Commit Graph

75 Commits

Author SHA1 Message Date
Alexander Alekhin
8b4fa2605e Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2021-12-03 12:32:49 +00:00
Smirnov Egor
0e2a3686c0 add alpha parameter to ELU layer 2021-11-30 12:20:35 +03:00
Hanxi Guo
1fcf7ba5bc
Merge pull request #20406 from MarkGHX:gsoc_2021_webnn
[GSoC] OpenCV.js: Accelerate OpenCV.js DNN via WebNN

* Add WebNN backend for OpenCV DNN Module

Update dnn.cpp

Update dnn.cpp

Update dnn.cpp

Update dnn.cpp

Add WebNN head files into OpenCV 3rd partiy files

Create webnn.hpp

update cmake

Complete README and add OpenCVDetectWebNN.cmake file

add webnn.cpp

Modify webnn.cpp

Can successfully compile the codes for creating a MLContext

Update webnn.cpp

Update README.md

Update README.md

Update README.md

Update README.md

Update cmake files and

update README.md

Update OpenCVDetectWebNN.cmake and README.md

Update OpenCVDetectWebNN.cmake

Fix OpenCVDetectWebNN.cmake and update README.md

Add source webnn_cpp.cpp and libary libwebnn_proc.so

Update dnn.cpp

Update dnn.cpp

Update dnn.cpp

Update dnn.cpp

update dnn.cpp

update op_webnn

update op_webnn

Update op_webnn.hpp

update op_webnn.cpp & hpp

Update op_webnn.hpp

Update op_webnn

update the skeleton

Update op_webnn.cpp

Update op_webnn

Update op_webnn.cpp

Update op_webnn.cpp

Update op_webnn.hpp

update op_webnn

update op_webnn

Solved the problems of released variables.

Fixed the bugs in op_webnn.cpp

Implement op_webnn

Implement Relu by WebNN API

Update dnn.cpp for better test

Update elementwise_layers.cpp

Implement ReLU6

Update elementwise_layers.cpp

Implement SoftMax using WebNN API

Implement Reshape by WebNN API

Implement PermuteLayer by WebNN API

Implement PoolingLayer using WebNN API

Update pooling_layer.cpp

Update pooling_layer.cpp

Update pooling_layer.cpp

Update pooling_layer.cpp

Update pooling_layer.cpp

Update pooling_layer.cpp

Implement poolingLayer by WebNN API and add more detailed logs

Update dnn.cpp

Update dnn.cpp

Remove redundant codes and add more logs for poolingLayer

Add more logs in the pooling layer implementation

Fix the indent issue and resolve the compiling issue

Fix the build problems

Fix the build issue

FIx the build issue

Update dnn.cpp

Update dnn.cpp

* Fix the build issue

* Implement BatchNorm Layer by WebNN API

* Update convolution_layer.cpp

This is a temporary file for Conv2d layer implementation

* Integrate some general functions into op_webnn.cpp&hpp

* Update const_layer.cpp

* Update convolution_layer.cpp

Still have some bugs that should be fixed.

* Update conv2d layer and fc layer

still have some problems to be fixed.

* update constLayer, conv layer, fc layer

There are still some bugs to be fixed.

* Fix the build issue

* Update concat_layer.cpp

Still have some bugs to be fixed.

* Update conv2d layer, fully connected layer and const layer

* Update convolution_layer.cpp

* Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron)

* Delete bib19450.aux

* Add WebNN backend for OpenCV DNN Module

Update dnn.cpp

Update dnn.cpp

Update dnn.cpp

Update dnn.cpp

Add WebNN head files into OpenCV 3rd partiy files

Create webnn.hpp

update cmake

Complete README and add OpenCVDetectWebNN.cmake file

add webnn.cpp

Modify webnn.cpp

Can successfully compile the codes for creating a MLContext

Update webnn.cpp

Update README.md

Update README.md

Update README.md

Update README.md

Update cmake files and

update README.md

Update OpenCVDetectWebNN.cmake and README.md

Update OpenCVDetectWebNN.cmake

Fix OpenCVDetectWebNN.cmake and update README.md

Add source webnn_cpp.cpp and libary libwebnn_proc.so

Update dnn.cpp

Update dnn.cpp

Update dnn.cpp

Update dnn.cpp

update dnn.cpp

update op_webnn

update op_webnn

Update op_webnn.hpp

update op_webnn.cpp & hpp

Update op_webnn.hpp

Update op_webnn

update the skeleton

Update op_webnn.cpp

Update op_webnn

Update op_webnn.cpp

Update op_webnn.cpp

Update op_webnn.hpp

update op_webnn

update op_webnn

Solved the problems of released variables.

