf{r_1} \hspace{0.5em} \mathbf{r_2} \hspace{0.5em} \left( \mathbf{r_1} \times \mathbf{r_2} \right ) \hspace{0.5em} \mathbf{t} \right ]
\end{align*}
\f]
This is a quick solution (see also \ref projective_transformations "2") as this does not ensure that the resulting rotation matrix will be orthogonal and the scale is estimated roughly by normalize the first column to 1.
A solution to have a proper rotation matrix (with the properties of a rotation matrix) consists to apply a polar decomposition
(see \ref polar_decomposition "6" or \ref polar_decomposition_svd "7" for some information):
A solution to have a proper rotation matrix (with the properties of a rotation matrix) consists to apply a polar decomposition, or orthogonalization of the rotation matrix
(see \ref polar_decomposition "6" or \ref polar_decomposition_svd "7" or \ref polar_decomposition_svd_2 "8" or \ref Kabsch_algorithm "9" for some information):
@snippet pose_from_homography.cpp polar-decomposition-of-the-rotation-matrix
@@ -239,7 +241,7 @@ To check the correctness of the calculation, the matching lines are displayed:
### Demo 3: Homography from the camera displacement {#tutorial_homography_Demo3}
The homography relates the transformation between two planes and it is possible to retrieve the corresponding camera displacement that allows to go from the first to the second plane view (see @cite Malis for more information).
The homography relates the transformation between two planes and it is possible to retrieve the corresponding camera displacement that allows to go from the first to the second plane view (see @cite Malis2007 for more information).
Before going into the details that allow to compute the homography from the camera displacement, some recalls about camera pose and homogeneous transformation.
The function @ref cv::solvePnP allows to compute the camera pose from the correspondences 3D object points (points expressed in the object frame) and the projected 2D image points (object points viewed in the image).
@@ -269,7 +271,7 @@ The intrinsic parameters and the distortion coefficients are required (see the c
Z_o \\
1
\end{bmatrix} \\
&= \boldsymbol{K} \hspace{0.2em} ^{c}\textrm{M}_o
&= \mathbf{K} \hspace{0.2em} ^{c}\mathbf{M}_o
\begin{bmatrix}
X_o \\
Y_o \\
@@ -279,9 +281,9 @@ The intrinsic parameters and the distortion coefficients are required (see the c
\end{align*}
\f]
\f$ \boldsymbol{K} \f$ is the intrinsic matrix and \f$ ^{c}\textrm{M}_o \f$ is the camera pose. The output of @ref cv::solvePnP is exactly this: `rvec` is the Rodrigues rotation vector and `tvec` the translation vector.
\f$ \mathbf{K} \f$ is the intrinsic matrix and \f$ ^{c}\mathbf{M}_o \f$ is the camera pose. The output of @ref cv::solvePnP is exactly this: `rvec` is the Rodrigues rotation vector and `tvec` the translation vector.
\f$ ^{c}\textrm{M}_o \f$ can be represented in a homogeneous form and allows to transform a point expressed in the object frame into the camera frame:
\f$ ^{c}\mathbf{M}_o \f$ can be represented in a homogeneous form and allows to transform a point expressed in the object frame into the camera frame:
\f[
\begin{align*}
@@ -291,7 +293,7 @@ The intrinsic parameters and the distortion coefficients are required (see the c
Z_c \\
1
\end{bmatrix} &=
\hspace{0.2em} ^{c}\textrm{M}_o
\hspace{0.2em} ^{c}\mathbf{M}_o
\begin{bmatrix}
X_o \\
Y_o \\
@@ -300,7 +302,7 @@ The intrinsic parameters and the distortion coefficients are required (see the c
\end{bmatrix} \\
&=
\begin{bmatrix}
^{c}\textrm{R}_o & ^{c}\textrm{t}_o \\
^{c}\mathbf{R}_o & ^{c}\mathbf{t}_o \\
0_{1\times3} & 1
\end{bmatrix}
\begin{bmatrix}
@@ -327,19 +329,19 @@ The intrinsic parameters and the distortion coefficients are required (see the c
Transform a point expressed in one frame to another frame can be easily done with matrix multiplication:
* \f$ ^{c_1}\textrm{M}_o \f$ is the camera pose for the camera 1
* \f$ ^{c_2}\textrm{M}_o \f$ is the camera pose for the camera 2
* \f$ ^{c_1}\mathbf{M}_o \f$ is the camera pose for the camera 1
* \f$ ^{c_2}\mathbf{M}_o \f$ is the camera pose for the camera 2
To transform a 3D point expressed in the camera 1 frame to the camera 2 frame:
\f[
^{c_2}\textrm{M}_{c_1} = \hspace{0.2em} ^{c_2}\textrm{M}_{o} \cdot \hspace{0.1em} ^{o}\textrm{M}_{c_1} = \hspace{0.2em} ^{c_2}\textrm{M}_{o} \cdot \hspace{0.1em} \left( ^{c_1}\textrm{M}_{o} \right )^{-1} =
^{c_2}\mathbf{M}_{c_1} = \hspace{0.2em} ^{c_2}\mathbf{M}_{o} \cdot \hspace{0.1em} ^{o}\mathbf{M}_{c_1} = \hspace{0.2em} ^{c_2}\mathbf{M}_{o} \cdot \hspace{0.1em} \left( ^{c_1}\mathbf{M}_{o} \right )^{-1} =
\begin{bmatrix}
^{c_2}\textrm{R}_{o} & ^{c_2}\textrm{t}_{o} \\
^{c_2}\mathbf{R}_{o} & ^{c_2}\mathbf{t}_{o} \\
0_{3 \times 1} & 1
\end{bmatrix} \cdot
\begin{bmatrix}
^{c_1}\textrm{R}_{o}^T & - \hspace{0.2em} ^{c_1}\textrm{R}_{o}^T \cdot \hspace{0.2em} ^{c_1}\textrm{t}_{o} \\
^{c_1}\mathbf{R}_{o}^T & - \hspace{0.2em} ^{c_1}\mathbf{R}_{o}^T \cdot \hspace{0.2em} ^{c_1}\mathbf{t}_{o} \\
0_{1 \times 3} & 1
\end{bmatrix}
\f]
@@ -362,11 +364,11 @@ On this figure, `n` is the normal vector of the plane and `d` the distance betwe
The [equation](https://en.wikipedia.org/wiki/Homography_(computer_vision)#3D_plane_to_plane_equation) to compute the homography from the camera displacement is:
\f[
^{2}\textrm{H}_{1} = \hspace{0.2em} ^{2}\textrm{R}_{1} - \hspace{0.1em} \frac{^{2}\textrm{t}_{1} \cdot n^T}{d}
^{2}\mathbf{H}_{1} = \hspace{0.2em} ^{2}\mathbf{R}_{1} - \hspace{0.1em} \frac{^{2}\mathbf{t}_{1} \cdot \hspace{0.1em} ^{1}\mathbf{n}^\top}{^1d}
\f]
Where \f$ ^{2}\textrm{H}_{1} \f$ is the homography matrix that maps the points in the first camera frame to the corresponding points in the second camera frame, \f$ ^{2}\textrm{R}_{1} = \hspace{0.2em} ^{c_2}\textrm{R}_{o} \cdot \hspace{0.1em} ^{c_1}\textrm{R}_{o}^{T} \f$
is the rotation matrix that represents the rotation between the two camera frames and \f$ ^{2}\textrm{t}_{1} = \hspace{0.2em} ^{c_2}\textrm{R}_{o} \cdot \left( - \hspace{0.1em} ^{c_1}\textrm{R}_{o}^{T} \cdot \hspace{0.1em} ^{c_1}\textrm{t}_{o} \right ) + \hspace{0.1em} ^{c_2}\textrm{t}_{o} \f$
Where \f$ ^{2}\mathbf{H}_{1} \f$ is the homography matrix that maps the points in the first camera frame to the corresponding points in the second camera frame, \f$ ^{2}\mathbf{R}_{1} = \hspace{0.2em} ^{c_2}\mathbf{R}_{o} \cdot \hspace{0.1em} ^{c_1}\mathbf{R}_{o}^{\top} \f$
is the rotation matrix that represents the rotation between the two camera frames and \f$ ^{2}\mathbf{t}_{1} = \hspace{0.2em} ^{c_2}\mathbf{R}_{o} \cdot \left( - \hspace{0.1em} ^{c_1}\mathbf{R}_{o}^{\top} \cdot \hspace{0.1em} ^{c_1}\mathbf{t}_{o} \right ) + \hspace{0.1em} ^{c_2}\mathbf{t}_{o} \f$
the translation vector between the two camera frames.
Here the normal vector `n` is the plane normal expressed in the camera frame 1 and can be computed as the cross product of 2 vectors (using 3 non collinear points that lie on the plane) or in our case directly with:
@@ -377,7 +379,7 @@ The distance `d` can be computed as the dot product between the plane normal and
@snippet homography_from_camera_displacement.cpp compute-plane-distance-to-the-camera-frame-1
The projective homography matrix \f$ \textbf{G} \f$ can be computed from the Euclidean homography \f$ \textbf{H} \f$ using the intrinsic matrix \f$ \textbf{K} \f$ (see @cite Malis), here assuming the same camera between the two plane views:
The projective homography matrix \f$ \textbf{G} \f$ can be computed from the Euclidean homography \f$ \textbf{H} \f$ using the intrinsic matrix \f$ \textbf{K} \f$ (see @cite Malis2007), here assuming the same camera between the two plane views:
\f[
\textbf{G} = \gamma \textbf{K} \textbf{H} \textbf{K}^{-1}
@@ -388,7 +390,7 @@ The projective homography matrix \f$ \textbf{G} \f$ can be computed from the Euc
In our case, the Z-axis of the chessboard goes inside the object whereas in the homography figure it goes outside. This is just a matter of sign:
\f[
^{2}\textrm{H}_{1} = \hspace{0.2em} ^{2}\textrm{R}_{1} + \hspace{0.1em} \frac{^{2}\textrm{t}_{1} \cdot n^T}{d}
^{2}\mathbf{H}_{1} = \hspace{0.2em} ^{2}\mathbf{R}_{1} + \hspace{0.1em} \frac{^{2}\mathbf{t}_{1} \cdot \hspace{0.1em} ^{1}\mathbf{n}^\top}{^1d}
\f]
@snippet homography_from_camera_displacement.cpp compute-homography-from-camera-displacement
@@ -410,10 +412,18 @@ homography from camera displacement:
The homography matrices are similar. If we compare the image 1 warped using both homography matrices:
![Left: image warped using the homography estimated. Right: using the homography computed from the camera displacement](images/homography_camera_displacement_compare.jpg)
![Left: image warped using the estimated homography. Right: using the homography computed from the camera displacement.](images/homography_camera_displacement_compare.jpg)
Visually, it is hard to distinguish a difference between the result image from the homography computed from the camera displacement and the one estimated with @ref cv::findHomography function.
#### Exercise
This demo shows you how to compute the homography transformation from two camera poses. Try to perform the same operations, but by computing N inter homography this time. Instead of computing one homography to directly warp the source image to the desired camera viewpoint, perform N warping operations to see the different transformations operating.
You should get something similar to the following:
![The first three images show the source image warped at three different interpolated camera viewpoints. The 4th image shows the "error image" between the warped source image at the final camera viewpoint and the desired image.](images/homography_camera_poses_interpolation.jpg)
### Demo 4: Decompose the homography matrix {#tutorial_homography_Demo4}
OpenCV 3 contains the function @ref cv::decomposeHomographyMat which allows to decompose the homography matrix to a set of rotations, translations and plane normals.
@@ -466,8 +476,8 @@ As you can see, there is one solution that matches almost perfectly with the com
At least two of the solutions may further be invalidated if point correspondences are available by applying positive depth constraint (all points must be in front of the camera).
```
As the result of the decomposition is a camera displacement, if we have the initial camera pose \f$ ^{c_1}\textrm{M}_{o} \f$, we can compute the current camera pose
\f$ ^{c_2}\textrm{M}_{o} = \hspace{0.2em} ^{c_2}\textrm{M}_{c_1} \cdot \hspace{0.1em} ^{c_1}\textrm{M}_{o} \f$ and test if the 3D object points that belong to the plane are projected in front of the camera or not.
As the result of the decomposition is a camera displacement, if we have the initial camera pose \f$ ^{c_1}\mathbf{M}_{o} \f$, we can compute the current camera pose
\f$ ^{c_2}\mathbf{M}_{o} = \hspace{0.2em} ^{c_2}\mathbf{M}_{c_1} \cdot \hspace{0.1em} ^{c_1}\mathbf{M}_{o} \f$ and test if the 3D object points that belong to the plane are projected in front of the camera or not.
Another solution could be to retain the solution with the closest normal if we know the plane normal expressed at the camera 1 pose.
The same thing but with the homography matrix estimated with @ref cv::findHomography
@@ -516,7 +526,7 @@ The [stitching module](@ref stitching) provides a complete pipeline to stitch im
The homography transformation applies only for planar structure. But in the case of a rotating camera (pure rotation around the camera axis of projection, no translation), an arbitrary world can be considered
([see previously](@ref tutorial_homography_What_is_the_homography_matrix)).
