opencv

Commit Graph

Author	SHA1	Message	Date
Alexander Alekhin	d16b3b2487	dnn(test): restore openvino tests with 'Cannot get memory' message	2 years ago
Zihao Mu	0fa43e3aac	Optimize the winograd futher more.	2 years ago
Alexander Alekhin	4d927e73f1	dnn(test): update OpenVINO tests 2022.1.0	3 years ago
Egor Smirnov	375fe81311	fix slice and expand	3 years ago
Alexander Alekhin	effce0573b	dnn: drop legacy Inference Engine NN builder API	3 years ago
Alexander Alekhin	bd396e1fd5	dnn(test): re-enable tests which works with OpenVINO 2021.4.x (3.4)	3 years ago
Alexander Alekhin	58dc397930	dnn(test): add two_inputs test with FP32/U8 data types - remove similar test from IE scope under HAVE_INF_ENGINE	3 years ago
Alexander Alekhin	985aa0423d	dnn(test): update InferenceEngine tests	3 years ago
rogday	38b9ec7a18	Merge pull request #20682 from rogday:min * Add Min layer to CPU, OpenCL, Halide, Inference Engine, NGraph and CUDA * fix indentation * add min to fusion and halide tests; fix doc	3 years ago
Julia Bareeva	e1cafa3834	Merge pull request #20442 from JulieBar:gru_layer * Add initialization and inference for GRU layer * fix issues found on review	3 years ago
Julia Bareeva	4e5699fa71	Merge pull request #20450 from JulieBar:lstm_inside Support non-zero hidden state for LSTM * fully support non-zero hidden state for LSTM * check dims of hidden state for LSTM * fix failed test Test_Model.TextRecognition * add new tests for LSTM w/ non-zero hidden params Co-authored-by: Julie Bareeva <julia.bareeva@xperience.ai>	3 years ago
Aaron Greig	f59917bea1	Introduce relaxed accuracy thresholds for CL target in some dnn tests. Partially addresses #9821	4 years ago
Alexander Alekhin	e56e4876e7	dnn(test): update tests for OpenVINO 2021.3	4 years ago
SamFC10	96947c30c0	Added exp layer backport of commit: `6111935835` partial backport of commit: `dd5976162b`	4 years ago
SamFC10	6111935835	Added exp layer	4 years ago
YashasSamaga	0f8ab0557e	enable fusion tests, update thresholds and fix missed eltwise fusions	4 years ago
Alexander Alekhin	cdcf7e62f3	dnn(opencl): bypass unsupported fusion cases 2	4 years ago
Alexander Alekhin	718dd9f170	dnn(opencl): bypass unsupported fusion cases	4 years ago
Alexander Alekhin	e87a0baa4b	dnn(test): enable tests from issue 17953	4 years ago
Alexander Alekhin	c08f29c803	dnn(opencl): fix convolution kernel w/o bias with activation	4 years ago
YashasSamaga	1df533c914	fix typo in fusion tests	4 years ago
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	4 years ago
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	4 years ago
Dmitry Kurtaev	cf8f65d806	Do not use size_t for nGraph layers	4 years ago
Alexander Alekhin	81e027eef7	dnn: fix OpenCL implementation of Slice layer	4 years ago
Alexander Alekhin	1c371d07b5	dnn(test): adjust tests for OpenVINO 2020.4	4 years ago
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	5 years ago
Dmitry Kurtaev	df305e83fa	Fix BatchNorm reinitialization after fusion	5 years ago
Dmitry Kurtaev	8b13b85c5e	dnn: Slice with variable input shapes	5 years ago
Dmitry Kurtaev	005f38fb45	Fix dnn::ResizeLayer to manage varying input shapes	5 years ago
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	5 years ago
YashasSamaga	fd369a5004	fix and optimize ROIPooling	5 years ago
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	5 years ago
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)	5 years ago
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	5 years ago
Lubov Batanina	7523c777c5	Merge pull request #15537 from l-bat:ngraph * Support nGraph * Fix resize	5 years ago
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	5 years ago
Dmitry Kurtaev	af61a15839	Fix Darknet eltwise	5 years ago
Dmitry Kurtaev	adbd613660	Enable Eltwise layer with different numbers of inputs channels	5 years ago
Andrew Ryrie	b88435fdc2	dnn: Allow LSTM layer to operate in reverse direction This is useful for bidirectional LSTMs.	5 years ago
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	5 years ago
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	5 years ago
Dmitry Kurtaev	77d4e3e8d2	Fix 2019R2 tests	5 years ago
Dmitry Kurtaev	75f4c1abf2	Enable some tests for Inference Engine backend	6 years ago
Alexander Alekhin	894f208de3	dnn(test): replace SkipTestException with tags	6 years ago
Dmitry Kurtaev	eba696a41e	Merge pull request #14792 from dkurt:dnn_ie_min_version_r5 * Remove Inference Engine 2018R3 and 2018R4 * Fix 2018R5	6 years ago
Alexander Alekhin	8483801eab	dnn: use OpenVINO 2019R1 defines	6 years ago
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	6 years ago
Dmitry Kurtaev	ed710eaa1c	Make Inference Engine R3 as a minimal supported version	6 years ago
Dmitry Kurtaev	bc4e471847	Add a mutex for shared Inference Engine plugins	6 years ago

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154 Commits (a08c98cdfb781af95dcf481c6ac38ad26ff945c3)