Alexander Alekhin
21e28adb87
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-05-22 19:50:14 +00:00
Liubov Batanina
d991c22090
Merge pull request #16575 from l-bat:flownet2
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Support FlowNet2 model
* Support DataAugmentation layer
* Fix warnings
* Fix comments
* Support Correlation layer
* TEST
* Support Correlation layer
* Supported Accum and FlowWarp layers
* Supported ChannelNorm layer
* Supported Resample with inputs.size() > 1
* Fixed comments
* Refactoring
* Added tests
* Add resample test
* Added asserts in resize layer
* Updated DataAugmentation layer
* Update convolution layer
* Refactoring
* Fix data augmentation layer
* Fix caffe importer
* Fix resize
* Switch to Mat ptr
* Remove useless resize type
* Used ResizeLayer in Accum
* Split ChannelNormLayer
* Delete duplicate assert
* Add sample
* Fix sample
* Added colormap
2020-05-19 12:29:50 +00:00
Alexander Alekhin
593af7287b
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-05-18 17:50:16 +00:00
Dmitry Kurtaev
df305e83fa
Fix BatchNorm reinitialization after fusion
2020-05-13 22:15:36 +03:00
Alexander Alekhin
09799402f9
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-05-06 19:53:51 +00:00
Dmitry Kurtaev
8b13b85c5e
dnn: Slice with variable input shapes
2020-05-05 13:35:17 +03:00
Alexander Alekhin
225566da7b
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-02-04 19:49:24 +03:00
Dmitry Kurtaev
005f38fb45
Fix dnn::ResizeLayer to manage varying input shapes
2020-02-04 09:06:17 +03:00
Alexander Alekhin
2ced568d34
Merge pull request #16220 from YashasSamaga:cuda4dnn-roi-pooling-test_fix-optim
2020-01-29 20:57:15 +00:00
Yashas Samaga B L
d85e67d3ec
Merge pull request #16063 from YashasSamaga:cuda4dnn-shortcut-unequal
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support eltwise sum with different number of input channels in CUDA backend
* add shortcut primitive
* add offsets in shortcut kernel
* skip tests involving more than two inputs
* remove redundant modulus operation
* support multiple inputs
* remove whole file indentation
* skip acc in0 trunc test if weighted
* use shortcut iff channels are unequal
2020-01-16 21:54:00 +03:00
YashasSamaga
fd369a5004
fix and optimize ROIPooling
2020-01-15 22:53:48 +05:30
Alexander Alekhin
4cb9faf6c9
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-01-14 17:04:22 +03:00
Dmitry Kurtaev
8f1e36f7c1
Disable some tests for Myriad target of nGraph
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Add lightweight IE hardware targets checks
nGraph: Concat with paddings
Enable more nGraph tests
Restore FP32->FP16 for GPU plugin of IE
try to fix buildbot
Use lightweight IE targets check only starts from R4
2020-01-13 15:35:47 +03:00
Yashas Samaga B L
1fac1421e5
Merge pull request #16010 from YashasSamaga:cuda4dnn-fp16-tests
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* enable tests for DNN_TARGET_CUDA_FP16
* disable deconvolution tests
* disable shortcut tests
* fix typos and some minor changes
* dnn(test): skip CUDA FP16 test too (run_pool_max)
2019-12-20 16:36:32 +03:00
Alexander Alekhin
92b9888837
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2019-12-12 13:02:19 +03:00
Alexander Alekhin
5ee7abbe3c
Merge pull request #16088 from alalek:dnn_eltwise_layer_different_src_channels
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dnn(eltwise): fix handling of different number of channels
* dnn(test): reproducer for Eltwise layer issue from PR16063
* dnn(eltwise): rework support for inputs with different channels
* dnn(eltwise): get rid of finalize(), variableChannels
* dnn(eltwise): update input sorting by number of channels
- do not swap inputs if number of channels are same after truncation
* dnn(test): skip "shortcut" with batch size 2 on MYRIAD targets
2019-12-11 20:16:58 +03:00
Alexander Alekhin
4b0132ed7a
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2019-12-02 16:26:52 +03:00
Lubov Batanina
7523c777c5
Merge pull request #15537 from l-bat:ngraph
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* Support nGraph
* Fix resize
2019-12-02 16:16:06 +03:00
Alexander Alekhin
055ffc0425
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2019-10-24 18:21:19 +00:00
Yashas Samaga B L
613c12e590
Merge pull request #14827 from YashasSamaga:cuda4dnn-csl-low
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CUDA backend for the DNN module
* stub cuda4dnn design
* minor fixes for tests and doxygen
* add csl public api directory to module headers