The homography can then be computed using the rotation transformation and the camera intrinsic parameters as (see for instance \ref homography_course "8"):
The homography can then be computed using the rotation transformation and the camera intrinsic parameters as (see for instance \ref homography_course "10"):
\f[
s
@@ -534,7 +544,7 @@ The homography can then be computed using the rotation transformation and the ca
\f]
To illustrate, we used Blender, a free and open-source 3D computer graphics software, to generate two camera views with only a rotation transformation between each other.
More information about how to retrieve the camera intrinsic parameters and the `3x4` extrinsic matrix with respect to the world can be found in \ref answer_blender "9" (an additional transformation
More information about how to retrieve the camera intrinsic parameters and the `3x4` extrinsic matrix with respect to the world can be found in \ref answer_blender "11" (an additional transformation
is needed to get the transformation between the camera and the object frames) with Blender.
The figure below shows the two generated views of the Suzanne model, with only a rotation transformation:
@@ -603,11 +613,13 @@ Additional references {#tutorial_homography_Additional_references}
---------------------
* \anchor lecture_16 1. [Lecture 16: Planar Homographies](http://www.cse.psu.edu/~rtc12/CSE486/lecture16.pdf), Robert Collins
* \anchor projective_transformations 2. [2D projective transformations (homographies)](https://ags.cs.uni-kl.de/fileadmin/inf_ags/3dcv-ws11-12/3DCV_WS11-12_lec04.pdf), Christiano Gava, Gabriele Bleser
* \anchor szeliski 3. [Computer Vision: Algorithms and Applications](http://szeliski.org/Book/drafts/SzeliskiBook_20100903_draft.pdf), Richard Szeliski
* \anchor projective_transformations 2. [2D projective transformations (homographies)](https://web.archive.org/web/20171226115739/https://ags.cs.uni-kl.de/fileadmin/inf_ags/3dcv-ws11-12/3DCV_WS11-12_lec04.pdf), Christiano Gava, Gabriele Bleser
* \anchor szeliski 3. [Computer Vision: Algorithms and Applications](https://szeliski.org/Book/), Richard Szeliski
* \anchor answer_dsp 4. [Step by Step Camera Pose Estimation for Visual Tracking and Planar Markers](https://dsp.stackexchange.com/a/2737)
* \anchor pose_ar 5. [Pose from homography estimation](https://team.inria.fr/lagadic/camera_localization/tutorial-pose-dlt-planar-opencv.html)
* \anchor pose_ar 5. [Pose from homography estimation](https://visp-doc.inria.fr/doxygen/camera_localization/tutorial-pose-dlt-planar-opencv.html)
* \anchor polar_decomposition 6. [Polar Decomposition (in Continuum Mechanics)](http://www.continuummechanics.org/polardecomposition.html)
* \anchor polar_decomposition_svd 7. [A Personal Interview with the Singular Value Decomposition](https://web.stanford.edu/~gavish/documents/SVD_ans_you.pdf), Matan Gavish
* \anchor homography_course 8. [Homography](http://people.scs.carleton.ca/~c_shu/Courses/comp4900d/notes/homography.pdf), Dr. Gerhard Roth
* \anchor answer_blender 9. [3x4 camera matrix from blender camera](https://blender.stackexchange.com/a/38210)
* \anchor polar_decomposition_svd 7. [Chapter 3 - 3.1.2 From matrices to rotations - Theorem 3.1 (Least-squares estimation of a rotation from a matrix K)](https://www-sop.inria.fr/asclepios/cours/MVA/Rotations.pdf)
* \anchor polar_decomposition_svd_2 8. [A Personal Interview with the Singular Value Decomposition](https://web.stanford.edu/~gavish/documents/SVD_ans_you.pdf), Matan Gavish
* \anchor Kabsch_algorithm 9. [Kabsch algorithm, Computation of the optimal rotation matrix](https://en.wikipedia.org/wiki/Kabsch_algorithm#Computation_of_the_optimal_rotation_matrix)
* \anchor homography_course 10. [Homography](http://people.scs.carleton.ca/~c_shu/Courses/comp4900d/notes/homography.pdf), Dr. Gerhard Roth
* \anchor answer_blender 11. [3x4 camera matrix from blender camera](https://blender.stackexchange.com/a/38210)
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@@ -0,0 +1,92 @@
Object detection with Generalized Ballard and Guil Hough Transform {#tutorial_generalized_hough_ballard_guil}
==================================================================
@tableofcontents
@prev_tutorial{tutorial_hough_circle}
@next_tutorial{tutorial_remap}
Goal
----
In this tutorial you will learn how to:
- Use @ref cv::GeneralizedHoughBallard and @ref cv::GeneralizedHoughGuil to detect an object
Example
-------
### What does this program do?
1. Load the image and template
![image](images/generalized_hough_mini_image.jpg)
![template](images/generalized_hough_mini_template.jpg)
2. Instantiate @ref cv::GeneralizedHoughBallard with the help of `createGeneralizedHoughBallard()`
3. Instantiate @ref cv::GeneralizedHoughGuil with the help of `createGeneralizedHoughGuil()`
4. Set the required parameters for both GeneralizedHough variants
5. Detect and show found results
@note
- Both variants can't be instantiated directly. Using the create methods is required.
- Guil Hough is very slow. Calculating the results for the "mini" files used in this tutorial
takes only a few seconds. With image and template in a higher resolution, as shown below,
my notebook requires about 5 minutes to calculate a result.
![image](images/generalized_hough_image.jpg)
![template](images/generalized_hough_template.jpg)
### Code
The complete code for this tutorial is shown below.
@include samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp
Explanation
-----------
### Load image, template and setup variables
@snippet samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp generalized-hough-transform-load-and-setup
The position vectors will contain the matches the detectors will find.
Every entry contains four floating point values:
position vector
- *[0]*: x coordinate of center point
- *[1]*: y coordinate of center point
- *[2]*: scale of detected object compared to template
- *[3]*: rotation of detected object in degree in relation to template
An example could look as follows: `[200, 100, 0.9, 120]`
### Setup parameters
@snippet samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp generalized-hough-transform-setup-parameters
Finding the optimal values can end up in trial and error and depends on many factors, such as the image resolution.
### Run detection
@snippet samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp generalized-hough-transform-run
As mentioned above, this step will take some time, especially with larger images and when using Guil.
### Draw results and show image
@snippet samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp generalized-hough-transform-draw-results
Result
------
![result image](images/generalized_hough_result_img.jpg)
The blue rectangle shows the result of @ref cv::GeneralizedHoughBallard and the green rectangles the results of @ref
cv::GeneralizedHoughGuil.
Getting perfect results like in this example is unlikely if the parameters are not perfectly adapted to the sample.
An example with less perfect parameters is shown below.
For the Ballard variant, only the center of the result is marked as a black dot on this image. The rectangle would be
the same as on the previous image.
![less perfect result](images/generalized_hough_less_perfect_result_img.jpg)
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@@ -2,7 +2,7 @@ Hough Circle Transform {#tutorial_hough_circle}
======================
@prev_tutorial{tutorial_hough_lines}
@next_tutorial{tutorial_remap}
@next_tutorial{tutorial_generalized_hough_ballard_guil}
Goal
----
@@ -1,7 +1,7 @@
Remapping {#tutorial_remap}
=========
@prev_tutorial{tutorial_hough_circle}
@prev_tutorial{tutorial_generalized_hough_ballard_guil}
@next_tutorial{tutorial_warp_affine}
Goal
@@ -173,6 +173,16 @@ In this section you will learn about the image processing (manipulation) functio
Where we learn how to detect circles
- @subpage tutorial_generalized_hough_ballard_guil
*Languages:* C++
*Compatibility:* \>= OpenCV 3.4
*Author:* Markus Heck
Detect an object in a picture with the help of GeneralizedHoughBallard and GeneralizedHoughGuil.
- @subpage tutorial_remap
*Languages:* C++, Java, Python
@@ -39,14 +39,14 @@ Open your Doxyfile using your favorite text editor and search for the key
`TAGFILES`. Change it as follows:
@code
TAGFILES = ./docs/doxygen-tags/opencv.tag=http://docs.opencv.org/3.4.18
TAGFILES = ./docs/doxygen-tags/opencv.tag=http://docs.opencv.org/3.4.19
@endcode
If you had other definitions already, you can append the line using a `\`:
@code
TAGFILES = ./docs/doxygen-tags/libstdc++.tag=https://gcc.gnu.org/onlinedocs/libstdc++/latest-doxygen \
./docs/doxygen-tags/opencv.tag=http://docs.opencv.org/3.4.18
./docs/doxygen-tags/opencv.tag=http://docs.opencv.org/3.4.19
@endcode
Doxygen can now use the information from the tag file to link to the OpenCV
@@ -3,6 +3,7 @@ Cascade Classifier Training {#tutorial_traincascade}
@prev_tutorial{tutorial_cascade_classifier}
Introduction
------------
+65 -51
View File
@@ -577,7 +577,7 @@ a vector\<Point2f\> .
- @ref RHO - PROSAC-based robust method
@param ransacReprojThreshold Maximum allowed reprojection error to treat a point pair as an inlier
(used in the RANSAC and RHO methods only). That is, if
\f[\| \texttt{dstPoints} _i - \texttt{convertPointsHomogeneous} ( \texttt{H} * \texttt{srcPoints} _i) \|_2 > \texttt{ransacReprojThreshold}\f]
\f[\| \texttt{dstPoints} _i - \texttt{convertPointsHomogeneous} ( \texttt{H} \cdot \texttt{srcPoints} _i) \|_2 > \texttt{ransacReprojThreshold}\f]
then the point \f$i\f$ is considered as an outlier. If srcPoints and dstPoints are measured in pixels,
it usually makes sense to set this parameter somewhere in the range of 1 to 10.
@param mask Optional output mask set by a robust method ( RANSAC or LMeDS ). Note that the input
@@ -642,7 +642,7 @@ CV_EXPORTS Mat findHomography( InputArray srcPoints, InputArray dstPoints,
@param Qz Optional output 3x3 rotation matrix around z-axis.
The function computes a RQ decomposition using the given rotations. This function is used in
decomposeProjectionMatrix to decompose the left 3x3 submatrix of a projection matrix into a camera
#decomposeProjectionMatrix to decompose the left 3x3 submatrix of a projection matrix into a camera
and a rotation matrix.
It optionally returns three rotation matrices, one for each axis, and the three Euler angles in
@@ -676,7 +676,7 @@ be used in OpenGL. Note, there is always more than one sequence of rotations abo
principal axes that results in the same orientation of an object, e.g. see @cite Slabaugh . Returned
tree rotation matrices and corresponding three Euler angles are only one of the possible solutions.
The function is based on RQDecomp3x3 .
The function is based on #RQDecomp3x3 .
*/
CV_EXPORTS_W void decomposeProjectionMatrix( InputArray projMatrix, OutputArray cameraMatrix,
OutputArray rotMatrix, OutputArray transVect,
@@ -696,7 +696,7 @@ CV_EXPORTS_W void decomposeProjectionMatrix( InputArray projMatrix, OutputArray
The function computes partial derivatives of the elements of the matrix product \f$A*B\f$ with regard to
the elements of each of the two input matrices. The function is used to compute the Jacobian
matrices in stereoCalibrate but can also be used in any other similar optimization function.
matrices in #stereoCalibrate but can also be used in any other similar optimization function.
*/
CV_EXPORTS_W void matMulDeriv( InputArray A, InputArray B, OutputArray dABdA, OutputArray dABdB );
@@ -722,10 +722,10 @@ The functions compute:
\f[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\f]
where \f$\mathrm{rodrigues}\f$ denotes a rotation vector to a rotation matrix transformation, and
\f$\mathrm{rodrigues}^{-1}\f$ denotes the inverse transformation. See Rodrigues for details.
\f$\mathrm{rodrigues}^{-1}\f$ denotes the inverse transformation. See #Rodrigues for details.
Also, the functions can compute the derivatives of the output vectors with regards to the input
vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in
vectors (see #matMulDeriv ). The functions are used inside #stereoCalibrate but can also be used in
your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a
function that contains a matrix multiplication.
*/
@@ -1084,7 +1084,7 @@ calibrateCamera for details.
old interface all the per-view vectors are concatenated.
@param imageSize Image size in pixels used to initialize the principal point.
@param aspectRatio If it is zero or negative, both \f$f_x\f$ and \f$f_y\f$ are estimated independently.
Otherwise, \f$f_x = f_y * \texttt{aspectRatio}\f$ .
Otherwise, \f$f_x = f_y \cdot \texttt{aspectRatio}\f$ .
The function estimates and returns an initial camera intrinsic matrix for the camera calibration process.
Currently, the function only supports planar calibration patterns, which are patterns where each
@@ -1098,12 +1098,12 @@ CV_EXPORTS_W Mat initCameraMatrix2D( InputArrayOfArrays objectPoints,
@param image Source chessboard view. It must be an 8-bit grayscale or color image.
@param patternSize Number of inner corners per a chessboard row and column
( patternSize = cvSize(points_per_row,points_per_colum) = cvSize(columns,rows) ).
( patternSize = cv::Size(points_per_row,points_per_colum) = cv::Size(columns,rows) ).
@param corners Output array of detected corners.
@param flags Various operation flags that can be zero or a combination of the following values:
- @ref CALIB_CB_ADAPTIVE_THRESH Use adaptive thresholding to convert the image to black
and white, rather than a fixed threshold level (computed from the average image brightness).
