Commit Graph

14 Commits

Author SHA1 Message Date
Alexander Alekhin
1060c0f439 dnn: apply CV_OVERRIDE/CV_FINAL 2018-03-28 18:43:27 +03:00
Alexander Alekhin
1b83bc48a1 dnn: make OpenCL DNN code optional 2018-03-01 12:12:40 +03:00
Vadim Pisarevsky
6dfd7e3da2 Merge pull request #10850 from dkurt:dnn_tf_deconv_tests 2018-02-14 10:35:14 +00:00
Dmitry Kurtaev
514e6df460 Refactored deep learning layers fusion 2018-02-13 14:35:58 +03:00
Dmitry Kurtaev
a6baedd02c Fix deconvolution layer. Add batch norm layer with mean-variance normalization from TensorFlow. 2018-02-13 11:00:27 +03:00
Li Peng
6aec71d7ee mvn layer ocl update
it fuse ocl kernels to reduce kernel enqueue

Signed-off-by: Li Peng <peng.li@intel.com>
2018-02-01 17:48:12 +08:00
Li Peng
83b16ab7b7 fix extra spaces in build option
Signed-off-by: Li Peng <peng.li@intel.com>
2018-02-01 17:46:11 +08:00
Li Peng
2493083935 mvn, batch_norm and relu layer fusion
Signed-off-by: Li Peng <peng.li@intel.com>
2018-01-25 18:57:05 +08:00
Li Peng
fe494297e4 more update on MVN layer ocl implementation
cut one ocl kernel if normVariance is disabled,
also use native_powr for performance reason.

Signed-off-by: Li Peng <peng.li@intel.com>
2018-01-19 22:54:04 +08:00
Li Peng
e77af4ae33 MVN layer ocl implementation
Signed-off-by: Li Peng <peng.li@intel.com>
2018-01-17 17:11:32 +08:00
Li Peng
8f99083726 Add new layer forward interface
Add layer forward interface with InputArrayOfArrays and
OutputArrayOfArrays parameters, it allows UMat buffer to be
processed and transferred in the layers.

Signed-off-by: Li Peng <peng.li@intel.com>
2017-11-09 15:59:39 +08:00
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
93729784bb dnn: move module from opencv_contrib
e6f63c7a38/modules/dnn
2017-06-26 13:41:51 +03:00