fa90e14b06
int8 layers and 8-bit quantization support
4 years ago
c0dd82fb53
Merge pull request #19632 from l-bat:lb/ie_arm_target
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Added OpenVINO ARM target
* Added IE ARM target
* Added OpenVINO ARM target
* Delete ARM target
* Detect ARM platform
* Changed device name in ArmPlugin
* Change ARM detection
4 years ago
8fa013309e
Merge pull request #19479 from ilyachur:remove_v0_multiply
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* Switched to v1 Multiply
* Apply changes only for new OV
4 years ago
83aa711346
dnn: rename clamp() => normalize_axis()
4 years ago
e231be86b7
support flownet2 with arbitary input size
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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
5 years ago
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
5 years ago
b27ae9c63b
Switch v1::Multiply to v0::Multiply
5 years ago
2aeb32d2d1
fix segfaults, support bias in untrainable mode, support batches in untrainable mode
5 years ago
7d1c42afe1
dnn: fix merge mistake in scale_layer.cpp
5 years ago
9e332dc5fb
Broadcasting from ONNX
5 years ago
124bf8339f
dnn(IE): use HAVE_DNN_IE_NN_BUILDER_2019 for NN Builder API code
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- CMake option: OPENCV_DNN_IE_NN_BUILDER_2019
5 years ago
29d214474f
dnn(IE): use HAVE_DNN_IE_NN_BUILDER_2019 for NN Builder API code
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- CMake option: OPENCV_DNN_IE_NN_BUILDER_2019
5 years ago
f3eef792eb
Enable Mask R-CNN with Inference Engine. Full coverage with nGraph
5 years ago
7523c777c5
Merge pull request #15537 from l-bat:ngraph
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* Support nGraph
* Fix resize
5 years ago
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
6 years ago
0e1ef8f8e1
Merge pull request #15184 from l-bat:IE_R2
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Support new IE API (#15184 )
* Add support OpenVINO R2 for layers
* Add Core API
* Fix tests
* Fix expectNoFallbacksFromIE for ONNX nets
* Remove deprecated API
* Remove td
* Remove TargetDevice
* Fix Async
* Add test
* Fix detectMyriadX
* Fix test
* Fix warning
6 years ago
eba696a41e
Merge pull request #14792 from dkurt:dnn_ie_min_version_r5
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* Remove Inference Engine 2018R3 and 2018R4
* Fix 2018R5
6 years ago
ca5976e3d4
Fix IE backend considering future changes.
6 years ago
f0ddf302b2
Move Inference Engine to new API
6 years ago
96c71dd3d2
dnn: reduce set of ignored warnings
7 years ago
a39e0daacf
Utilize CV_UNUSED macro
7 years ago
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
7 years ago
d2e08a524e
core: repair CV_Assert() messages
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Multi-argument CV_Assert() is accessible via CV_Assert_N() (with malformed messages).
7 years ago
8e034053af
Faster-RCNN from TensorFlow on CPU with Intel's Inference Engine backend
7 years ago
b781ac7346
Make Intel's Inference Engine backend is default if no preferable backend is specified.
7 years ago
2c3c59d018
Remove Shift deep learning layer
7 years ago
895e10c317
dnn: fixed IE support on Windows
7 years ago
709cf5d038
OpenCL GPU target for Inference Engine deep learning backend
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Enable FP16 GPU target for DL Inference Engine backend.
7 years ago
1060c0f439
dnn: apply CV_OVERRIDE/CV_FINAL
7 years ago
6c051a55e5
cmake: don't add include <module>/src directory to avoid conflicts
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during opencv_world builds
7 years ago
514e6df460
Refactored deep learning layers fusion
7 years ago
10e1de74d2
Intel Inference Engine deep learning backend ( #10608 )
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* Intel Inference Engine deep learning backend.
* OpenFace network using Inference Engine backend
7 years ago
1f4fdfd599
Untrainable version of Scale layer from Caffe
7 years ago
e307065c8e
Scale layer in case of 2D inputs
7 years ago
8f99083726
Add new layer forward interface
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Add layer forward interface with InputArrayOfArrays and
OutputArrayOfArrays parameters, it allows UMat buffer to be
processed and transferred in the layers.
Signed-off-by: Li Peng <peng.li@intel.com>
8 years ago
e268606e26
Grayscale colorization model ( https://github.com/richzhang/colorization ) test.
8 years ago
ed10383359
dnn: added trace macros
8 years ago
93729784bb
dnn: move module from opencv_contrib
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e6f63c7a38/modules/dnn
8 years ago
SamFC10
Liubov Batanina
Ilya Churaev
Alexander Alekhin
zhaoyue-zephyrus
YashasSamaga
Alexander Alekhin
Dmitry Kurtaev
Hamdi Sahloul
Maksim Shabunin
Li Peng