- @ref CALIB_CB_NORMALIZE_IMAGE Normalize the image gamma with equalizeHist before
- @ref CALIB_CB_NORMALIZE_IMAGE Normalize the image gamma with #equalizeHist before
applying fixed or adaptive thresholding.
- @ref CALIB_CB_FILTER_QUADS Use additional criteria (like contour area, perimeter,
square-like shape) to filter out false quads extracted at the contour retrieval stage.
@@ -1117,7 +1117,7 @@ are found and they are placed in a certain order (row by row, left to right in e
Otherwise, if the function fails to find all the corners or reorder them, it returns 0. For example,
a regular chessboard has 8 x 8 squares and 7 x 7 internal corners, that is, points where the black
squares touch each other. The detected coordinates are approximate, and to determine their positions
more accurately, the function calls cornerSubPix. You also may use the function cornerSubPix with
more accurately, the function calls #cornerSubPix. You also may use the function #cornerSubPix with
different parameters if returned coordinates are not accurate enough.
Sample usage of detecting and drawing chessboard corners: :
@@ -1154,9 +1154,9 @@ CV_EXPORTS_W bool find4QuadCornerSubpix( InputArray img, InputOutputArray corner
@param image Destination image. It must be an 8-bit color image.
@param patternSize Number of inner corners per a chessboard row and column
(patternSize = cv::Size(points_per_row,points_per_column)).
@param corners Array of detected corners, the output of findChessboardCorners.
@param corners Array of detected corners, the output of #findChessboardCorners.
@param patternWasFound Parameter indicating whether the complete board was found or not. The
return value of findChessboardCorners should be passed here.
return value of #findChessboardCorners should be passed here.
The function draws individual chessboard corners detected either as red circles if the board was not
found, or as colored corners connected with lines if the board was found.
@@ -1542,7 +1542,7 @@ Besides the stereo-related information, the function can also perform a full cal
the two cameras. However, due to the high dimensionality of the parameter space and noise in the
input data, the function can diverge from the correct solution. If the intrinsic parameters can be
estimated with high accuracy for each of the cameras individually (for example, using
calibrateCamera ), you are recommended to do so and then pass @ref CALIB_FIX_INTRINSIC flag to the
#calibrateCamera ), you are recommended to do so and then pass @ref CALIB_FIX_INTRINSIC flag to the
function along with the computed intrinsic parameters. Otherwise, if all the parameters are
estimated at once, it makes sense to restrict some parameters, for example, pass
@ref CALIB_SAME_FOCAL_LENGTH and @ref CALIB_ZERO_TANGENT_DIST flags, which is usually a
@@ -1608,7 +1608,7 @@ pixels from the original images from the cameras are retained in the rectified i
image pixels are lost). Any intermediate value yields an intermediate result between
those two extreme cases.
@param newImageSize New image resolution after rectification. The same size should be passed to
initUndistortRectifyMap (see the stereo_calib.cpp sample in OpenCV samples directory). When (0,0)
#initUndistortRectifyMap (see the stereo_calib.cpp sample in OpenCV samples directory). When (0,0)
is passed (default), it is set to the original imageSize . Setting it to a larger value can help you
preserve details in the original image, especially when there is a big radial distortion.
@param validPixROI1 Optional output rectangles inside the rectified images where all the pixels
@@ -1620,7 +1620,7 @@ are valid. If alpha=0 , the ROIs cover the whole images. Otherwise, they are lik
The function computes the rotation matrices for each camera that (virtually) make both camera image
planes the same plane. Consequently, this makes all the epipolar lines parallel and thus simplifies
the dense stereo correspondence problem. The function takes the matrices computed by stereoCalibrate
the dense stereo correspondence problem. The function takes the matrices computed by #stereoCalibrate
as input. As output, it provides two rotation matrices and also two projection matrices in the new
coordinates. The function distinguishes the following two cases:
@@ -1636,11 +1636,18 @@ coordinates. The function distinguishes the following two cases:
\end{bmatrix}\f]
\f[\texttt{P2} = \begin{bmatrix}
f & 0 & cx_2 & T_x*f \\
f & 0 & cx_2 & T_x \cdot f \\
0 & f & cy & 0 \\
0 & 0 & 1 & 0
\end{bmatrix} ,\f]
\f[\texttt{Q} = \begin{bmatrix}
1 & 0 & 0 & -cx_1 \\
0 & 1 & 0 & -cy \\
0 & 0 & 0 & f \\
0 & 0 & -\frac{1}{T_x} & \frac{cx_1 - cx_2}{T_x}
\end{bmatrix} \f]
where \f$T_x\f$ is a horizontal shift between the cameras and \f$cx_1=cx_2\f$ if
@ref CALIB_ZERO_DISPARITY is set.
@@ -1656,15 +1663,22 @@ coordinates. The function distinguishes the following two cases:
\f[\texttt{P2} = \begin{bmatrix}
f & 0 & cx & 0 \\
0 & f & cy_2 & T_y*f \\
0 & f & cy_2 & T_y \cdot f \\
0 & 0 & 1 & 0
\end{bmatrix},\f]
\f[\texttt{Q} = \begin{bmatrix}
1 & 0 & 0 & -cx \\
0 & 1 & 0 & -cy_1 \\
0 & 0 & 0 & f \\
0 & 0 & -\frac{1}{T_y} & \frac{cy_1 - cy_2}{T_y}
\end{bmatrix} \f]
where \f$T_y\f$ is a vertical shift between the cameras and \f$cy_1=cy_2\f$ if
@ref CALIB_ZERO_DISPARITY is set.
As you can see, the first three columns of P1 and P2 will effectively be the new "rectified" camera
matrices. The matrices, together with R1 and R2 , can then be passed to initUndistortRectifyMap to
matrices. The matrices, together with R1 and R2 , can then be passed to #initUndistortRectifyMap to
initialize the rectification map for each camera.
See below the screenshot from the stereo_calib.cpp sample. Some red horizontal lines pass through
@@ -1687,20 +1701,20 @@ CV_EXPORTS_W void stereoRectify( InputArray cameraMatrix1, InputArray distCoeffs
@param points1 Array of feature points in the first image.
@param points2 The corresponding points in the second image. The same formats as in
findFundamentalMat are supported.
#findFundamentalMat are supported.
@param F Input fundamental matrix. It can be computed from the same set of point pairs using
findFundamentalMat .
#findFundamentalMat .
@param imgSize Size of the image.
@param H1 Output rectification homography matrix for the first image.
@param H2 Output rectification homography matrix for the second image.
@param threshold Optional threshold used to filter out the outliers. If the parameter is greater
than zero, all the point pairs that do not comply with the epipolar geometry (that is, the points
for which \f$|\texttt{points2[i]}^T*\texttt{F}*\texttt{points1[i]}|>\texttt{threshold}\f$ ) are
rejected prior to computing the homographies. Otherwise, all the points are considered inliers.
for which \f$|\texttt{points2[i]}^T \cdot \texttt{F} \cdot \texttt{points1[i]}|>\texttt{threshold}\f$ )
are rejected prior to computing the homographies. Otherwise, all the points are considered inliers.
The function computes the rectification transformations without knowing intrinsic parameters of the
cameras and their relative position in the space, which explains the suffix "uncalibrated". Another
related difference from stereoRectify is that the function outputs not the rectification
related difference from #stereoRectify is that the function outputs not the rectification
transformations in the object (3D) space, but the planar perspective transformations encoded by the
homography matrices H1 and H2 . The function implements the algorithm @cite Hartley99 .
@@ -1709,8 +1723,8 @@ homography matrices H1 and H2 . The function implements the algorithm @cite Hart
depends on the epipolar geometry. Therefore, if the camera lenses have a significant distortion,
it would be better to correct it before computing the fundamental matrix and calling this
function. For example, distortion coefficients can be estimated for each head of stereo camera
separately by using calibrateCamera . Then, the images can be corrected using undistort , or
just the point coordinates can be corrected with undistortPoints .
separately by using #calibrateCamera . Then, the images can be corrected using #undistort , or
just the point coordinates can be corrected with #undistortPoints .
*/
CV_EXPORTS_W bool stereoRectifyUncalibrated( InputArray points1, InputArray points2,
InputArray F, Size imgSize,
@@ -1738,10 +1752,10 @@ assumed.
@param imageSize Original image size.
@param alpha Free scaling parameter between 0 (when all the pixels in the undistorted image are
valid) and 1 (when all the source image pixels are retained in the undistorted image). See
stereoRectify for details.
#stereoRectify for details.
@param newImgSize Image size after rectification. By default, it is set to imageSize .
@param validPixROI Optional output rectangle that outlines all-good-pixels region in the
undistorted image. See roi1, roi2 description in stereoRectify .
undistorted image. See roi1, roi2 description in #stereoRectify .
@param centerPrincipalPoint Optional flag that indicates whether in the new camera intrinsic matrix the
principal point should be at the image center or not. By default, the principal point is chosen to
best fit a subset of the source image (determined by alpha) to the corrected image.
@@ -1753,7 +1767,7 @@ image pixels if there is valuable information in the corners alpha=1 , or get so
When alpha\>0 , the undistorted result is likely to have some black pixels corresponding to
"virtual" pixels outside of the captured distorted image. The original camera intrinsic matrix, distortion
coefficients, the computed new camera intrinsic matrix, and newImageSize should be passed to
initUndistortRectifyMap to produce the maps for remap .
#initUndistortRectifyMap to produce the maps for #remap .
*/
CV_EXPORTS_W Mat getOptimalNewCameraMatrix( InputArray cameraMatrix, InputArray distCoeffs,
Size imageSize, double alpha, Size newImgSize = Size(),
@@ -1920,7 +1934,7 @@ CV_EXPORTS_W void convertPointsFromHomogeneous( InputArray src, OutputArray dst
@param dst Output vector of 2D, 3D, or 4D points.
The function converts 2D or 3D points from/to homogeneous coordinates by calling either
convertPointsToHomogeneous or convertPointsFromHomogeneous.
#convertPointsToHomogeneous or #convertPointsFromHomogeneous.
@note The function is obsolete. Use one of the previous two functions instead.
*/
@@ -1957,9 +1971,9 @@ the found fundamental matrix. Normally just one matrix is found. But in case of
algorithm, the function may return up to 3 solutions ( \f$9 \times 3\f$ matrix that stores all 3
matrices sequentially).
The calculated fundamental matrix may be passed further to computeCorrespondEpilines that finds the
The calculated fundamental matrix may be passed further to #computeCorrespondEpilines that finds the
epipolar lines corresponding to the specified points. It can also be passed to
stereoRectifyUncalibrated to compute the rectification transformation. :
#stereoRectifyUncalibrated to compute the rectification transformation. :
@code
// Example. Estimation of fundamental matrix using the RANSAC algorithm
int point_count = 100;
@@ -2023,7 +2037,7 @@ This function estimates essential matrix based on the five-point algorithm solve
where \f$E\f$ is an essential matrix, \f$p_1\f$ and \f$p_2\f$ are corresponding points in the first and the
second images, respectively. The result of this function may be passed further to
decomposeEssentialMat or recoverPose to recover the relative pose between cameras.
#decomposeEssentialMat or #recoverPose to recover the relative pose between cameras.
*/
CV_EXPORTS_W Mat findEssentialMat( InputArray points1, InputArray points2,
InputArray cameraMatrix, int method,
@@ -2099,7 +2113,7 @@ unit length.
CV_EXPORTS_W void decomposeEssentialMat( InputArray E, OutputArray R1, OutputArray R2, OutputArray t );
/** @brief Recovers the relative camera rotation and the translation from an estimated essential
matrix and the corresponding points in two images, using cheirality check. Returns the number of
matrix and the corresponding points in two images, using chirality check. Returns the number of
inliers that pass the check.
@param E The input essential matrix.
@@ -2117,11 +2131,11 @@ described below.
therefore is only known up to scale, i.e. t is the direction of the translation vector and has unit
length.
@param mask Input/output mask for inliers in points1 and points2. If it is not empty, then it marks
inliers in points1 and points2 for then given essential matrix E. Only these inliers will be used to
recover pose. In the output mask only inliers which pass the cheirality check.
inliers in points1 and points2 for the given essential matrix E. Only these inliers will be used to
recover pose. In the output mask only inliers which pass the chirality check.
This function decomposes an essential matrix using @ref decomposeEssentialMat and then verifies
possible pose hypotheses by doing cheirality check. The cheirality check means that the
possible pose hypotheses by doing chirality check. The chirality check means that the
triangulated 3D points should have positive depth. Some details can be found in @cite Nister03.
This function can be used to process the output E and mask from @ref findEssentialMat. In this
@@ -2168,8 +2182,8 @@ length.
are feature points from cameras with same focal length and principal point.
@param pp principal point of the camera.
@param mask Input/output mask for inliers in points1 and points2. If it is not empty, then it marks
inliers in points1 and points2 for then given essential matrix E. Only these inliers will be used to
recover pose. In the output mask only inliers which pass the cheirality check.
inliers in points1 and points2 for the given essential matrix E. Only these inliers will be used to
recover pose. In the output mask only inliers which pass the chirality check.