Fixed the bugs in op_webnn.cpp

Implement op_webnn

Implement Relu by WebNN API

Update dnn.cpp for better test

Update elementwise_layers.cpp

Implement ReLU6

Update elementwise_layers.cpp

Implement SoftMax using WebNN API

Implement Reshape by WebNN API

Implement PermuteLayer by WebNN API

Implement PoolingLayer using WebNN API

Update pooling_layer.cpp

Update pooling_layer.cpp

Update pooling_layer.cpp

Update pooling_layer.cpp

Update pooling_layer.cpp

Update pooling_layer.cpp

Implement poolingLayer by WebNN API and add more detailed logs

Update dnn.cpp

Update dnn.cpp

Remove redundant codes and add more logs for poolingLayer

Add more logs in the pooling layer implementation

Fix the indent issue and resolve the compiling issue

Fix the build problems

Fix the build issue

FIx the build issue

Update dnn.cpp

Update dnn.cpp

* Fix the build issue

* Implement BatchNorm Layer by WebNN API

* Update convolution_layer.cpp

This is a temporary file for Conv2d layer implementation

* Integrate some general functions into op_webnn.cpp&hpp

* Update const_layer.cpp

* Update convolution_layer.cpp

Still have some bugs that should be fixed.

* Update conv2d layer and fc layer

still have some problems to be fixed.

* update constLayer, conv layer, fc layer

There are still some bugs to be fixed.

* Update conv2d layer, fully connected layer and const layer

* Update convolution_layer.cpp

* Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron)

* Update dnn.cpp

* Fix Error in dnn.cpp

* Resolve duplication in conditions in convolution_layer.cpp

* Fixed the issues in the comments

* Fix building issue

* Update tutorial

* Fixed comments

* Address the comments

* Update CMakeLists.txt

* Offer more accurate perf test on native

* Add better perf tests for both native and web

* Modify per tests for better results

* Use more latest version of Electron

* Support latest WebNN Clamp op

* Add definition of HAVE_WEBNN macro

* Support group convolution

* Implement Scale_layer using WebNN

* Add Softmax option for native classification example

* Fix comments

* Fix comments
2021-11-23 21:15:31 +00:00
rogday
b3f966e2ca
Merge pull request #20883 from rogday:eltwise_refactoring
* backport elementwise_layers refactor

* keep NULL
2021-10-19 13:29:22 +00:00
Smirnov Egor
1feb3838b5 add Ceil, Floor, Log, Round, Sqrt, Not, Equal, Less, Greater 2021-10-15 16:02:46 +03:00
Alexander Alekhin
c3ac834526 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2021-09-11 21:27:26 +00:00
rogday
d31b93b513
Merge pull request #20674 from rogday:prelu_slope
Fix PReLU negative slope access pattern

* fix prelu negative slope access pattern

* change begin() to ptr()
2021-09-10 11:07:16 +00:00
SamFC10
fa90e14b06 int8 layers and 8-bit quantization support 2021-08-19 09:56:47 +05:30
Alexander Alekhin
ca8c3dd9b5 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2021-03-22 12:05:23 +00:00
Liubov Batanina
c0dd82fb53
Merge pull request #19632 from l-bat:lb/ie_arm_target
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
2021-03-20 11:20:02 +00:00
SamFC10
96947c30c0 Added exp layer
backport of commit: 6111935835
partial backport of commit: dd5976162b
2021-02-28 19:59:40 +00:00
Maksim Shabunin
dd5976162b Fixed several issues found by static analysis 2021-02-25 15:08:39 +03:00
SamFC10
6111935835 Added exp layer 2021-02-20 22:16:00 +05:30
Alexander Alekhin
afe9993376 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-07-28 17:25:20 +00:00
Sinitsina
0ac2f0e04c mish_functor_update 2020-07-23 09:02:00 +03:00
Alexander Alekhin
c81d785ada Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-06-23 19:15:47 +00:00
Dmitry Kurtaev
1491934d17 Optimize Mish for CPU backend 2020-06-22 23:27:47 +03:00
Alexander Alekhin
124bf8339f dnn(IE): use HAVE_DNN_IE_NN_BUILDER_2019 for NN Builder API code
- CMake option: OPENCV_DNN_IE_NN_BUILDER_2019
2020-03-03 08:07:54 +00:00
Alexander Alekhin
29d214474f dnn(IE): use HAVE_DNN_IE_NN_BUILDER_2019 for NN Builder API code
- CMake option: OPENCV_DNN_IE_NN_BUILDER_2019
2020-03-03 07:45:09 +00:00
Alexander Alekhin
f3237fdc6e Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-02-14 19:54:59 +03:00
Dmitry Kurtaev
9a4cafa319 Resolve #14566 2020-02-14 00:21:38 +03:00
Alexander Alekhin
92b9888837 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-12-12 13:02:19 +03:00
Liubov Batanina
660a709840 Support Swish and Mish activations 2019-12-06 11:27:59 +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
Manjunath Bhat
78c5e41c23 Merge pull request #15808 from thebhatman:Mish_swish
* Added Swish and Mish activations

