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171 Commits

Author SHA1 Message Date
Alexander Alekhin
5c76f99fdd Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-09-05 19:37:38 +00:00
YashasSamaga
1df533c914 fix typo in fusion tests 2020-09-02 14:25:36 +05:30
Alexander Alekhin
ba147d2be2 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-08-26 15:51:25 +00:00
Alexander Alekhin
792722865f Merge pull request #17919 from zhaoyue-zephyrus:flownet2_with_anysize 2020-08-26 11:43:17 +00:00
Alexander Alekhin
b45273eccb Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-08-14 19:45:45 +00:00
Yashas Samaga B L
2171cae8ff
Merge pull request #17976 from YashasSamaga:dnn-fusion-tests-fix-ocl 
dnn: add exhaustive fusion tests, enable more eltwise fusions

* add eltwise fusion tests, enable more eltwise fusions

* merge weighted eltwise tests with eltwise tests
 2020-08-13 10:55:41 +00:00
zhaoyue-zephyrus
e231be86b7 support flownet2 with arbitary input size 
revise default proto to match the filename in documentations

fix a bug

beautify python codes

fix bug

beautify codes

add test samples with larger/smaller size

remove unless code

using bytearray without creating tmp file

remove useless codes
 2020-08-12 00:50:58 +08:00
Alexander Alekhin
fa25faa2d2 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-08-06 14:15:52 +00:00
Dmitry Kurtaev
cf8f65d806 Do not use size_t for nGraph layers 2020-08-02 20:50:44 +03:00
Alexander Alekhin
9b7b22ee0e Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-07-16 20:13:27 +00:00
Alexander Alekhin
b2ebd37ee2 Merge pull request #17856 from alalek:dnn_openvino_2020.4.0 2020-07-16 20:08:00 +00:00
Alexander Alekhin
81e027eef7 dnn: fix OpenCL implementation of Slice layer 2020-07-16 04:33:52 +00:00
Alexander Alekhin
1c371d07b5 dnn(test): adjust tests for OpenVINO 2020.4 2020-07-15 23:47:40 +00:00
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 
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 
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 
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 
* 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 
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 
* 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 
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 
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 
* 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) 
* 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 
* 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 
* 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 
* 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 
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. 
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 
"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 
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) 
* 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. 
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. 
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 
- 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 
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 
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 
and add parametric unit test for crop layer.
 2018-01-17 10:52:36 -05:00
Li Peng
e77af4ae33 MVN layer ocl implementation 
Signed-off-by: Li Peng <peng.li@intel.com>
 2018-01-17 17:11:32 +08:00