This function differs from the one above that it computes camera intrinsic matrix from focal length and
principal point:
@@ -2204,12 +2218,12 @@ length.
@param distanceThresh threshold distance which is used to filter out far away points (i.e. infinite
points).
@param mask Input/output mask for inliers in points1 and points2. If it is not empty, then it marks
inliers in points1 and points2 for then given essential matrix E. Only these inliers will be used to
recover pose. In the output mask only inliers which pass the cheirality check.
inliers in points1 and points2 for the given essential matrix E. Only these inliers will be used to
recover pose. In the output mask only inliers which pass the chirality check.
@param triangulatedPoints 3D points which were reconstructed by triangulation.
This function differs from the one above that it outputs the triangulated 3D point that are used for
the cheirality check.
the chirality check.
*/
CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray points2,
InputArray cameraMatrix, OutputArray R, OutputArray t, double distanceThresh, InputOutputArray mask = noArray(),
@@ -2220,14 +2234,14 @@ CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray point
@param points Input points. \f$N \times 1\f$ or \f$1 \times N\f$ matrix of type CV_32FC2 or
vector\<Point2f\> .
@param whichImage Index of the image (1 or 2) that contains the points .
@param F Fundamental matrix that can be estimated using findFundamentalMat or stereoRectify .
@param F Fundamental matrix that can be estimated using #findFundamentalMat or #stereoRectify .
@param lines Output vector of the epipolar lines corresponding to the points in the other image.
Each line \f$ax + by + c=0\f$ is encoded by 3 numbers \f$(a, b, c)\f$ .
For every point in one of the two images of a stereo pair, the function finds the equation of the
corresponding epipolar line in the other image.
From the fundamental matrix definition (see findFundamentalMat ), line \f$l^{(2)}_i\f$ in the second
From the fundamental matrix definition (see #findFundamentalMat ), line \f$l^{(2)}_i\f$ in the second
image for the point \f$p^{(1)}_i\f$ in the first image (when whichImage=1 ) is computed as:
\f[l^{(2)}_i = F p^{(1)}_i\f]
@@ -2277,12 +2291,12 @@ CV_EXPORTS_W void triangulatePoints( InputArray projMatr1, InputArray projMatr2,
@param newPoints1 The optimized points1.
@param newPoints2 The optimized points2.
The function implements the Optimal Triangulation Method (see Multiple View Geometry for details).
The function implements the Optimal Triangulation Method (see Multiple View Geometry @cite HartleyZ00 for details).
For each given point correspondence points1[i] \<-\> points2[i], and a fundamental matrix F, it
computes the corrected correspondences newPoints1[i] \<-\> newPoints2[i] that minimize the geometric
error \f$d(points1[i], newPoints1[i])^2 + d(points2[i],newPoints2[i])^2\f$ (where \f$d(a,b)\f$ is the
geometric distance between points \f$a\f$ and \f$b\f$ ) subject to the epipolar constraint
\f$newPoints2^T * F * newPoints1 = 0\f$ .
\f$newPoints2^T \cdot F \cdot newPoints1 = 0\f$ .
*/
CV_EXPORTS_W void correctMatches( InputArray F, InputArray points1, InputArray points2,
OutputArray newPoints1, OutputArray newPoints2 );
@@ -2559,7 +2573,7 @@ Check @ref tutorial_homography "the corresponding tutorial" for more details.
This function extracts relative camera motion between two views of a planar object and returns up to
four mathematical solution tuples of rotation, translation, and plane normal. The decomposition of
the homography matrix H is described in detail in @cite Malis.
the homography matrix H is described in detail in @cite Malis2007.
If the homography H, induced by the plane, gives the constraint
\f[s_i \vecthree{x'_i}{y'_i}{1} \sim H \vecthree{x_i}{y_i}{1}\f] on the source image points
@@ -2584,10 +2598,10 @@ CV_EXPORTS_W int decomposeHomographyMat(InputArray H,
@param beforePoints Vector of (rectified) visible reference points before the homography is applied
@param afterPoints Vector of (rectified) visible reference points after the homography is applied
@param possibleSolutions Vector of int indices representing the viable solution set after filtering
@param pointsMask optional Mat/Vector of 8u type representing the mask for the inliers as given by the findHomography function
@param pointsMask optional Mat/Vector of 8u type representing the mask for the inliers as given by the #findHomography function
This function is intended to filter the output of the decomposeHomographyMat based on additional
information as described in @cite Malis . The summary of the method: the decomposeHomographyMat function
This function is intended to filter the output of the #decomposeHomographyMat based on additional
information as described in @cite Malis2007 . The summary of the method: the #decomposeHomographyMat function
returns 2 unique solutions and their "opposites" for a total of 4 solutions. If we have access to the
sets of points visible in the camera frame before and after the homography transformation is applied,
we can determine which are the true potential solutions and which are the opposites by verifying which
@@ -2977,14 +2991,14 @@ optimization. It stays at the center or at a different location specified when @
camera.
@param P2 Output 3x4 projection matrix in the new (rectified) coordinate systems for the second
camera.
@param Q Output \f$4 \times 4\f$ disparity-to-depth mapping matrix (see reprojectImageTo3D ).
@param Q Output \f$4 \times 4\f$ disparity-to-depth mapping matrix (see #reprojectImageTo3D ).
@param flags Operation flags that may be zero or @ref fisheye::CALIB_ZERO_DISPARITY . If the flag is set,
the function makes the principal points of each camera have the same pixel coordinates in the
rectified views. And if the flag is not set, the function may still shift the images in the
horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the
useful image area.
@param newImageSize New image resolution after rectification. The same size should be passed to
initUndistortRectifyMap (see the stereo_calib.cpp sample in OpenCV samples directory). When (0,0)
#initUndistortRectifyMap (see the stereo_calib.cpp sample in OpenCV samples directory). When (0,0)
is passed (default), it is set to the original imageSize . Setting it to larger value can help you
preserve details in the original image, especially when there is a big radial distortion.
@param balance Sets the new focal length in range between the min focal length and the max focal
@@ -699,10 +699,10 @@ public class Calib3dTest extends OpenCVTestCase {
D.put(2,0,-0.021509225493198905);
D.put(3,0,0.0043378096628297145);
K_new_truth.put(0,0, 387.4809086880343);
K_new_truth.put(0,2, 1036.669802754649);
K_new_truth.put(1,1, 373.6375700303157);
K_new_truth.put(1,2, 538.8373261247601);
K_new_truth.put(0,0, 387.5118215642316);
K_new_truth.put(0,2, 1033.936556777084);
K_new_truth.put(1,1, 373.6673784974842);
K_new_truth.put(1,2, 538.794152656429);
Calib3d.fisheye_estimateNewCameraMatrixForUndistortRectify(K,D,new Size(1920,1080),
new Mat().eye(3, 3, CvType.CV_64F), K_new, 0.0, new Size(1920,1080));
+3 -2
View File
@@ -1232,7 +1232,7 @@ int ChessBoardDetector::cleanFoundConnectedQuads(std::vector<ChessBoardQuad*>& q
centers[i] = ci;
center += ci;
}
center.x *= (1.0f / quad_count);
center *= (1.0f / quad_count);
// If we still have more quadrangles than we should,
// we try to eliminate bad ones based on minimizing the bounding box.
@@ -1256,7 +1256,7 @@ int ChessBoardDetector::cleanFoundConnectedQuads(std::vector<ChessBoardQuad*>& q
Mat points(1, quad_count, CV_32FC2, &centers[0]);
cv::convexHull(points, hull, true);
centers[skip] = temp;
double hull_area = contourArea(hull, true);
double hull_area = contourArea(hull, false);
// remember smallest box area
if (hull_area < min_box_area)
@@ -1298,6 +1298,7 @@ int ChessBoardDetector::cleanFoundConnectedQuads(std::vector<ChessBoardQuad*>& q
quad_group[min_box_area_index] = quad_group[quad_count];
centers[min_box_area_index] = centers[quad_count];
}
quad_group.resize(quad_count);
return quad_count;
}
+2 -2
View File
@@ -388,7 +388,7 @@ void cv::fisheye::undistortPoints( InputArray distorted, OutputArray undistorted
if (theta_d > 1e-8)
{
// compensate distortion iteratively
// compensate distortion iteratively using Newton method
double theta = theta_d;
const double EPS = 1e-8; // or std::numeric_limits<double>::epsilon();
@@ -572,7 +572,7 @@ void cv::fisheye::estimateNewCameraMatrixForUndistortRectify(InputArray K, Input
: K.getMat().at<double>(0,0)/K.getMat().at<double>(1,1);
// convert to identity ratio
cn[0] *= aspect_ratio;
cn[1] *= aspect_ratio;
for(size_t i = 0; i < points.total(); ++i)
pptr[i][1] *= aspect_ratio;
+1 -1
View File
@@ -520,7 +520,7 @@ int cv::recoverPose( InputArray E, InputArray _points1, InputArray _points2,
P3(Range::all(), Range(0, 3)) = R1 * 1.0; P3.col(3) = -t * 1.0;
P4(Range::all(), Range(0, 3)) = R2 * 1.0; P4.col(3) = -t * 1.0;
// Do the cheirality check.
// Do the chirality check.
// Notice here a threshold dist is used to filter
// out far away points (i.e. infinite points) since
// their depth may vary between positive and negative.
+11 -4
View File
@@ -149,12 +149,13 @@ public:
int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
{
Mat opoints = _m1.getMat(), ipoints = _m2.getMat();
Mat iter_rvec = rvec.clone();
Mat iter_tvec = tvec.clone();
bool correspondence = solvePnP( _m1, _m2, cameraMatrix, distCoeffs,
rvec, tvec, useExtrinsicGuess, flags );
iter_rvec, iter_tvec, useExtrinsicGuess, flags );
Mat _local_model;
hconcat(rvec, tvec, _local_model);
hconcat(iter_rvec, iter_tvec, _local_model);
_local_model.copyTo(_model);
return correspondence;
@@ -313,7 +314,13 @@ bool solvePnPRansac(InputArray _opoints, InputArray _ipoints,
ipoints_inliers.resize(npoints1);
try
{
result = solvePnP(opoints_inliers, ipoints_inliers, cameraMatrix,
if (flags == SOLVEPNP_ITERATIVE && !useExtrinsicGuess)
{
rvec = _local_model.col(0).clone();
tvec = _local_model.col(1).clone();
useExtrinsicGuess = true;
}
result = solvePnP(opoints_inliers, ipoints_inliers, cameraMatrix,
distCoeffs, rvec, tvec, useExtrinsicGuess,
(flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P) ? SOLVEPNP_EPNP : flags) ? 1 : -1;
}
+1 -1
View File
@@ -111,7 +111,7 @@ private:
static double det3x3(const cv::Matx<double, 9, 1>& e);
/*
* @brief Tests the cheirality for a given solution.
* @brief Tests the chirality for a given solution.
* @param solution The solution to evaluate.