* Fixed whitespace errors

* Kernel implementation done

* Added function for launching kernel

* Changed type of 1.0

* Attempt to add test for Swish and Mish

* Resolving type mismatch for log

* exp from device

* Use log1pexp instead of adding 1

* Added openCL kernels
2019-12-02 00:06:17 +03:00
thebhatman
8a18d132fc Port Swish and Mish layers 2019-12-01 11:55:39 +03:00
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
Alexander Alekhin
174b4ce29d Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-08-05 18:11:43 +00:00
Dmitry Kurtaev
77d4e3e8d2 Fix 2019R2 tests 2019-07-27 13:30:15 +03:00
Alexander Alekhin
b95e93c20a Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-06-26 20:19:04 +00:00
Alexander Alekhin
24790e4061
Merge pull request #14899 from alalek:dnn_fix_bnll_layer
* dnn: fix BNLLLayer implementation

details: https://github.com/BVLC/caffe/blame/1.0/src/caffe/layers/bnll_layer.cpp#L17

* dnn: enable OCV/OpenCL BNLL layer
2019-06-26 23:04:26 +03:00
Alexander Alekhin
66d7956e67 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-06-15 16:25:11 +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
4635356435 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-04-13 20:00:54 +00:00
Dmitry Kurtaev
a2bbfa1db5 Enable some tests for Inference Engine 2019R1 2019-04-12 15:21:42 +03:00
Alexander Alekhin
8bde6aea4b Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-02-19 19:49:13 +00:00
Dmitry Kurtaev
ca5976e3d4 Fix IE backend considering future changes. 2019-02-18 19:26:04 +03:00
Alexander Alekhin
631b246881 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-01-22 18:00:34 +00:00
Dmitry Kurtaev
f0ddf302b2 Move Inference Engine to new API 2019-01-17 14:28:48 +03:00
Alexander Alekhin
8f4e5c2fb8 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2018-11-26 15:37:45 +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
Alexander Alekhin
8409aa9eba Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2018-11-14 19:41:09 +00:00
catree
10b482ff1e Fix code and missing intrin header. Remove useless header. 2018-11-14 19:00:59 +01:00
WuZhiwen
6e3ea8b49d Merge pull request #12703 from wzw-intel:vkcom
* dnn: Add a Vulkan based backend

This commit adds a new backend "DNN_BACKEND_VKCOM" and a
new target "DNN_TARGET_VULKAN". VKCOM means vulkan based
computation library.

This backend uses Vulkan API and SPIR-V shaders to do
the inference computation for layers. The layer types
that implemented in DNN_BACKEND_VKCOM include:
Conv, Concat, ReLU, LRN, PriorBox, Softmax, MaxPooling,
AvePooling, Permute

This is just a beginning work for Vulkan in OpenCV DNN,
more layer types will be supported and performance
tuning is on the way.

Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>

* dnn/vulkan: Add FindVulkan.cmake to detect Vulkan SDK

In order to build dnn with Vulkan support, need installing
Vulkan SDK and setting environment variable "VULKAN_SDK" and
add "-DWITH_VULKAN=ON" to cmake command.

You can download Vulkan SDK from:
https://vulkan.lunarg.com/sdk/home#linux

For how to install, see
https://vulkan.lunarg.com/doc/sdk/latest/linux/getting_started.html
https://vulkan.lunarg.com/doc/sdk/latest/windows/getting_started.html
https://vulkan.lunarg.com/doc/sdk/latest/mac/getting_started.html
respectively for linux, windows and mac.

To run the vulkan backend, also need installing mesa driver.
On Ubuntu, use this command 'sudo apt-get install mesa-vulkan-drivers'

To test, use command '$BUILD_DIR/bin/opencv_test_dnn --gtest_filter=*VkCom*'

Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>

* dnn/Vulkan: dynamically load Vulkan runtime

No compile-time dependency on Vulkan library.
If Vulkan runtime is unavailable, fallback to CPU path.

Use environment "OPENCL_VULKAN_RUNTIME" to specify path to your
own vulkan runtime library.

Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>

* dnn/Vulkan: Add a python script to compile GLSL shaders to SPIR-V shaders

The SPIR-V shaders are in format of text-based 32-bit hexadecimal
numbers, and inserted into .cpp files as unsigned int32 array.

* dnn/Vulkan: Put Vulkan headers into 3rdparty directory and some other fixes

Vulkan header files are copied from
https://github.com/KhronosGroup/Vulkan-Docs/tree/master/include/vulkan
to 3rdparty/include

Fix the Copyright declaration issue.

Refine OpenCVDetectVulkan.cmake

* dnn/Vulkan: Add vulkan backend tests into existing ones.

Also fixed some test failures.

- Don't use bool variable as uniform for shader
- Fix dispathed group number beyond max issue
- Bypass "group > 1" convolution. This should be support in future.

* dnn/Vulkan: Fix multiple initialization in one thread.
2018-10-29 17:51:26 +03:00
Alexander Alekhin
9d02d42afe dnn(ocl4dnn): don't use getUMat()
especially in CPU only processing
2018-10-05 15:24:51 +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
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
2018-08-31 15:41:56 +03:00
Dmitry Kurtaev
3e027df583 Enable more deep learning tests using Intel's Inference Engine backend 2018-08-27 18:37:35 +03:00
Dmitry Kurtaev
2c291bc2fb Enable FastNeuralStyle and OpenFace networks with IE backend 2018-06-09 15:57:12 +03:00