* add low-level CSL components
* add high-level CSL components
* integrate csl::Tensor into backbone code
* switch to CPU iff unsupported; otherwise, fail on error
* add fully connected layer
* add softmax layer
* add activation layers
* support arbitary rank TensorDescriptor
* pass input wrappers to `initCUDA()`
* add 1d/2d/3d-convolution
* add pooling layer
* reorganize and refactor code
* fixes for gcc, clang and doxygen; remove cxx14/17 code
* add blank_layer
* add LRN layer
* add rounding modes for pooling layer
* split tensor.hpp into tensor.hpp and tensor_ops.hpp
* add concat layer
* add scale layer
* add batch normalization layer
* split math.cu into activations.cu and math.hpp
* add eltwise layer
* add flatten layer
* add tensor transform api
* add asymmetric padding support for convolution layer
* add reshape layer
* fix rebase issues
* add permute layer
* add padding support for concat layer
* refactor and reorganize code
* add normalize layer
* optimize bias addition in scale layer
* add prior box layer
* fix and optimize normalize layer
* add asymmetric padding support for pooling layer
* add event API
* improve pooling performance for some padding scenarios
* avoid over-allocation of compute resources to kernels
* improve prior box performance
* enable layer fusion
* add const layer
* add resize layer
* add slice layer
* add padding layer
* add deconvolution layer
* fix channelwise ReLU initialization
* add vector traits
* add vectorized versions of relu, clipped_relu, power
* add vectorized concat kernels
* improve concat_with_offsets performance
* vectorize scale and bias kernels
* add support for multi-billion element tensors
* vectorize prior box kernels
* fix address alignment check
* improve bias addition performance of conv/deconv/fc layers
* restructure code for supporting multiple targets
* add DNN_TARGET_CUDA_FP64
* add DNN_TARGET_FP16
* improve vectorization
* add region layer
* improve tensor API, add dynamic ranks
1. use ManagedPtr instead of a Tensor in backend wrapper
2. add new methods to tensor classes
- size_range: computes the combined size of for a given axis range
- tensor span/view can be constructed from a raw pointer and shape
3. the tensor classes can change their rank at runtime (previously rank was fixed at compile-time)
4. remove device code from tensor classes (as they are unused)
5. enforce strict conditions on tensor class APIs to improve debugging ability
* fix parametric relu activation
* add squeeze/unsqueeze tensor API
* add reorg layer
* optimize permute and enable 2d permute
* enable 1d and 2d slice
* add split layer
* add shuffle channel layer
* allow tensors of different ranks in reshape primitive
* patch SliceOp to allow Crop Layer
* allow extra shape inputs in reshape layer
* use `std::move_backward` instead of `std::move` for insert in resizable_static_array
* improve workspace management
* add spatial LRN
* add nms (cpu) to region layer
* add max pooling with argmax ( and a fix to limits.hpp)
* add max unpooling layer
* rename DNN_TARGET_CUDA_FP32 to DNN_TARGET_CUDA
* update supportBackend to be more rigorous
* remove stray include from preventing non-cuda build
* include op_cuda.hpp outside condition #if
* refactoring, fixes and many optimizations
* drop DNN_TARGET_CUDA_FP64
* fix gcc errors
* increase max. tensor rank limit to six
* add Interp layer
* drop custom layers; use BackendNode
* vectorize activation kernels
* fixes for gcc
* remove wrong assertion
* fix broken assertion in unpooling primitive
* fix build errors in non-CUDA build
* completely remove workspace from public API
* fix permute layer
* enable accuracy and perf. tests for DNN_TARGET_CUDA
* add asynchronous forward
* vectorize eltwise ops
* vectorize fill kernel
* fixes for gcc
* remove CSL headers from public API
* remove csl header source group from cmake
* update min. cudnn version in cmake
* add numerically stable FP32 log1pexp
* refactor code
* add FP16 specialization to cudnn based tensor addition
* vectorize scale1 and bias1 + minor refactoring
* fix doxygen build
* fix invalid alignment assertion
* clear backend wrappers before allocateLayers
* ignore memory lock failures
* do not allocate internal blobs
* integrate NVTX
* add numerically stable half precision log1pexp
* fix indentation, following coding style, improve docs
* remove accidental modification of IE code
* Revert "add asynchronous forward"
This reverts commit 1154b9da9da07e9b52f8a81bdcea48cf31c56f70.