*/
inline bool positiveDepth(const SQPSolution& solution) const;
+47 -27
View File
@@ -101,6 +101,15 @@ TEST_F(fisheyeTest, projectPoints)
EXPECT_MAT_NEAR(distorted0, distorted2, 1e-10);
}
// we use it to reduce patch size for images in testdata
static void throwAwayHalf(Mat img)
{
int whalf = img.cols / 2, hhalf = img.rows / 2;
Rect tl(0, 0, whalf, hhalf), br(whalf, hhalf, whalf, hhalf);
img(tl) = 0;
img(br) = 0;
};
TEST_F(fisheyeTest, undistortImage)
{
cv::Matx33d theK = this->K;
@@ -112,32 +121,41 @@ TEST_F(fisheyeTest, undistortImage)
newK(0, 0) = 100;
newK(1, 1) = 100;
cv::fisheye::undistortImage(distorted, undistorted, theK, theD, newK);
cv::Mat correct = cv::imread(combine(datasets_repository_path, "new_f_100.png"));
if (correct.empty())
CV_Assert(cv::imwrite(combine(datasets_repository_path, "new_f_100.png"), undistorted));
else
EXPECT_MAT_NEAR(correct, undistorted, 1e-10);
std::string imageFilename = combine(datasets_repository_path, "new_f_100.png");
cv::Mat correct = cv::imread(imageFilename);
ASSERT_FALSE(correct.empty()) << "Correct image " << imageFilename.c_str() << " can not be read" << std::endl;
throwAwayHalf(correct);
throwAwayHalf(undistorted);
EXPECT_MAT_NEAR(correct, undistorted, 1e-10);
}
{
double balance = 1.0;
cv::fisheye::estimateNewCameraMatrixForUndistortRectify(theK, theD, distorted.size(), cv::noArray(), newK, balance);
cv::fisheye::undistortImage(distorted, undistorted, theK, theD, newK);
cv::Mat correct = cv::imread(combine(datasets_repository_path, "balance_1.0.png"));
if (correct.empty())
CV_Assert(cv::imwrite(combine(datasets_repository_path, "balance_1.0.png"), undistorted));
else
EXPECT_MAT_NEAR(correct, undistorted, 1e-10);
std::string imageFilename = combine(datasets_repository_path, "balance_1.0.png");
cv::Mat correct = cv::imread(imageFilename);
ASSERT_FALSE(correct.empty()) << "Correct image " << imageFilename.c_str() << " can not be read" << std::endl;
throwAwayHalf(correct);
throwAwayHalf(undistorted);
EXPECT_MAT_NEAR(correct, undistorted, 1e-10);
}
{
double balance = 0.0;
cv::fisheye::estimateNewCameraMatrixForUndistortRectify(theK, theD, distorted.size(), cv::noArray(), newK, balance);
cv::fisheye::undistortImage(distorted, undistorted, theK, theD, newK);
cv::Mat correct = cv::imread(combine(datasets_repository_path, "balance_0.0.png"));
if (correct.empty())
CV_Assert(cv::imwrite(combine(datasets_repository_path, "balance_0.0.png"), undistorted));
else
EXPECT_MAT_NEAR(correct, undistorted, 1e-10);
std::string imageFilename = combine(datasets_repository_path, "balance_0.0.png");
cv::Mat correct = cv::imread(imageFilename);
ASSERT_FALSE(correct.empty()) << "Correct image " << imageFilename.c_str() << " can not be read" << std::endl;
throwAwayHalf(correct);
throwAwayHalf(undistorted);
EXPECT_MAT_NEAR(correct, undistorted, 1e-10);
}
}
@@ -422,19 +440,19 @@ TEST_F(fisheyeTest, stereoRectify)
0.002076471801477729, 0.006463478587068991, 0.9999769555891836
);
cv::Matx34d P1_ref(
420.8551870450913, 0, 586.501617798451, 0,
0, 420.8551870450913, 374.7667511986098, 0,
420.9684016542647, 0, 586.3059567784627, 0,
0, 420.9684016542647, 374.8571836462291, 0,
0, 0, 1, 0
);
cv::Matx34d P2_ref(
420.8551870450913, 0, 586.501617798451, -41.77758076597302,
0, 420.8551870450913, 374.7667511986098, 0,
420.9684016542647, 0, 586.3059567784627, -41.78881938824554,
0, 420.9684016542647, 374.8571836462291, 0,
0, 0, 1, 0
);
cv::Matx44d Q_ref(
1, 0, 0, -586.501617798451,
0, 1, 0, -374.7667511986098,
0, 0, 0, 420.8551870450913,
1, 0, 0, -586.3059567784627,
0, 1, 0, -374.8571836462291,
0, 0, 0, 420.9684016542647,
0, 0, 10.07370889670733, -0
);
@@ -489,7 +507,9 @@ TEST_F(fisheyeTest, stereoRectify)
cv::Mat rectification;
merge4(l, r, lundist, rundist, rectification);
cv::imwrite(cv::format("fisheye_rectification_AB_%03d.png", i), rectification);
// Add the "--test_debug" to arguments for file output
if (cvtest::debugLevel > 0)
cv::imwrite(cv::format("fisheye_rectification_AB_%03d.png", i), rectification);
}
}
@@ -683,13 +703,13 @@ TEST_F(fisheyeTest, estimateNewCameraMatrixForUndistortRectify)
cv::Mat K_new_truth(3, 3, cv::DataType<double>::type);
K_new_truth.at<double>(0, 0) = 387.4809086880343;
K_new_truth.at<double>(0, 0) = 387.5118215642316;
K_new_truth.at<double>(0, 1) = 0.0;
K_new_truth.at<double>(0, 2) = 1036.669802754649;
K_new_truth.at<double>(0, 2) = 1033.936556777084;
K_new_truth.at<double>(1, 0) = 0.0;
K_new_truth.at<double>(1, 1) = 373.6375700303157;
K_new_truth.at<double>(1, 2) = 538.8373261247601;
K_new_truth.at<double>(1, 1) = 373.6673784974842;
K_new_truth.at<double>(1, 2) = 538.794152656429;
K_new_truth.at<double>(2, 0) = 0.0;
K_new_truth.at<double>(2, 1) = 0.0;
+1 -1
View File
@@ -6,7 +6,7 @@ ocv_add_dispatched_file(arithm SSE2 SSE4_1 AVX2 VSX3)
ocv_add_dispatched_file(convert SSE2 AVX2 VSX3)
ocv_add_dispatched_file(convert_scale SSE2 AVX2)
ocv_add_dispatched_file(count_non_zero SSE2 AVX2)
ocv_add_dispatched_file(matmul SSE2 SSE4_1 AVX2 AVX512_SKX)
ocv_add_dispatched_file(matmul SSE2 SSE4_1 AVX2 AVX512_SKX NEON_DOTPROD)
ocv_add_dispatched_file(mean SSE2 AVX2)
ocv_add_dispatched_file(merge SSE2 AVX2)
ocv_add_dispatched_file(split SSE2 AVX2)
+12 -12
View File
@@ -71,7 +71,7 @@ data sharing. A destructor decrements the reference counter associated with the
The buffer is deallocated if and only if the reference counter reaches zero, that is, when no other
structures refer to the same buffer. Similarly, when a Mat instance is copied, no actual data is
really copied. Instead, the reference counter is incremented to memorize that there is another owner
of the same data. There is also the Mat::clone method that creates a full copy of the matrix data.
of the same data. There is also the cv::Mat::clone method that creates a full copy of the matrix data.
See the example below:
```.cpp
// create a big 8Mb matrix
@@ -159,11 +159,11 @@ grayscale conversion. Note that frame and edges are allocated only once during t
of the loop body since all the next video frames have the same resolution. If you somehow change the
video resolution, the arrays are automatically reallocated.
The key component of this technology is the Mat::create method. It takes the desired array size and
type. If the array already has the specified size and type, the method does nothing. Otherwise, it
releases the previously allocated data, if any (this part involves decrementing the reference
The key component of this technology is the cv::Mat::create method. It takes the desired array size
and type. If the array already has the specified size and type, the method does nothing. Otherwise,
it releases the previously allocated data, if any (this part involves decrementing the reference
counter and comparing it with zero), and then allocates a new buffer of the required size. Most
functions call the Mat::create method for each output array, and so the automatic output data
functions call the cv::Mat::create method for each output array, and so the automatic output data
allocation is implemented.
Some notable exceptions from this scheme are cv::mixChannels, cv::RNG::fill, and a few other
@@ -247,9 +247,9 @@ Examples:
// matrix (10-element complex vector)
Mat img(Size(1920, 1080), CV_8UC3); // make a 3-channel (color) image
// of 1920 columns and 1080 rows.
Mat grayscale(image.size(), CV_MAKETYPE(image.depth(), 1)); // make a 1-channel image of
// the same size and same
// channel type as img
Mat grayscale(img.size(), CV_MAKETYPE(img.depth(), 1)); // make a 1-channel image of
// the same size and same
// channel type as img
```
Arrays with more complex elements cannot be constructed or processed using OpenCV. Furthermore, each
function or method can handle only a subset of all possible array types. Usually, the more complex
@@ -269,14 +269,14 @@ extended in future based on user requests.
### InputArray and OutputArray
Many OpenCV functions process dense 2-dimensional or multi-dimensional numerical arrays. Usually,
such functions take cppMat as parameters, but in some cases it's more convenient to use
such functions take `cv::Mat` as parameters, but in some cases it's more convenient to use
`std::vector<>` (for a point set, for example) or `cv::Matx<>` (for 3x3 homography matrix and such). To
avoid many duplicates in the API, special "proxy" classes have been introduced. The base "proxy"
class is cv::InputArray. It is used for passing read-only arrays on a function input. The derived from
InputArray class cv::OutputArray is used to specify an output array for a function. Normally, you should
not care of those intermediate types (and you should not declare variables of those types
explicitly) - it will all just work automatically. You can assume that instead of
InputArray/OutputArray you can always use `Mat`, `std::vector<>`, `cv::Matx<>`, `cv::Vec<>` or `cv::Scalar`. When a
InputArray/OutputArray you can always use `cv::Mat`, `std::vector<>`, `cv::Matx<>`, `cv::Vec<>` or `cv::Scalar`. When a
function has an optional input or output array, and you do not have or do not want one, pass
cv::noArray().
@@ -288,7 +288,7 @@ the optimization algorithm did not converge), it returns a special error code (t
boolean variable).
The exceptions can be instances of the cv::Exception class or its derivatives. In its turn,
cv::Exception is a derivative of std::exception. So it can be gracefully handled in the code using
cv::Exception is a derivative of `std::exception`. So it can be gracefully handled in the code using
other standard C++ library components.
The exception is typically thrown either using the `#CV_Error(errcode, description)` macro, or its
@@ -297,7 +297,7 @@ printf-like `#CV_Error_(errcode, (printf-spec, printf-args))` variant, or using
satisfied. For performance-critical code, there is #CV_DbgAssert(condition) that is only retained in
the Debug configuration. Due to the automatic memory management, all the intermediate buffers are
automatically deallocated in case of a sudden error. You only need to add a try statement to catch
exceptions, if needed: :
exceptions, if needed:
```.cpp
try
{
+7 -3
View File
@@ -3095,12 +3095,16 @@ public:
/** @brief Stores algorithm parameters in a file storage
*/
virtual void write(FileStorage& fs) const { CV_UNUSED(fs); }
CV_WRAP virtual void write(FileStorage& fs) const { CV_UNUSED(fs); }
/** @brief simplified API for language bindings
/**
* @overload
*/
CV_WRAP void write(const Ptr<FileStorage>& fs, const String& name = String()) const;
CV_WRAP void write(FileStorage& fs, const String& name) const;
#if CV_VERSION_MAJOR < 5
/** @deprecated */
void write(const Ptr<FileStorage>& fs, const String& name = String()) const;
#endif
/** @brief Reads algorithm parameters from a file storage
*/
@@ -213,6 +213,17 @@ AsyncArray testAsyncException()
return p.getArrayResult();
}
struct CV_EXPORTS_W_SIMPLE ClassWithKeywordProperties {
CV_PROP_RW int lambda;
CV_PROP int except;
CV_WRAP explicit ClassWithKeywordProperties(int lambda_arg = 24, int except_arg = 42)
{
lambda = lambda_arg;
except = except_arg;
}
};
namespace nested {
CV_WRAP static inline bool testEchoBooleanFunction(bool flag) {
return flag;
@@ -65,6 +65,7 @@ struct CheckContext {
static const cv::detail::CheckContext CV__CHECK_LOCATION_VARNAME(id) = \
{ CV__CHECK_FUNCTION, CV__CHECK_FILENAME, __LINE__, testOp, "" message, "" p1_str, "" p2_str }
CV_EXPORTS void CV_NORETURN check_failed_auto(const bool v1, const bool v2, const CheckContext& ctx);
CV_EXPORTS void CV_NORETURN check_failed_auto(const int v1, const int v2, const CheckContext& ctx);
CV_EXPORTS void CV_NORETURN check_failed_auto(const size_t v1, const size_t v2, const CheckContext& ctx);
CV_EXPORTS void CV_NORETURN check_failed_auto(const float v1, const float v2, const CheckContext& ctx);
@@ -74,6 +75,9 @@ CV_EXPORTS void CV_NORETURN check_failed_MatDepth(const int v1, const int v2, co
CV_EXPORTS void CV_NORETURN check_failed_MatType(const int v1, const int v2, const CheckContext& ctx);
CV_EXPORTS void CV_NORETURN check_failed_MatChannels(const int v1, const int v2, const CheckContext& ctx);
CV_EXPORTS void CV_NORETURN check_failed_true(const bool v, const CheckContext& ctx);
CV_EXPORTS void CV_NORETURN check_failed_false(const bool v, const CheckContext& ctx);
CV_EXPORTS void CV_NORETURN check_failed_auto(const int v, const CheckContext& ctx);
CV_EXPORTS void CV_NORETURN check_failed_auto(const size_t v, const CheckContext& ctx);
CV_EXPORTS void CV_NORETURN check_failed_auto(const float v, const CheckContext& ctx);
@@ -134,6 +138,12 @@ CV_EXPORTS void CV_NORETURN check_failed_MatChannels(const int v, const CheckCon
/// Example: v == A || v == B
#define CV_Check(v, test_expr, msg) CV__CHECK_CUSTOM_TEST(_, auto, v, (test_expr), #v, #test_expr, msg)
/// Example: v == true
#define CV_CheckTrue(v, msg) CV__CHECK_CUSTOM_TEST(_, true, v, v, #v, "", msg)
/// Example: v == false
#define CV_CheckFalse(v, msg) CV__CHECK_CUSTOM_TEST(_, false, v, (!(v)), #v, "", msg)
/// Some complex conditions: CV_Check(src2, src2.empty() || (src2.type() == src1.type() && src2.size() == src1.size()), "src2 should have same size/type as src1")
// TODO define pretty-printers
@@ -488,8 +488,16 @@ public:
//! Allocates a new GpuMat of given size and type.
GpuMat getBuffer(int rows, int cols, int type);
// WARNING: unreachable code using Ninja
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(push)
#pragma warning(disable: 4702)
#endif
//! Allocates a new GpuMat of given size and type.
GpuMat getBuffer(Size size, int type) { return getBuffer(size.height, size.width, type); }
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(pop)
#endif
//! Returns the allocator associated with the stream.
