opencv

Commit Graph

Author	SHA1	Message	Date
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
Dmitry Kurtaev	c918ac298c	Fix IE tests	6 years ago
Dmitry Kurtaev	ff775b2e54	Remove ASSERT_ANY_THROW checks fpr Myriad plugin and FP32 networks	6 years ago
Alexander Nesterov	97c3bcb1b7	Added fix for other size	6 years ago
Dmitry Kurtaev	f0ddf302b2	Move Inference Engine to new API	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	84ce2cc211	Enable some dnn tests according to the new Intel's Inference Engine release (R4)	6 years ago
Dmitry Kurtaev	0d117312c9	DNN_TARGET_FPGA using Intel's Inference Engine	6 years ago
Dmitry Kurtaev	b5c54e447c	Extra hyperparameters for Intel's Inference Engine layers	6 years ago
Alexander Alekhin	96c71dd3d2	dnn: reduce set of ignored warnings	6 years ago
Dmitry Kurtaev	09fa758725	Replace Darknet's Reorg to permute layer	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	3e027df583	Enable more deep learning tests using Intel's Inference Engine backend	6 years ago
Alexander Alekhin	d2e08a524e	core: repair CV_Assert() messages Multi-argument CV_Assert() is accessible via CV_Assert_N() (with malformed messages).	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
Dmitry Kurtaev	070393dfda	uint8 inputs for deep learning networks	6 years ago
Dmitry Kurtaev	dcc1beb1f8	Clip kernel for OpenCL PriorBox layer	6 years ago
Alexander Alekhin	e2b5d11290	dnn: allow to use external protobuf "custom layers" feature will not work properly in these builds.	6 years ago
Alexander Alekhin	52b151dceb	dnn(test): use checkMyriadTarget() in Test_Caffe_layers.Conv_Elu test	6 years ago
Dmitry Kurtaev	019c2f2115	Enable more deep learning tests	6 years ago
Dmitry Kurtaev	f25a01bb5a	Disable fusion to output layers	6 years ago
Dmitry Kurtaev	7ed5d85f25	Add Reshape layer tests	7 years ago
Dmitry Kurtaev	346871e27f	Set output layers names and types for models in DLDT's intermediate representation	7 years ago
Dmitry Kurtaev	b11e22c25b	Update Inference Engine tests	7 years ago
Dmitry Kurtaev	e8e9d1d021	Implement Interp layer using Resize layer	7 years ago
Dmitry Kurtaev	4626246087	Add ShuffleChannel layer	7 years ago
Dmitry Kurtaev	40b85c1cd9	Remove undocumented feature to retreive layers outputs by indices	7 years ago
Dmitry Kurtaev	40765c5f8d	Enable SSD models from TensorFlow with OpenCL plugin of Intel's Inference Engine	7 years ago
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	7 years ago
Dmitry Kurtaev	b781ac7346	Make Intel's Inference Engine backend is default if no preferable backend is specified.	7 years ago
Dmitry Kurtaev	ab389142af	Fix multiple networks with Intel's Inference Engine backend	7 years ago
Dmitry Kurtaev	32bab45f81	Fix Inference Engine graphs with fused output layers	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

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94 Commits (4de1efd3c81c7799883204c1bdcb1fd209fa3c94)