* [cmake] throw error for unsupported CC versions
* fix rebase issues
* add more docs, refactor code, fix bugs
* minor refactoring and fixes
* resolve warnings/errors from clang
* remove haveCUDA() checks from supportBackend()
* remove NVTX integration
* changes based on review comments
* avoid exception when no CUDA device is present
* add color code for CUDA in Net::dump
2019-10-21 14:28:00 +03:00
Dmitry Kurtaev
af61a15839
Fix Darknet eltwise
2019-10-19 12:54:15 +03:00
Dmitry Kurtaev
adbd613660
Enable Eltwise layer with different numbers of inputs channels
2019-10-18 18:51:52 +03:00
Alexander Alekhin
7ce9428e96
Merge pull request #15580 from smbz:dnn-lstm-reverse
2019-09-25 15:54:06 +00:00
Andrew Ryrie
b88435fdc2
dnn: Allow LSTM layer to operate in reverse direction
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This is useful for bidirectional LSTMs.
2019-09-25 14:12:43 +01:00
Dmitry Kurtaev
ba703157cf
Merge pull request #15063 from dkurt:dnn_ie_ocv_layers
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* Wrap unsupported by IE layers as custom layers
* Replace pointers to layers blobs to their shapes
* Enable Faster R-CNN with IE backend on CPU
2019-09-03 18:58:57 +03:00
Alexander Alekhin
b584c23061
Merge pull request #15158 from dkurt:fix_tf_ssd_configs
2019-08-02 16:08:55 +00:00
Lubov Batanina
5a6b23e8f3
Support for several min and max sizes in PriorBox layer (Merge pull request #15076 )
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* Support for several min and max sizes in PriorBox layer
* Fix minSize
* Check size
* Modify initInfEngine
* Fix tests
* Fix IE support
* Add priorbox test
* Remove inputs
2019-07-30 17:23:47 +03:00
Dmitry Kurtaev
77d4e3e8d2
Fix 2019R2 tests
2019-07-27 13:30:15 +03:00
Dmitry Kurtaev
75f4c1abf2
Enable some tests for Inference Engine backend
2019-06-28 15:52:31 +03:00
Alexander Alekhin
894f208de3
dnn(test): replace SkipTestException with tags
2019-06-23 13:12:23 +00:00
Dmitry Kurtaev
eba696a41e
Merge pull request #14792 from dkurt:dnn_ie_min_version_r5
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* Remove Inference Engine 2018R3 and 2018R4
* Fix 2018R5
2019-06-14 18:17:02 +03:00
Alexander Alekhin
8483801eab
dnn: use OpenVINO 2019R1 defines
2019-04-03 15:39:47 +03:00
Lubov Batanina
7d3d6bc4e2
Merge pull request #13932 from l-bat:MyriadX_master_dldt
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* Fix precision in tests for MyriadX
* Fix ONNX tests
* Add output range in ONNX tests
* Skip tests on Myriad OpenVINO 2018R5
* Add detect MyriadX
* Add detect MyriadX on OpenVINO R5
* Skip tests on Myriad next version of OpenVINO
* dnn(ie): VPU type from environment variable
* dnn(test): validate VPU type
* dnn(test): update DLIE test skip conditions
2019-03-29 16:42:58 +03:00
Dmitry Kurtaev
ed710eaa1c
Make Inference Engine R3 as a minimal supported version
2019-02-21 09:32:26 +03:00
Alexander Alekhin
f67b197d49