Ptr<GpuMat::Allocator> getAllocator() const { return allocator_; }
@@ -75,6 +75,11 @@ GpuMat::GpuMat(Size size_, int type_, Allocator* allocator_)
create(size_.height, size_.width, type_);
}
// WARNING: unreachable code using Ninja
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(push)
#pragma warning(disable: 4702)
#endif
inline
GpuMat::GpuMat(int rows_, int cols_, int type_, Scalar s_, Allocator* allocator_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
@@ -96,6 +101,9 @@ GpuMat::GpuMat(Size size_, int type_, Scalar s_, Allocator* allocator_)
setTo(s_);
}
}
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(pop)
#endif
inline
GpuMat::GpuMat(const GpuMat& m)
@@ -158,11 +166,19 @@ GpuMat GpuMat::clone() const
return m;
}
// WARNING: unreachable code using Ninja
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(push)
#pragma warning(disable: 4702)
#endif
inline
void GpuMat::copyTo(OutputArray dst, InputArray mask) const
{
copyTo(dst, mask, Stream::Null());
}
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(pop)
#endif
inline
GpuMat& GpuMat::setTo(Scalar s)
@@ -176,6 +192,11 @@ GpuMat& GpuMat::setTo(Scalar s, InputArray mask)
return setTo(s, mask, Stream::Null());
}
// WARNING: unreachable code using Ninja
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(push)
#pragma warning(disable: 4702)
#endif
inline
void GpuMat::convertTo(OutputArray dst, int rtype) const
{
@@ -187,6 +208,9 @@ void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, double beta) co
{
convertTo(dst, rtype, alpha, beta, Stream::Null());
}
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(pop)
#endif
inline
void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, Stream& stream) const
@@ -554,6 +578,11 @@ Event::Event(const Ptr<Impl>& impl)
// Initialization & Info
//===================================================================================
// WARNING: unreachable code using Ninja
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(push)
#pragma warning(disable: 4702)
#endif
inline
bool TargetArchs::has(int major, int minor)
{
@@ -571,6 +600,9 @@ DeviceInfo::DeviceInfo()
{
device_id_ = getDevice();
}
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(pop)
#endif
inline
DeviceInfo::DeviceInfo(int device_id)
@@ -579,6 +611,11 @@ DeviceInfo::DeviceInfo(int device_id)
device_id_ = device_id;
}
// WARNING: unreachable code using Ninja
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(push)
#pragma warning(disable: 4702)
#endif
inline
int DeviceInfo::deviceID() const
{
@@ -607,6 +644,9 @@ bool DeviceInfo::supports(FeatureSet feature_set) const
int version = majorVersion() * 10 + minorVersion();
return version >= feature_set;
}
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(pop)
#endif
}} // namespace cv { namespace cuda {
@@ -79,6 +79,10 @@
# endif
# define CV_FP16 1
#endif
#ifdef CV_CPU_COMPILE_NEON_DOTPROD
# include <arm_neon.h>
# define CV_NEON_DOT 1
#endif
#ifdef CV_CPU_COMPILE_AVX2
# include <immintrin.h>
# define CV_AVX2 1
@@ -420,6 +420,27 @@
#endif
#define __CV_CPU_DISPATCH_CHAIN_NEON(fn, args, mode, ...) CV_CPU_CALL_NEON(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_NEON_DOTPROD
# define CV_TRY_NEON_DOTPROD 1
# define CV_CPU_FORCE_NEON_DOTPROD 1
# define CV_CPU_HAS_SUPPORT_NEON_DOTPROD 1
# define CV_CPU_CALL_NEON_DOTPROD(fn, args) return (cpu_baseline::fn args)
# define CV_CPU_CALL_NEON_DOTPROD_(fn, args) return (opt_NEON_DOTPROD::fn args)
#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_NEON_DOTPROD
# define CV_TRY_NEON_DOTPROD 1
# define CV_CPU_FORCE_NEON_DOTPROD 0
# define CV_CPU_HAS_SUPPORT_NEON_DOTPROD (cv::checkHardwareSupport(CV_CPU_NEON_DOTPROD))
# define CV_CPU_CALL_NEON_DOTPROD(fn, args) if (CV_CPU_HAS_SUPPORT_NEON_DOTPROD) return (opt_NEON_DOTPROD::fn args)
# define CV_CPU_CALL_NEON_DOTPROD_(fn, args) if (CV_CPU_HAS_SUPPORT_NEON_DOTPROD) return (opt_NEON_DOTPROD::fn args)
#else
# define CV_TRY_NEON_DOTPROD 0
# define CV_CPU_FORCE_NEON_DOTPROD 0
# define CV_CPU_HAS_SUPPORT_NEON_DOTPROD 0
# define CV_CPU_CALL_NEON_DOTPROD(fn, args)
# define CV_CPU_CALL_NEON_DOTPROD_(fn, args)
#endif
#define __CV_CPU_DISPATCH_CHAIN_NEON_DOTPROD(fn, args, mode, ...) CV_CPU_CALL_NEON_DOTPROD(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_MSA
# define CV_TRY_MSA 1
# define CV_CPU_FORCE_MSA 1
+3 -1
View File
@@ -282,6 +282,7 @@ namespace cv {
#define CV_CPU_AVX_5124FMAPS 27
#define CV_CPU_NEON 100
#define CV_CPU_NEON_DOTPROD 101
#define CV_CPU_MSA 150
@@ -334,6 +335,7 @@ enum CpuFeatures {
CPU_AVX_5124FMAPS = 27,
CPU_NEON = 100,
CPU_NEON_DOTPROD = 101,
CPU_MSA = 150,
@@ -721,7 +723,7 @@ Cv64suf;
// Integer types portatibility
// Integer types portability
#ifdef OPENCV_STDINT_HEADER
#include OPENCV_STDINT_HEADER
#elif defined(__cplusplus)
@@ -50,6 +50,12 @@
#include <stdlib.h>
#include "opencv2/core/cvdef.h"
#if defined(__GNUC__) && __GNUC__ == 12
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wuninitialized"
#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
#endif
#define OPENCV_HAL_ADD(a, b) ((a) + (b))
#define OPENCV_HAL_AND(a, b) ((a) & (b))
#define OPENCV_HAL_NOP(a) (a)
@@ -695,4 +701,8 @@ CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
//! @endcond
#if defined(__GNUC__) && __GNUC__ == 12
#pragma GCC diagnostic pop
#endif
#endif
@@ -78,8 +78,6 @@ CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
#define CV_NEON_AARCH64 0
#endif
// TODO
#define CV_NEON_DOT 0
//////////// Utils ////////////
@@ -667,11 +665,22 @@ inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b, const v_int64
}
// 8 >> 32
#ifdef CV_NEON_DOT
#define OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_OP(_Tpvec1, _Tpvec2, suffix) \
inline _Tpvec1 v_dotprod_expand(const _Tpvec2& a, const _Tpvec2& b) \
{ \
return _Tpvec1(vdotq_##suffix(vdupq_n_##suffix(0), a.val, b.val));\
} \
inline _Tpvec1 v_dotprod_expand(const _Tpvec2& a, const _Tpvec2& b, const _Tpvec1& c) \
{ \
return _Tpvec1(vdotq_##suffix(c.val, a.val, b.val)); \
}
OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_OP(v_uint32x4, v_uint8x16, u32)
OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_OP(v_int32x4, v_int8x16, s32)
#else
inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b)
{
#if CV_NEON_DOT
return v_uint32x4(vdotq_u32(vdupq_n_u32(0), a.val, b.val));
#else
const uint8x16_t zero = vreinterpretq_u8_u32(vdupq_n_u32(0));
const uint8x16_t mask = vreinterpretq_u8_u32(vdupq_n_u32(0x00FF00FF));
const uint16x8_t zero32 = vreinterpretq_u16_u32(vdupq_n_u32(0));
@@ -687,23 +696,15 @@ inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b)
uint32x4_t s1 = vaddq_u32(vshrq_n_u32(vreinterpretq_u32_u16(even), 16),
vshrq_n_u32(vreinterpretq_u32_u16(odd), 16));
return v_uint32x4(vaddq_u32(s0, s1));
#endif
}
inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b,
const v_uint32x4& c)
{
#if CV_NEON_DOT
return v_uint32x4(vdotq_u32(c.val, a.val, b.val));
#else
return v_dotprod_expand(a, b) + c;
#endif
}
inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b)
{
#if CV_NEON_DOT
return v_int32x4(vdotq_s32(vdupq_n_s32(0), a.val, b.val));
#else
int16x8_t p0 = vmull_s8(vget_low_s8(a.val), vget_low_s8(b.val));
int16x8_t p1 = vmull_s8(vget_high_s8(a.val), vget_high_s8(b.val));
int16x8_t uzp1, uzp2;
@@ -712,18 +713,13 @@ inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b)
int16x4_t uzpl1, uzpl2;
_v128_unzip(vget_low_s16(sum), vget_high_s16(sum), uzpl1, uzpl2);
return v_int32x4(vaddl_s16(uzpl1, uzpl2));
#endif
}
inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b,
const v_int32x4& c)
{
#if CV_NEON_DOT
return v_int32x4(vdotq_s32(c.val, a.val, b.val));
#else
return v_dotprod_expand(a, b) + c;
#endif
}
#endif
// 16 >> 64
inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b)
{
@@ -832,45 +828,44 @@ inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b, const v_
}
// 8 >> 32
#ifdef CV_NEON_DOT
#define OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_FAST_OP(_Tpvec1, _Tpvec2, suffix) \
inline _Tpvec1 v_dotprod_expand_fast(const _Tpvec2& a, const _Tpvec2& b) \
{ \
return v_dotprod_expand(a, b); \
} \
inline _Tpvec1 v_dotprod_expand_fast(const _Tpvec2& a, const _Tpvec2& b, const _Tpvec1& c) \
{ \
return v_dotprod_expand(a, b, c); \
}
OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_FAST_OP(v_uint32x4, v_uint8x16, u32)
OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_FAST_OP(v_int32x4, v_int8x16, s32)
#else
inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b)
{
#if CV_NEON_DOT
return v_uint32x4(vdotq_u32(vdupq_n_u32(0), a.val, b.val));
#else
uint16x8_t p0 = vmull_u8(vget_low_u8(a.val), vget_low_u8(b.val));
uint16x8_t p1 = vmull_u8(vget_high_u8(a.val), vget_high_u8(b.val));
uint32x4_t s0 = vaddl_u16(vget_low_u16(p0), vget_low_u16(p1));
uint32x4_t s1 = vaddl_u16(vget_high_u16(p0), vget_high_u16(p1));
return v_uint32x4(vaddq_u32(s0, s1));
#endif
}
inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
{
#if CV_NEON_DOT
return v_uint32x4(vdotq_u32(c.val, a.val, b.val));
#else
return v_dotprod_expand_fast(a, b) + c;
#endif
}
inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b)
{
#if CV_NEON_DOT
return v_int32x4(vdotq_s32(vdupq_n_s32(0), a.val, b.val));
#else
int16x8_t prod = vmull_s8(vget_low_s8(a.val), vget_low_s8(b.val));
prod = vmlal_s8(prod, vget_high_s8(a.val), vget_high_s8(b.val));
return v_int32x4(vaddl_s16(vget_low_s16(prod), vget_high_s16(prod)));
#endif
}
inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
{
#if CV_NEON_DOT
return v_int32x4(vdotq_s32(c.val, a.val, b.val));
#else
return v_dotprod_expand_fast(a, b) + c;
#endif
}
#endif
// 16 >> 64
inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b)
@@ -681,11 +681,19 @@ Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp
for(int i = 16; i < channels; i++) val[i] = _Tp(0);
}
// WARNING: unreachable code using Ninja
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(push)
#pragma warning(disable: 4702)
#endif
template<typename _Tp, int m, int n> inline
Matx<_Tp, m, n>::Matx(const _Tp* values)
{
for( int i = 0; i < channels; i++ ) val[i] = values[i];
}
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(pop)
#endif
#ifdef CV_CXX11
template<typename _Tp, int m, int n> inline
@@ -703,10 +703,18 @@ cv::ogl::Texture2D::Format cv::ogl::Texture2D::format() const
///////
// WARNING: unreachable code using Ninja
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(push)
#pragma warning(disable: 4702)
#endif
inline
cv::ogl::Arrays::Arrays() : size_(0)
{
}
#if defined _MSC_VER && _MSC_VER >= 1920
#pragma warning(pop)
#endif
inline
int cv::ogl::Arrays::size() const
@@ -36,7 +36,7 @@ namespace cv { namespace utils { namespace fs {
* Provides interprocess synchronization mechanism.
* Platform dependent.
*
* Supports multiple readers / single writer access pattern (RW / readerswriter / shared-exclusive lock).
* Supports multiple readers / single writer access pattern (RW / readers-writer / shared-exclusive lock).
*
* File must exist.
