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Commit Graph

66 Commits

Author SHA1 Message Date
Dmitry Kurtaev 7dc6b1d7d4 Layers for OpenFace face recognition network 2017-09-14 09:11:31 +03:00
Dmitry Kurtaev 58b890b9f7 Dilated convolution import from TensorFlow 2017-09-13 18:44:14 +03:00
dkurt 339793143c Unit tests for TensorFlow importer 2017-08-03 11:29:48 +03:00
Aleksandr Rybnikov 7d1140340e Rewrote googlenet tests 2017-07-18 18:49:14 +03:00
Vadim Pisarevsky 0488d9bdb2 optimize out scaleLayer & concatLayer whenever possible
fixed problem in concat layer by disabling memory re-use in layers with multiple inputs

trying to fix the tests when Halide is used to run deep nets

another attempt to fix Halide tests

see if the Halide tests will pass with concat layer fusion turned off

trying to fix failures in halide tests; another try

one more experiment to make halide_concat & halide_enet tests pass

continue attempts to fix halide tests

moving on

uncomment parallel concat layer

seemingly fixed failures in Halide tests and re-enabled concat layer fusion; thanks to dkurt for the patch
2017-07-14 18:30:53 +03:00
Alexander Alekhin 4784c7be5f dnn: cleanup dispatched code, fix SIMD128 types 2017-07-13 19:00:34 +03:00
Vadim Pisarevsky ed9564106c reuse AVX2-optimized kernels for AVX1 CPUs (like IvyBridge) 2017-07-06 21:36:59 +03:00
Maksim Shabunin e0393f8557 Fixed some issues found by static analysis (4th round) 2017-06-30 12:26:53 +03:00
Vadim Pisarevsky ac49a17a82 Merge pull request #9022 from dkurt:keep_conv_weights_for_halide 2017-06-29 11:09:17 +00:00
Maksim Shabunin ace0701a46 Merge pull request #9019 from alalek:dnn_trace 2017-06-29 07:33:46 +00:00
Maksim Shabunin a769d69a9d Fixed several issues found by static analysis 2017-06-28 18:06:18 +03:00
dkurt b46f5b1b38 Align convolutional layer weights separately from origin ones 2017-06-28 17:05:56 +03:00
Alexander Alekhin ed10383359 dnn: added trace macros 2017-06-28 14:57:26 +03:00
Vadim Pisarevsky 8b3d6603d5 another round of dnn optimization (#9011)
* another round of dnn optimization:
* increased malloc alignment across OpenCV from 16 to 64 bytes to make it AVX2 and even AVX-512 friendly
* improved SIMD optimization of pooling layer, optimized average pooling
* cleaned up convolution layer implementation
* made activation layer "attacheable" to all other layers, including fully connected and addition layer.
* fixed bug in the fusion algorithm: "LayerData::consumers" should not be cleared, because it desctibes the topology.
* greatly optimized permutation layer, which improved SSD performance
* parallelized element-wise binary/ternary/... ops (sum, prod, max)

* also, added missing copyrights to many of the layer implementation files

* temporarily disabled (again) the check for intermediate blobs consistency; fixed warnings from various builders
2017-06-28 11:15:22 +03:00
Alexander Alekhin f8a75c4361 dispatch: added CV_TRY_${OPT} macro, fix dnn build
- 1: OPT is available directly or via dispatcher
- 0: optimization is not compiled at all
2017-06-27 17:05:15 +03:00
Alexander Alekhin 93729784bb dnn: move module from opencv_contrib
https://github.com/opencv/opencv_contrib/tree/e6f63c7a38ca40c5dc33e38736e3027e3528d6cb/modules/dnn
2017-06-26 13:41:51 +03:00