Merge pull request #13738 from dkurt:dnn_ie_lock_shared_plugins
2019-02-06 12:09:58 +00:00
Dmitry Kurtaev
bc4e471847
Add a mutex for shared Inference Engine plugins
2019-02-05 19:26:58 +03:00
Dmitry Kurtaev
c918ac298c
Fix IE tests
2019-01-31 14:14:38 +03:00
Dmitry Kurtaev
ff775b2e54
Remove ASSERT_ANY_THROW checks fpr Myriad plugin and FP32 networks
2019-01-25 20:09:54 +03:00
Alexander Nesterov
97c3bcb1b7
Added fix for other size
2019-01-24 12:51:16 -01:00
Dmitry Kurtaev
f0ddf302b2
Move Inference Engine to new API
2019-01-17 14:28:48 +03:00
Dmitry Kurtaev
59ce1d80a5
Fix dnn tests for Inference Engine R5
2018-12-21 12:33:30 +03:00
Dmitry Kurtaev
53f6198f27
Minor fixes in IE backend tests
2018-12-10 20:08:13 +03:00
Dmitry Kurtaev
84ce2cc211
Enable some dnn tests according to the new Intel's Inference Engine release (R4)
2018-11-26 13:02:24 +03:00
Dmitry Kurtaev
0d117312c9
DNN_TARGET_FPGA using Intel's Inference Engine
2018-11-19 11:41:43 +03:00
Alexander Alekhin
f2bec05e6d
Merge pull request #12913 from dkurt:dnn_fix_ie_hyperparams
2018-11-16 18:36:12 +00:00
Dmitry Kurtaev
b5c54e447c
Extra hyperparameters for Intel's Inference Engine layers
2018-11-15 20:06:37 +03:00
Alexander Alekhin
96c71dd3d2
dnn: reduce set of ignored warnings
2018-11-15 13:15:59 +03:00
Dmitry Kurtaev
09fa758725
Replace Darknet's Reorg to permute layer
2018-09-12 18:13:39 +03:00
Dmitry Kurtaev
d486204a0d
Merge pull request #12264 from dkurt:dnn_remove_forward_method
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* Remove a forward method in dnn::Layer
* Add a test
* Fix tests
* Mark multiple dnn::Layer::finalize methods as deprecated
* Replace back dnn's inputBlobs to vector of pointers
* Remove Layer::forward_fallback from CV_OCL_RUN scopes
2018-09-06 13:26:47 +03:00
Dmitry Kurtaev
6ec230480d
Enable Myriad tests with batch size > 1
2018-09-05 10:45:09 +03:00
Dmitry Kurtaev
3e027df583
Enable more deep learning tests using Intel's Inference Engine backend
2018-08-27 18:37:35 +03:00
Alexander Alekhin
d2e08a524e
core: repair CV_Assert() messages
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Multi-argument CV_Assert() is accessible via CV_Assert_N() (with malformed messages).
2018-08-15 17:43:10 +03:00
Dmitry Kurtaev
faa6c4e1e1
Faster-RCNN anf RFCN models on CPU using Intel's Inference Engine backend.
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Enable Torch layers tests with Intel's Inference Engine backend.
2018-07-25 19:04:55 +03:00
Dmitry Kurtaev
070393dfda
uint8 inputs for deep learning networks
2018-07-19 14:37:33 +03:00
Dmitry Kurtaev
dcc1beb1f8
Clip kernel for OpenCL PriorBox layer
2018-07-13 14:49:13 +03:00
Alexander Alekhin
529d38613b
Merge pull request #11923 from alalek:dnn_external_protobuf
2018-07-09 16:07:42 +00:00
Alexander Alekhin
e2b5d11290
dnn: allow to use external protobuf
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"custom layers" feature will not work properly in these builds.