* File can't be re-used (for example, I/O operations via std::fstream is not safe)
@@ -7,8 +7,8 @@
#define CV_VERSION_MAJOR 3
#define CV_VERSION_MINOR 4
#define CV_VERSION_REVISION 18
#define CV_VERSION_STATUS "-pre"
#define CV_VERSION_REVISION 19
#define CV_VERSION_STATUS ""
#define CVAUX_STR_EXP(__A) #__A
#define CVAUX_STR(__A) CVAUX_STR_EXP(__A)
+13 -5
View File
@@ -55,19 +55,27 @@ Algorithm::~Algorithm()
CV_TRACE_FUNCTION();
}
void Algorithm::write(const Ptr<FileStorage>& fs, const String& name) const
void Algorithm::write(FileStorage& fs, const String& name) const
{
CV_TRACE_FUNCTION();
if(name.empty())
{
write(*fs);
write(fs);
return;
}
*fs << name << "{";
write(*fs);
*fs << "}";
fs << name << "{";
write(fs);
fs << "}";
}
#if CV_VERSION_MAJOR < 5
void Algorithm::write(const Ptr<FileStorage>& fs, const String& name) const
{
CV_Assert(fs);
write(*fs, name);
}
#endif
void Algorithm::save(const String& filename) const
{
CV_TRACE_FUNCTION();
+1 -2
View File
@@ -29,8 +29,7 @@ public:
}
void cleanup() const
{
CV_Assert(ptr && *ptr);
*ptr = 0;
CV_DbgAssert(ptr);
if (raw_mem)
fastFree(raw_mem);
}
+20
View File
@@ -97,6 +97,10 @@ void check_failed_MatChannels(const int v1, const int v2, const CheckContext& ct
{
check_failed_auto_<int>(v1, v2, ctx);
}
void check_failed_auto(const bool v1, const bool v2, const CheckContext& ctx)
{
check_failed_auto_<bool>(v1, v2, ctx);
}
void check_failed_auto(const int v1, const int v2, const CheckContext& ctx)
{
check_failed_auto_<int>(v1, v2, ctx);
@@ -151,6 +155,22 @@ void check_failed_MatChannels(const int v, const CheckContext& ctx)
{
check_failed_auto_<int>(v, ctx);
}
void check_failed_true(const bool v, const CheckContext& ctx)
{
CV_UNUSED(v);
std::stringstream ss;
ss << ctx.message << ":" << std::endl
<< " '" << ctx.p1_str << "' must be 'true'";
cv::errorNoReturn(cv::Error::StsError, ss.str(), ctx.func, ctx.file, ctx.line);
}
void check_failed_false(const bool v, const CheckContext& ctx)
{
CV_UNUSED(v);
std::stringstream ss;
ss << ctx.message << ":" << std::endl
<< " '" << ctx.p1_str << "' must be 'false'";
cv::errorNoReturn(cv::Error::StsError, ss.str(), ctx.func, ctx.file, ctx.line);
}
void check_failed_auto(const int v, const CheckContext& ctx)
{
check_failed_auto_<int>(v, ctx);
+6 -2
View File
@@ -67,7 +67,7 @@
#if defined(__clang__) && defined(__has_feature)
#if __has_feature(memory_sanitizer)
#define CV_ANNOTATE_MEMORY_IS_INITIALIZED(address, size) \
__msan_unpoison(adresse, size)
__msan_unpoison(address, size)
#endif
#endif
#ifndef CV_ANNOTATE_MEMORY_IS_INITIALIZED
@@ -244,6 +244,11 @@ lapack_SVD(fptype* a, size_t a_step, fptype *w, fptype* u, size_t u_step, fptype
lwork = (int)round(work1); //optimal buffer size
fptype* buffer = new fptype[lwork + 1];
// Make sure MSAN sees the memory as having been written.
// MSAN does not think it has been written because a different language is called.
// Note: we do this here because if dgesdd is C++, MSAN errors can be reported within it.
CV_ANNOTATE_MEMORY_IS_INITIALIZED(buffer, sizeof(fptype) * (lwork + 1));
if(typeid(fptype) == typeid(float))
OCV_LAPACK_FUNC(sgesdd)(mode, &m, &n, (float*)a, &lda, (float*)w, (float*)u, &ldu, (float*)vt, &ldv, (float*)buffer, &lwork, iworkBuf, info);
else if(typeid(fptype) == typeid(double))
@@ -252,7 +257,6 @@ lapack_SVD(fptype* a, size_t a_step, fptype *w, fptype* u, size_t u_step, fptype
// Make sure MSAN sees the memory as having been written.
// MSAN does not think it has been written because a different language was called.
CV_ANNOTATE_MEMORY_IS_INITIALIZED(a, a_step * n);
CV_ANNOTATE_MEMORY_IS_INITIALIZED(buffer, sizeof(fptype) * (lwork + 1));
if (u)
CV_ANNOTATE_MEMORY_IS_INITIALIZED(u, u_step * m);
if (vt)
+6
View File
@@ -973,6 +973,12 @@ bool ocl_minMaxIdx( InputArray _src, double* minVal, double* maxVal, int* minLoc
return false;
#endif
if (dev.deviceVersionMajor() == 1 && dev.deviceVersionMinor() < 2)
{
// 'static' storage class specifier used by "minmaxloc" is available from OpenCL 1.2+ only
return false;
}
bool doubleSupport = dev.doubleFPConfig() > 0, haveMask = !_mask.empty(),
haveSrc2 = _src2.kind() != _InputArray::NONE;
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type),
+3 -1
View File
@@ -52,11 +52,13 @@ DECLARE_CV_PAUSE
#endif
#ifndef CV_PAUSE
# if defined __GNUC__ && (defined __i386__ || defined __x86_64__)
# include <x86intrin.h> /* for __rdtsc */
# if !defined(__SSE2__)
static inline void cv_non_sse_mm_pause() { __asm__ __volatile__ ("rep; nop"); }
# define _mm_pause cv_non_sse_mm_pause
# endif
# define CV_PAUSE(v) do { for (int __delay = (v); __delay > 0; --__delay) { _mm_pause(); } } while (0)
// With Skylake CPUs and above, _mm_pause takes 140 cycles so no need for a loop.
# define CV_PAUSE(v) do { (void)v; _mm_pause(); } while (0)
# elif defined __GNUC__ && defined __aarch64__
# define CV_PAUSE(v) do { for (int __delay = (v); __delay > 0; --__delay) { asm volatile("yield" ::: "memory"); } } while (0)
# elif defined __GNUC__ && defined __arm__
+39 -3
View File
@@ -301,6 +301,9 @@ DECLARE_CV_CPUID_X86
#endif
#endif
#if defined CV_CXX11
#include <chrono>
#endif
namespace cv
{
@@ -411,6 +414,7 @@ struct HWFeatures
g_hwFeatureNames[CPU_AVX_5124FMAPS] = "AVX5124FMAPS";
g_hwFeatureNames[CPU_NEON] = "NEON";
g_hwFeatureNames[CPU_NEON_DOTPROD] = "NEON_DOTPROD";
g_hwFeatureNames[CPU_VSX] = "VSX";
g_hwFeatureNames[CPU_VSX3] = "VSX3";
@@ -555,6 +559,24 @@ struct HWFeatures
#ifdef __aarch64__
have[CV_CPU_NEON] = true;
have[CV_CPU_FP16] = true;
int cpufile = open("/proc/self/auxv", O_RDONLY);
if (cpufile >= 0)
{
Elf64_auxv_t auxv;
const size_t size_auxv_t = sizeof(auxv);
while ((size_t)read(cpufile, &auxv, size_auxv_t) == size_auxv_t)
{
if (auxv.a_type == AT_HWCAP)
{
have[CV_CPU_NEON_DOTPROD] = (auxv.a_un.a_val & (1 << 20)) != 0;
break;
}
}
close(cpufile);
}
#elif defined __arm__ && defined __ANDROID__
#if defined HAVE_CPUFEATURES
CV_LOG_INFO(NULL, "calling android_getCpuFeatures() ...");
@@ -598,13 +620,20 @@ struct HWFeatures
close(cpufile);
}
#endif
#elif (defined __clang__ || defined __APPLE__)
#elif (defined __APPLE__)
#if (defined __ARM_NEON__ || (defined __ARM_NEON && defined __aarch64__))
have[CV_CPU_NEON] = true;
#endif
#if (defined __ARM_FP && (((__ARM_FP & 0x2) != 0) && defined __ARM_NEON__))
have[CV_CPU_FP16] = true;
#endif
#elif (defined __clang__)
#if (defined __ARM_NEON__ || (defined __ARM_NEON && defined __aarch64__))
have[CV_CPU_NEON] = true;
#if (defined __ARM_FP && ((__ARM_FP & 0x2) != 0))
have[CV_CPU_FP16] = true;
#endif
#endif
#endif
#if defined _ARM_ && (defined(_WIN32_WCE) && _WIN32_WCE >= 0x800)
have[CV_CPU_NEON] = true;
@@ -833,7 +862,10 @@ bool useOptimized(void)
int64 getTickCount(void)
{
#if defined _WIN32 || defined WINCE
#if defined CV_CXX11
std::chrono::steady_clock::time_point now = std::chrono::steady_clock::now();
return (int64)now.time_since_epoch().count();
#elif defined _WIN32 || defined WINCE
LARGE_INTEGER counter;
QueryPerformanceCounter( &counter );
return (int64)counter.QuadPart;
@@ -852,7 +884,11 @@ int64 getTickCount(void)
double getTickFrequency(void)
{
#if defined _WIN32 || defined WINCE
#if defined CV_CXX11
using clock_period_t = std::chrono::steady_clock::duration::period;
double clock_freq = clock_period_t::den / clock_period_t::num;
return clock_freq;
#elif defined _WIN32 || defined WINCE
LARGE_INTEGER freq;
QueryPerformanceFrequency(&freq);
return (double)freq.QuadPart;
-7
View File
@@ -403,9 +403,6 @@ TEST_P(BufferArea, basic)
EXPECT_EQ((double)0, dbl_ptr[i]);
}
}
EXPECT_TRUE(int_ptr == NULL);
EXPECT_TRUE(uchar_ptr == NULL);
EXPECT_TRUE(dbl_ptr == NULL);
}
TEST_P(BufferArea, align)
@@ -442,10 +439,6 @@ TEST_P(BufferArea, align)
}
}
}
for (size_t i = 0; i < CNT; ++i)
{
EXPECT_TRUE(buffers[i] == NULL);
}
}
TEST_P(BufferArea, default_align)
+2 -2
View File
@@ -47,9 +47,9 @@
#include "opencv2/core/async.hpp"
#if !defined CV_DOXYGEN && !defined CV_STATIC_ANALYSIS && !defined CV_DNN_DONT_ADD_EXPERIMENTAL_NS
#define CV__DNN_EXPERIMENTAL_NS_BEGIN namespace experimental_dnn_34_v25 {
#define CV__DNN_EXPERIMENTAL_NS_BEGIN namespace experimental_dnn_34_v26 {
#define CV__DNN_EXPERIMENTAL_NS_END }
namespace cv { namespace dnn { namespace experimental_dnn_34_v25 { } using namespace experimental_dnn_34_v25; }}
namespace cv { namespace dnn { namespace experimental_dnn_34_v26 { } using namespace experimental_dnn_34_v26; }}
#else
#define CV__DNN_EXPERIMENTAL_NS_BEGIN
#define CV__DNN_EXPERIMENTAL_NS_END
@@ -160,22 +160,49 @@ static inline MatShape shape(int a0, int a1=-1, int a2=-1, int a3=-1)
static inline int total(const MatShape& shape, int start = -1, int end = -1)
{
if (start == -1) start = 0;
if (end == -1) end = (int)shape.size();
if (shape.empty())
return 0;
int dims = (int)shape.size();
if (start == -1) start = 0;
if (end == -1) end = dims;
CV_CheckLE(0, start, "");
CV_CheckLE(start, end, "");
CV_CheckLE(end, dims, "");
int elems = 1;
CV_Assert(start <= (int)shape.size() && end <= (int)shape.size() &&
start <= end);
for(int i = start; i < end; i++)
for (int i = start; i < end; i++)
{
elems *= shape[i];
}
return elems;
}
// TODO: rename to countDimsElements()
static inline int total(const Mat& mat, int start = -1, int end = -1)
{
if (mat.empty())
return 0;
int dims = mat.dims;
if (start == -1) start = 0;
if (end == -1) end = dims;
CV_CheckLE(0, start, "");
CV_CheckLE(start, end, "");
CV_CheckLE(end, dims, "");
int elems = 1;
for (int i = start; i < end; i++)
{
elems *= mat.size[i];
}
return elems;
}
static inline MatShape concat(const MatShape& a, const MatShape& b)
{
MatShape c = a;
+2 -3
View File
@@ -204,14 +204,13 @@ public:
std::vector<InferenceEngine::DataConfig> outDataConfig;
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_2)
InferenceEngine::SizeVector order;
size_t offset = std::numeric_limits<size_t>::max();
for (int i = 0; i < node->get_input_size(); ++i)
{
InferenceEngine::DataConfig conf;
auto shape = node->input_value(i).get_shape();
order.resize(shape.size());
std::iota(order.begin(), order.end(), 0);
conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order, offset});
conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order});
inDataConfig.push_back(conf);
}
@@ -221,7 +220,7 @@ public:
auto shape = node->output(i).get_shape();
order.resize(shape.size());
std::iota(order.begin(), order.end(), 0);
conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order, offset});
conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order});
outDataConfig.push_back(conf);
}
#else
@@ -208,8 +208,8 @@ public:
const float* inpData = inp0.ptr<float>();
float* outData = outputs[0].ptr<float>();
size_t num = total(shape(inp0.size), 0, startAxis);
size_t numPlanes = total(shape(inp0.size), startAxis, endAxis + 1);
size_t num = total(inp0, 0, startAxis);
size_t numPlanes = total(inp0, startAxis, endAxis + 1);
CV_Assert(num * numPlanes != 0);
size_t planeSize = inp0.total() / (num * numPlanes);
for (size_t n = 0; n < num; ++n)
+10
View File
@@ -91,6 +91,16 @@ public:
if (hasWeights && hasBias)
CV_CheckEQ(weights.total(), bias.total(), "Incompatible weights/bias blobs");
if (weights.total() == 1)
{
// The total() of bias should be same as weights.
if (hasBias)
inpBlob.convertTo(outBlob, CV_32F, weights.at<float>(0), bias.at<float>(0));
else
inpBlob.convertTo(outBlob, CV_32F, weights.at<float>(0));
return;
}
int endAxis;
for (endAxis = axis + 1; endAxis <= inpBlob.dims; ++endAxis)
{
+26 -19
View File
@@ -1759,15 +1759,15 @@ void ONNXImporter::parseBatchNormalization(LayerParams& layerParams, const openc
addLayer(layerParams, node_proto);
}
// A * B + C = Y, we require that the dimension of A is [m, k], and the dimension of B is [n, k].
