opencv

Commit Graph

Author	SHA1	Message	Date
Alexander Alekhin	bd396e1fd5	dnn(test): re-enable tests which works with OpenVINO 2021.4.x (3.4)	3 years ago
Alexander Alekhin	985aa0423d	dnn(test): update InferenceEngine tests	3 years ago
Alexander Alekhin	6797fd65a5	dnn(test): update tests for OpenVINO 2021.4	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
YashasSamaga	0f8ab0557e	enable fusion tests, update thresholds and fix missed eltwise fusions	4 years ago
Alexander Alekhin	6da05f7086	dnn(test): update tests for OpenVINO 2021.1	4 years ago
Tomoaki Teshima	48368dc9a1	loosen threshold for Mali	4 years ago
Dmitry Kurtaev	d8dea7896b	Merge pull request #16628 from dkurt:dnn_ngraph_custom_layers * Custom layers with nGraph * nGraph: multiple outputs from nodes	5 years ago
Alexander Alekhin	8ecfb59930	dnn(test): skip failed ngraph tests	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
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	e35fd463e7	Enable ENet with Inference Engine backend on CPU	5 years ago
Dmitry Kurtaev	6193e403e7	Enable some tests for 2019R2	5 years ago
Alexander Alekhin	894f208de3	dnn(test): replace SkipTestException with tags	6 years ago
Alexander Alekhin	13a782c039	test: fix usage of findDataFile() misused 'optional' mode	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
Dmitry Kurtaev	9c0af1f675	Enable more deconvolution layer configurations with IE backend	6 years ago
Alexander Alekhin	e0841f3d6e	dnn(test-tags): add time / memory tags	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
Alexander Nesterov	74574dfae4	Added optimization fuse	6 years ago
Dmitry Kurtaev	ed710eaa1c	Make Inference Engine R3 as a minimal supported version	6 years ago
Liubov Batanina	183c0fcab1	Changed condition for resize and lrn layers	6 years ago
Liubov Batanina	6b4becfd03	Enabled tests on IE backend	6 years ago
Dmitry Kurtaev	f0ddf302b2	Move Inference Engine to new API	6 years ago
Dmitry Kurtaev	840c892abd	Batch normalization in training phase from Torch	6 years ago
Dmitry Kurtaev	59ce1d80a5	Fix dnn tests for Inference Engine R5	6 years ago
Dmitry Kurtaev	53f6198f27	Minor fixes in IE backend tests	6 years ago
Dmitry Kurtaev	b5c54e447c	Extra hyperparameters for Intel's Inference Engine layers	6 years ago
Dmitry Kurtaev	e7015f6ae8	Fix ENet test	6 years ago
Dmitry Kurtaev	58ac3e09da	Change default value of crop argument of blobFromImage from true to false	6 years ago
Vadim Pisarevsky	54279523a3	Merge pull request #12437 from vpisarev:avx2_fixes * trying to fix the custom AVX2 builder test failures (false alarms) * fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests * fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests * fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests * seemingly disabled false alarm warning in surf.cpp; increased tolerance thresholds in the tests for SolvePnP and in DNN/ENet	6 years ago
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	6 years ago
Dmitry Kurtaev	6ec230480d	Enable Myriad tests with batch size > 1	6 years ago
Dmitry Kurtaev	50bceea038	Include preprocessing nodes to object detection TensorFlow networks (#12211 ) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test	6 years ago
Dmitry Kurtaev	3e027df583	Enable more deep learning tests using Intel's Inference Engine backend	6 years ago
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.	6 years ago
Alexander Alekhin	452fa3011c	dnn(test): drop CV_ENUM for DNNBackend / DNNTarget	6 years ago
Dmitry Kurtaev	019c2f2115	Enable more deep learning tests	6 years ago
Dmitry Kurtaev	40b85c1cd9	Remove undocumented feature to retreive layers outputs by indices	7 years ago
Dmitry Kurtaev	2c291bc2fb	Enable FastNeuralStyle and OpenFace networks with IE backend	7 years ago
Dmitry Kurtaev	b781ac7346	Make Intel's Inference Engine backend is default if no preferable backend is specified.	7 years ago
Kuang Fangjun	9ae28415ec	fix doc.	7 years ago
Dmitry Kurtaev	4ec456f0a0	Custom layers for deep learning networks (#11129 ) * Custom deep learning layers support * Stack custom deep learning layers	7 years ago
Dmitry Kurtaev	818a91f4f7	Update Torch testdata	7 years ago
Dmitry Kurtaev	598039c0ed	Fix embedded Torch's nn.ConcatTable	7 years ago
Dmitry Kurtaev	0a61ebdd66	Replace DNNTarget and DNNBackend in tests	7 years ago
Dmitry Kurtaev	e1c3237532	Parametric OpenCL deep learning tests	7 years ago

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79 Commits (41d108ead6a1f8701092f6b1bee2569f68c16bfd)