2018-07-09 17:28:45 +03:00
Alexander Alekhin
52b151dceb
dnn(test): use checkMyriadTarget() in Test_Caffe_layers.Conv_Elu test
2018-07-09 16:20:46 +03:00
Vadim Pisarevsky
523b6f32ba
Merge pull request #11867 from dkurt:dnn_ie_layers
2018-07-06 13:13:20 +00:00
Dmitry Kurtaev
019c2f2115
Enable more deep learning tests
2018-07-05 14:23:15 +03:00
Dmitry Kurtaev
f25a01bb5a
Disable fusion to output layers
2018-07-04 15:53:47 +03:00
Dmitry Kurtaev
7ed5d85f25
Add Reshape layer tests
2018-07-03 08:26:43 +03:00
Dmitry Kurtaev
346871e27f
Set output layers names and types for models in DLDT's intermediate representation
2018-06-28 10:21:45 +03:00
Dmitry Kurtaev
b11e22c25b
Update Inference Engine tests
2018-06-26 15:38:08 +03:00
Dmitry Kurtaev
e8e9d1d021
Implement Interp layer using Resize layer
2018-06-22 19:26:47 +03:00
Dmitry Kurtaev
4626246087
Add ShuffleChannel layer
2018-06-21 19:10:42 +03:00
Dmitry Kurtaev
40b85c1cd9
Remove undocumented feature to retreive layers outputs by indices
2018-06-20 14:44:21 +03:00
Dmitry Kurtaev
40765c5f8d
Enable SSD models from TensorFlow with OpenCL plugin of Intel's Inference Engine
2018-06-08 16:55:21 +03:00
rockzhan
1187a7fa34
Merge pull request #11649 from rockzhan:dnn_dw_prelu
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dnn: Fix output mismatch when forward dnn model contain [depthwise conv(group=1) + bn + prelu] (#11649 )
* this can make sure [depthwise conv(group=1) + bn + prelu] output not shift
* add TEST to show the output mismatch in [DWconv+Prelu]
* fix typo
* change loading image to init cvMat directly
* build runtime model, without loading external model
* remove whitespace
* change way to create a cvmat
* add bias_term, add target output
* fix [dwconv + prelu] value mismatch when no optimizations
* fix Test error when change output channels
* add parametric test
* change num_output to group value
* change conv code and change test back
2018-06-07 13:45:54 +00:00
Vadim Pisarevsky
3cbd2e2764
Merge pull request #11650 from dkurt:dnn_default_backend
2018-06-06 09:30:39 +00:00
Dmitry Kurtaev
b781ac7346
Make Intel's Inference Engine backend is default if no preferable backend is specified.
2018-06-04 18:31:46 +03:00
Dmitry Kurtaev
ab389142af
Fix multiple networks with Intel's Inference Engine backend
2018-06-01 14:10:32 +03:00
Dmitry Kurtaev
32bab45f81
Fix Inference Engine graphs with fused output layers
2018-05-31 16:21:08 +03:00
Dmitry Kurtaev
4ec456f0a0
Custom layers for deep learning networks ( #11129 )
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* Custom deep learning layers support
* Stack custom deep learning layers
2018-04-24 14:59:59 +03:00
Dmitry Kurtaev
4ef6c91583
Fix multiple inputs for models from Intel's Model Optimizer
2018-04-11 13:28:07 +03:00
Dmitry Kurtaev
ef1aaf12c9
Fix Proposal deep learning layer
2018-04-04 14:48:29 +03:00
Alexander Alekhin
e8a67de0d2
Merge pull request #11182 from dkurt:fix_11102_part_2
2018-03-30 13:11:01 +00:00
Dmitry Kurtaev
e039fc3a63
Replace protobuf's ReleaseLast to RemoveLast to deallocate memory.