// And the dim of output Y is [m, n]
void ONNXImporter::parseGemm(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto)
{
CV_Assert(node_proto.input_size() >= 2);
layerParams.type = "InnerProduct";
Mat weights = getBlob(node_proto, 1);
int ind_num_out = 0;
if (layerParams.has("transB") && !layerParams.get<int>("transB")) {
if (!layerParams.get<int>("transB", 0)) {
transpose(weights, weights);
ind_num_out = 1;
}
layerParams.blobs.push_back(weights);
@@ -1789,7 +1789,7 @@ void ONNXImporter::parseGemm(LayerParams& layerParams, const opencv_onnx::NodePr
addLayer(constParams, proto);
}
layerParams.set("num_output", layerParams.blobs[0].size[ind_num_out]);
layerParams.set("num_output", layerParams.blobs[0].size[0]);
layerParams.set("bias_term", node_proto.input_size() == 3);
addLayer(layerParams, node_proto);
}
@@ -1818,6 +1818,8 @@ void ONNXImporter::parseMatMul(LayerParams& layerParams, const opencv_onnx::Node
void findBroadAxis(const MatShape& broadShape, const MatShape& outShape, size_t& axis, int& broadAxis)
{
// Currently, this function can only complete 1-dimensional expansion of broadShape.
// If there are two dimensions in broadShape that need to be expended, it will fail.
const size_t diff = outShape.size() - broadShape.size();
// find the first non-one element of the broadcasting shape
@@ -1982,25 +1984,30 @@ void ONNXImporter::parseMul(LayerParams& layerParams, const opencv_onnx::NodePro
const MatShape& outShape = outShapes[node_proto.input(0)];
size_t axis = 0;
int broadAxis = -1;
findBroadAxis(broadShape, outShape, axis, broadAxis);
// if there is a one dimension in the middle that should be broadcasted, broadcast it
if (broadAxis != -1)
if (total(broadShape) != 1)
{
opencv_onnx::NodeProto concat_node_proto = node_proto;
const std::string& input1 = concat_node_proto.input(1);
// If broadShape is a scalar, we set axis as 0.
// Other-wise, we check broadcast is available.
int broadAxis = -1;
findBroadAxis(broadShape, outShape, axis, broadAxis);
expandMid(layerParams.name, concat_node_proto, input1, outShape[broadAxis]);
// if there is a one dimension in the middle that should be broadcasted, broadcast it
if (broadAxis != -1)
{
opencv_onnx::NodeProto concat_node_proto = node_proto;
const std::string& input1 = concat_node_proto.input(1);
LayerParams concatLP;
concatLP.name = layerParams.name + "/concat";
concatLP.set("axis", broadAxis);
concatLP.type = "Concat";
concat_node_proto.set_output(0, concatLP.name);
expandMid(layerParams.name, concat_node_proto, input1, outShape[broadAxis]);
addLayer(concatLP, concat_node_proto);
node_proto.set_input(1, concatLP.name);
LayerParams concatLP;
concatLP.name = layerParams.name + "/concat";
concatLP.set("axis", broadAxis);
concatLP.type = "Concat";
concat_node_proto.set_output(0, concatLP.name);
addLayer(concatLP, concat_node_proto);
node_proto.set_input(1, concatLP.name);
}
}
CV_Assert(axis != outShape.size());
@@ -829,12 +829,19 @@ void RemoveIdentityOps(tensorflow::GraphDef& net)
IdentityOpsMap::iterator it = identity_ops.find(input_op_name);
if (it != identity_ops.end()) {
std::set<String> loopCheckSet;
// In case of Identity after Identity
while (true)
{
IdentityOpsMap::iterator nextIt = identity_ops.find(it->second);
if (nextIt != identity_ops.end())
{
// Loop check
if (loopCheckSet.find(it->second) != loopCheckSet.end())
CV_Error(Error::StsError, "Found a loop in your input Tensorflow model, which is illegal!");
loopCheckSet.insert(it->second);
it = nextIt;
}
else
break;
}
-6
View File
@@ -207,12 +207,6 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe_Different_Width_Height)
if (backend == DNN_BACKEND_HALIDE)
applyTestTag(CV_TEST_TAG_DNN_SKIP_HALIDE);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// May hang on some configurations
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
-10
View File
@@ -699,10 +699,6 @@ TEST_P(Test_Caffe_nets, FasterRCNN_vgg16)
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// Check 'backward_compatible_check || in_out_elements_equal' failed at core/src/op/reshape.cpp:427:
// While validating node 'v1::Reshape bbox_pred_reshape (bbox_pred[0]:f32{1,84}, Constant_265242[0]:i64{4}) -> (f32{?,?,?,?})' with friendly_name 'bbox_pred_reshape':
// Requested output shape {1,6300,4,1} is incompatible with input shape {1, 84}
@@ -734,12 +730,6 @@ TEST_P(Test_Caffe_nets, FasterRCNN_zf)
);
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 ||
backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
@@ -916,20 +916,10 @@ TEST_P(Test_Darknet_layers, shortcut_leaky)
}
TEST_P(Test_Darknet_layers, shortcut_unequal)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
testDarknetLayer("shortcut_unequal");
}
TEST_P(Test_Darknet_layers, shortcut_unequal_2)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
testDarknetLayer("shortcut_unequal_2");
}
-6
View File
@@ -637,12 +637,6 @@ TEST_P(NoParamActivation, Accuracy)
Target targetId = get<1>(get<1>(GetParam()));
std::string layer_type = get<0>(GetParam());
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && targetId == DNN_TARGET_CPU && layer_type == "BNLL")
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
LayerParams lp;
lp.type = layer_type;
lp.name = "testLayer";
+1 -16
View File
@@ -1431,12 +1431,6 @@ static void test_dldt_fused_output(Backend backend, Target target)
TEST_P(Test_DLDT_layers, fused_output)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
CV_DNN_REGISTER_LAYER_CLASS(Unsupported, UnsupportedLayer);
try
{
@@ -1596,16 +1590,7 @@ TEST_P(Test_Caffe_layers, Interp)
TEST_P(Test_Caffe_layers, DISABLED_Interp) // requires patched protobuf (available in OpenCV source tree only)
#endif
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
);
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); // exception
#endif
+12 -70
View File
@@ -103,12 +103,6 @@ TEST_P(Test_ONNX_layers, MaxPooling)
}
TEST_P(Test_ONNX_layers, MaxPooling_2)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
testONNXModels("two_maxpooling", npy, 0, 0, false, false);
}
@@ -725,6 +719,8 @@ TEST_P(Test_ONNX_layers, Div)
normAssert(ref, out, "", default_l1, default_lInf);
expectNoFallbacksFromIE(net);
testONNXModels("div_test_1x1",npy, 0, 0, false, true, 2);
}
TEST_P(Test_ONNX_layers, DynamicReshape)
@@ -791,17 +787,6 @@ TEST_P(Test_ONNX_layers, Slice_Steps_2DInput)
TEST_P(Test_ONNX_layers, Slice_Steps_3DInput)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
);
#endif
testONNXModels("slice_opset_11_steps_3d");
}
@@ -812,20 +797,6 @@ TEST_P(Test_ONNX_layers, Slice_Steps_4DInput)
TEST_P(Test_ONNX_layers, Slice_Steps_5DInput)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// IE exception: Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
);
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
testONNXModels("slice_opset_11_steps_5d");
}
@@ -848,9 +819,6 @@ TEST_P(Test_ONNX_layers, Split_EltwiseMax)
TEST_P(Test_ONNX_layers, LSTM_Activations)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// IE exception: Node Block1326/lstm/reshape_0/permute was not assigned on any pointed device
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
@@ -887,9 +855,6 @@ TEST_P(Test_ONNX_layers, LSTM_hidden)
TEST_P(Test_ONNX_layers, LSTM_hidden_bidirectional)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// IE exception: Node Transpose_45 was not assigned on any pointed device.
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
@@ -917,11 +882,7 @@ TEST_P(Test_ONNX_layers, LSTM_cell_forward)
}
TEST_P(Test_ONNX_layers, LSTM_cell_bidirectional)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000)
// Ngraph operation Reshape with name LSTM_16/lstm_y/reshape has dynamic output shape on 0 port, but CPU plug-in supports only static shape
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -1283,16 +1244,7 @@ TEST_P(Test_ONNX_layers, MaxPoolSigmoid1d)
TEST_P(Test_ONNX_layers, MaxPool1d_Twise)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
);
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
{
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
@@ -1307,11 +1259,7 @@ TEST_P(Test_ONNX_layers, MaxPool1d_Twise)
TEST_P(Test_ONNX_layers, AvePool1d)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
{
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
@@ -1326,19 +1274,7 @@ TEST_P(Test_ONNX_layers, AvePool1d)
TEST_P(Test_ONNX_layers, PoolConv1d)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
);
#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2021040000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
{
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
@@ -1389,6 +1325,12 @@ TEST_P(Test_ONNX_layers, DivConst)
testONNXModels("div_const");
}
TEST_P(Test_ONNX_layers, Gemm)
{
testONNXModels("gemm_no_transB");
testONNXModels("gemm_transB_0");
}
TEST_P(Test_ONNX_layers, OutputRegistration)
{
testONNXModels("output_registration", npy, 0, 0, false, true, 2);
+1 -50
View File
@@ -207,9 +207,6 @@ TEST_P(Test_TensorFlow_layers, conv_keras_atrous_conv2d_same)
TEST_P(Test_TensorFlow_layers, conv_pool_nchw)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// [ GENERAL_ERROR ] AssertionFailed: !expired()
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -476,9 +473,6 @@ TEST_P(Test_TensorFlow_layers, slim_batch_norm)
TEST_P(Test_TensorFlow_layers, pooling_max_pool_even)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// [ GENERAL_ERROR ] AssertionFailed: !expired()
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -491,9 +485,6 @@ TEST_P(Test_TensorFlow_layers, pooling_max_pool_even)
TEST_P(Test_TensorFlow_layers, pooling_max_pool_odd_valid)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// [ GENERAL_ERROR ] AssertionFailed: !expired()
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -506,9 +497,6 @@ TEST_P(Test_TensorFlow_layers, pooling_max_pool_odd_valid)
TEST_P(Test_TensorFlow_layers, pooling_max_pool_odd_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// [ GENERAL_ERROR ] AssertionFailed: !expired()
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -789,14 +777,6 @@ TEST_P(Test_TensorFlow_layers, BiasAdd)
TEST_P(Test_TensorFlow_layers, l2_normalize_3d)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
);
// accuracy
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -999,9 +979,6 @@ TEST_P(Test_TensorFlow_nets, Faster_RCNN_resnet50_coco_2018_01_28)
);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// [ GENERAL_ERROR ] AssertionFailed: subgraphTopoSortsStep < subgraphs.size()
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -1210,9 +1187,6 @@ TEST_P(Test_TensorFlow_layers, fp16_weights_fp16_single_conv)
TEST_P(Test_TensorFlow_layers, fp16_weights_fp16_max_pool_odd_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// [ GENERAL_ERROR ] AssertionFailed: !expired()
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -1241,9 +1215,6 @@ TEST_P(Test_TensorFlow_layers, fp16_weights_fp16_padding_valid)
TEST_P(Test_TensorFlow_layers, fp16_weights_fp16_max_pool_even)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// [ GENERAL_ERROR ] AssertionFailed: !expired()
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -1268,9 +1239,6 @@ TEST_P(Test_TensorFlow_layers, fp16_weights_fp16_deconvolution)
TEST_P(Test_TensorFlow_layers, fp16_weights_fp16_max_pool_odd_valid)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// [ GENERAL_ERROR ] AssertionFailed: !expired()
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
@@ -1355,16 +1323,6 @@ TEST_P(Test_TensorFlow_layers, split_equals)
TEST_P(Test_TensorFlow_layers, resize_nearest_neighbor)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
);
#endif
runTensorFlowNet("resize_nearest_neighbor");
}
TEST_P(Test_TensorFlow_layers, resize_nearest_neighbor_keras_upsampling2d)
@@ -1434,14 +1392,7 @@ TEST_P(Test_TensorFlow_layers, relu6)
TEST_P(Test_TensorFlow_layers, subpixel)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
// Cannot get memory!
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#elif defined(INF_ENGINE_RELEASE)
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)

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