Removal of deprecated functions in imgproc #26914
Fixes : #26410
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Extension to PR #26605 ldm inpainting sample #26904
This PR adds and fixes following points in the ldm_inpainting sample on top of original PR #26605 by @Abdurrahheem
DONE:
1. Added functionality to load models from a YAML configuration file, allowing for automatic downloading if models are not found locally.
2. Updated the script usage instructions to reflect the correct command format.
3. Improved user interaction by adding instructions to the image window for inpainting controls.
4. Introduced a new models.yml configuration section for inpainting models weights downloading, including placeholders for model SHA1 checksums.
5. Fixed input types and names of the onnx graph generation.
6. Added links to onnx graphs in models.yml
7. Support added for findModels and standarized the sample usage similar to other dnn samples
8. Fixes issue in download_models.py for downloading models from dl.opencv.org
9. Fixes issue in common.py which used to print duplicated positional arguments in case of samples that use multiple models.
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---------
Co-authored-by: Abdurrahheem <abduragim.shtanchaev@xperience.ai>
Added lama inpainting onnx model sample #26736
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Replaced sprintf with snprintf #26815
Fixes : #26814
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Feature: weighted Hough Transform #21407
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AndroidMediaNdkVideoWriter pixel format enhancement #26698
* videoio(Android): Add source pixel formats RGBA and GRAY to AndroidMediaNdkVideoWriter
Let AndroidMediaNdkVideoWriter::write() deduce source pixel format from matrix type:
CV_8UC3 -> BGR (as before)
CV_8UC4 -> RGBA (use in conjunction with CvCameraViewFrame)
CV_8UC1 -> GRAY
* samples/android/video-recorder: Send images to VideoWriter in RGBA format
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AndroidMediaNdkCapture pixel format enhancement #26656
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Animated WebP Support #25608
related issues #24855#22569
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Update printingin GPT2 sample #26584
This PR update how GPT2 prints its output
**Note**: As the length of the prompt increases while inference, the token generation time slows down. May be its right time to introduce QK cashing to speed up the inference
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Previously, the yoloPostProcessing function assumed that the number of classes (nc) was fixed at 80. This caused incorrect behavior when a different number of classes was specified, leading to mismatched output shapes.
This update modifies the code to use the provided `nc` value dynamically, ensuring that the output shapes are correctly calculated based on the specified number of classes. This prevents issues when `nc` is not equal to 80 and allows for greater flexibility in model configurations.
This branch and commit address an issue in the YOLO example (samples/dnn/yolo_detector.cpp) where the mean and scale parameters only affected the first channel (B) due to single-value input. The modification updates these parameters to accept multi-channel values, ensuring consistent preprocessing across all image channels.
Updated trackbar callback function and improved documentation #26524
This Fixes#26467
Description:
This pull request improve the OpenCV documentation regarding the Trackbar functionality. The current documentation does not provide clear guidance on certain aspects, such as handling the value pointer deprecation and utilizing callback arguments in C. This update addresses those gaps and provides an updated example for better clarity.
Changes:
Updated Documentation:
Clarified the usage of the value pointer and explained how to pass an initial value, since the value pointer is deprecated.
Added more detailed explanations about callback arguments in C, ensuring that users understand how to access and use them in Trackbar callbacks.
Added a note on how to properly handle initial value passing without relying on the deprecated value pointer.
Updated Tutorial Example:
Renamed and used callback function parameters to make them more understandable.
Included a demonstration on how to utilize userdata in the callback function.
Additional Notes:
Removed reliance on the value pointer for updating trackbar values. Users are now encouraged to use other mechanisms as per the current implementation to avoid the runtime warning.
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Improved Tracker Samples #26202
Relates to #25006
This sample has been rewritten to track a selected target in a video or camera stream. It combines VIT tracker, Nano tracker and Dasiamrpn tracker into one tracker sample
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Fix gpt2 sample #26573
This PR adds dynamic input support for `gpt2_inference.py` sample.
Fixes#26518Fixes#26517
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Code Fixes and changed post processing based on models.yml in Object Detection Sample #26486
## Major Changes
1. Changes to add findModel support for config file in models like yolov4, yolov4-tiny, yolov3, ssd_caffe, tiny-yolo-voc, ssd_tf and faster_rcnn_tf.
2. Added new model and config download links for ssd_caffe, as previous links were not working.
3. Switched to DNN ENGINE_CLASSIC for non-cpu convig as new engine does not support it.
4. Fixes in python sample related to yolov5 usage.
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Removed g-api from the main repo #26469
Following #25000.
CI patch: https://github.com/opencv/ci-gha-workflow/pull/196
This is migration of G-API from opencv to opencv_contrib, part 1.
Here we simply remove G-API from the main repo. The next patch should bring G-API to opencv_contrib.
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Modify DNN Samples to use ENGINE_CLASSIC for Non-Default Back-end or Target #26334
PR resolves#26325 regarding fall-back to ENGINE_CLASSIC if non-default back-end or target is passed by user.
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Updated segmentation sample as per current update usage and engine #26347
This PR updates segmentation sample as per new usage, and change their DNN engines. It adds usage of findModel, dynamic fontsize, etc. in segmentation sample.
The PR makes the sample consistent with other dnn samples
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[BUG FIX] Object detection sample preprocessing #26326
PR resloves #26315 related to incorrect preprocessing for 'Image2BlobParams' in object detection sample.
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[BUG FIX] Fix issues in Person ReID C++ sample #26336
This PR fixes multiple issues in the Person ReID C++ sample that were causing incorrect outputs. It addresses improper matrix initialization, adds a missing return statement, and ensures that vectors are properly cleared before reuse. These changes correct the output of the sample.
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Improved person reid cpp and python sample #25667#25006
This sample has been rewritten to track a selected target in a video or camera stream. Person detection has been integrated using yolov8 and the user can provide a target image via command line or interactively select the target at start of the execution
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Features2d cleanup: Move several feature detectors and descriptors to opencv_contrib #25292
features2d cleanup: #24999
The PR moves KAZE, AKAZE, AgastFeatureDetector, BRISK and BOW to opencv_contrib/xfeatures2d.
Related PR: opencv/opencv_contrib#3709
Update Documentation #26260
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- Added function overload for the simple case
- Added CV_Bool type support for masks
- `parallel_for_` for intrinsics calibration for faster inference
- Homogenize parameters order with other calibrateXXX functions
Reworked multiview calibration interface #26221
- Use InputArray / OutputArray
- Use enum for camera type
- Sort parameters according guidelines
- Made more outputs optional
- Introduce flags and added tests for intrinsics and extrinsics guess.
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Add support for downloading DNN config files in download_models.py #26186
PR resloves #26160 related to downloading DNN config files using download_models.py
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shyama7004
Alexander Smorkalov
Skreg
Gursimar Singh
Kababey
MaximSmolskiy
Alexander Smorkalov
Masahiro Ogawa
Rüdiger Ihle
Suleyman TURKMEN
Abduragim Shtanchaev
KangJialiang
MurtazaSaherwala
FantasqueX
Vadim Pisarevsky
WU Jia
Maksim Shabunin
Alexander Smorkalov
Javier Macias Sola
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