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Change an order of PriorBox layer operations.
2018-03-28 17:27:36 +03:00
Dmitry Kurtaev
7972f47ed4
Load networks from intermediate representation of Intel's Deep learning deployment toolkit.
2018-03-26 07:24:21 +03:00
Dmitry Kurtaev
e8fe6ee4e3
Fix prior box generation in case of squared proposals.
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Fix batch norm in training phase.
2018-03-23 09:44:59 +03:00
Dmitry Kurtaev
f8d0d6365e
Add a flag to manage average pooling with padding
2018-02-14 16:56:31 +03:00
Alexander Alekhin
4a297a2443
ts: refactor OpenCV tests
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- removed tr1 usage (dropped in C++17)
- moved includes of vector/map/iostream/limits into ts.hpp
- require opencv_test + anonymous namespace (added compile check)
- fixed norm() usage (must be from cvtest::norm for checks) and other conflict functions
- added missing license headers
2018-02-03 19:39:47 +00:00
Li Peng
7a4c5e9421
slice layer ocl support
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Signed-off-by: Li Peng <peng.li@intel.com>
2018-01-29 22:34:32 +08:00
Alexander Alekhin
c3569211d5
Merge pull request #10591 from drkoller:master
2018-01-19 09:44:21 +00:00
Li Peng
2124361ff7
ocl support for Deconvolution layer
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Signed-off-by: Li Peng <peng.li@intel.com>
2018-01-18 23:40:22 +08:00
David Koller
d1a3b530be
Make DNN Crop layer match Caffe default offset behavior
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and add parametric unit test for crop layer.
2018-01-17 10:52:36 -05:00
Li Peng
e77af4ae33
MVN layer ocl implementation
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Signed-off-by: Li Peng <peng.li@intel.com>
2018-01-17 17:11:32 +08:00
Li Peng
7bc017601f
Power, Tanh and Channels ReLU layer ocl support
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Signed-off-by: Li Peng <peng.li@intel.com>
2018-01-17 17:11:27 +08:00
Dmitry Kurtaev
1f4fdfd599
Untrainable version of Scale layer from Caffe
2018-01-13 10:35:29 +03:00
Li Peng
f99a135eda
add eltwise layer ocl implementation
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Signed-off-by: Li Peng <peng.li@intel.com>
2018-01-05 19:38:30 +08:00
Alexander Alekhin
2b3c140f04
Merge pull request #10436 from alalek:test_threads
2017-12-28 18:29:30 +03:00
Li Peng
00f03c5739
Add ocl version FasterRCNN accuracy test
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Signed-off-by: Li Peng <peng.li@intel.com>
2017-12-28 19:15:15 +08:00
Alexander Alekhin
9b131b5f7e
dnn(test): avoid calling of cv::setNumThreads() in tests directly
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It is not necessary by default.
Also it breaks test system command-line parameters: --perf_threads / --test_threads
2017-12-27 15:16:41 +00:00
Dmitry Kurtaev
70c605a03d
Limit Concat layer optimization
2017-12-26 16:49:33 +03:00
Dmitry Kurtaev
08112f3821
Faster-RCNN models support
2017-12-15 12:16:21 +03:00
Dmitry Kurtaev
17dcf0e82d
ROIPooling layer
2017-12-07 19:04:38 +03:00
Dmitry Kurtaev
20a2dc6ac5
Fix multiple inputs models from Caffe.
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Fixed Concat optimization.
2017-11-02 18:55:08 +03:00
Dmitry Kurtaev
a36ebaecdc
PReLU layer for multidimensional input
2017-10-23 16:13:03 +03:00
Vadim Pisarevsky
b7ff9ddcdd
Merge pull request #9705 from AlexeyAB:dnn_darknet_yolo_v2
2017-10-10 12:02:03 +00:00
AlexeyAB
ecc34dc521
Added DNN Darknet Yolo v2 for object detection
2017-10-09 21:08:44 +03:00