[teset data in opencv_extra](https://github.com/opencv/opencv_extra/pull/1016)
NanoTrack is an extremely lightweight and fast object-tracking model.
The total size is **1.1 MB**.
And the FPS on M1 chip is **150**, on Raspberry Pi 4 is about **30**. (Float32 CPU only)
With this model, many users can run object tracking on the edge device.
The author of NanoTrack is @HonglinChu.
The original repo is https://github.com/HonglinChu/NanoTrack.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
* cmake: Fix DirectX detection in mingw
The pragma comment directive is valid for MSVC only. So, the DirectX detection
fails in mingw. The failure is fixed by adding the required linking library
(here d3d11) in the try_compile() function in OpenCVDetectDirectX.cmake file.
Also add a message if the first DirectX check fails.
* gapi: Fix compilation with mingw
These changes remove MSVC specific pragma directive. The compilation fails at
linking time due to absence of proper linking library. The required libraries
are added in corresponding CMakeLists.txt file.
* samples: Fix compilation with mingw
These changes remove MSVC specific pragma directive. The compilation fails at
linking time due to absence of proper linking library. The required libraries
are added in corresponding CMakeLists.txt file.
Add -imshow-scale flag to resize the image when displaying the results.
Add -enable-k3 flag to enable or disable the estimation of the K3 distortion coefficient.
Add flags to set the camera intrinsic parameters as an initial guess (can allow converging to the correct camera intrinsic parameters).
Add -imshow-scale flag to resize the image when displaying the results.
Add -enable-k3 flag to enable or disable the estimation of the K3 distortion coefficient.
* videoio: add support for obsensor (Orbbec RGB-D Camera )
* obsensor: code format issues fixed and some code optimized
* obsensor: fix typo and format issues
* obsensor: fix crosses initialization error
Replaced sprintf with safer snprintf
* Straightforward replacement of sprintf with safer snprintf
* Trickier replacement of sprintf with safer snprintf
Some functions were changed to take another parameter: the size of the buffer, so that they can pass that size on to snprintf.
### Critical bugs fixed:
- `seam_finder.find()` returns None and overwrites `masks_warped`
- `indices` is only 1-dimensional
### Nice-to-have bugs fixed:
- avoid invalid value in sqrt and subsequent runtime warning
- avoid printing help string on each run (use argparse builtin behavior)
### New features:
- added graphcut seam finder support
### Test Summary:
Tested on Ubuntu 20.04 with python 3.8.10 and opencv-python-contrib 4.5.5.62
there is a recent change, how `std::vector<int>` is wrapped in python,
it used to be a 2d array (requirig that weird `[0]` indexing), now it is only 1d
fix cvtColor-error
* fix gray image channel error
* fix gray image channel error
* fix cvtColor error after the video end
* fix cvtColor error after the video end and change next variable
* fix cvtColor error after the video end
* reset next variable
* fix cvtColor error after the video end
* fix cvtColor error after the video end
Avoid `SyntaxWarning` on Python >= 3.8
```
>>> "convolutional" == "convolutional"
True
>>> "convolutional" is "convolutional"
<stdin>:1: SyntaxWarning: "is" with a literal. Did you mean "=="?
True
```
Related to #21121
[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
Add DNN-based face detection and face recognition into modules/objdetect
* Add DNN-based face detector impl and interface
* Add a sample for DNN-based face detector
* add recog
* add notes
* move samples from samples/cpp to samples/dnn
* add documentation for dnn_face
* add set/get methods for input size, nms & score threshold and topk
* remove the DNN prefix from the face detector and face recognizer
* remove default values in the constructor of impl
* regenerate priors after setting input size
* two filenames for readnet
* Update face.hpp
* Update face_recognize.cpp
* Update face_match.cpp
* Update face.hpp
* Update face_recognize.cpp
* Update face_match.cpp
* Update face_recognize.cpp
* Update dnn_face.markdown
* Update dnn_face.markdown
* Update face.hpp
* Update dnn_face.markdown
* add regression test for face detection
* remove underscore prefix; fix warnings
* add reference & acknowledgement for face detection
* Update dnn_face.markdown
* Update dnn_face.markdown
* Update ts.hpp
* Update test_face.cpp
* Update face_match.cpp
* fix a compile error for python interface; add python examples for face detection and recognition
* Major changes for Vadim's comments:
* Replace class name FaceDetector with FaceDetectorYN in related failes
* Declare local mat before loop in modules/objdetect/src/face_detect.cpp
* Make input image and save flag optional in samples/dnn/face_detect(.cpp, .py)
* Add camera support in samples/dnn/face_detect(.cpp, .py)
* correct file paths for regression test
* fix convertion warnings; remove extra spaces
* update face_recog
* Update dnn_face.markdown
* Fix warnings and errors for the default CI reports:
* Remove trailing white spaces and extra new lines.
* Fix convertion warnings for windows and iOS.
* Add braces around initialization of subobjects.
* Fix warnings and errors for the default CI systems:
* Add prefix 'FR_' for each value name in enum DisType to solve the
redefinition error for iOS compilation; Modify other code accordingly
* Add bookmark '#tutorial_dnn_face' to solve warnings from doxygen
* Correct documentations to solve warnings from doxygen
* update FaceRecognizerSF
* Fix the error for CI to find ONNX models correctly
* add suffix f to float assignments
* add backend & target options for initializing face recognizer
* add checkeq for checking input size and preset size
* update test and threshold
* changes in response to alalek's comments:
* fix typos in samples/dnn/face_match.py
* import numpy before importing cv2
* add documentation to .setInputSize()
* remove extra include in face_recognize.cpp
* fix some bugs
* Update dnn_face.markdown
* update thresholds; remove useless code
* add time suffix to YuNet filename in test
* objdetect: update test code
Tutorial for parallel_for_ and Universal Intrinsic (GSoC '21)
* New parallel_for tutorial
* Universal Intrinsics Draft Tutorial
* Added draft of universal intrinsic tutorial
* * Added final markdown for parallel_for_new
* Added first half of universal intrinsic tutorial
* Fixed warnings in documentation and sample code for parallel_for_new
tutorial
* Restored original parallel_for_ tutorial and table_of_content_core
* Minor changes
* Added demonstration of 1-D vectorized convolution
* * Added 2-D convolution implementation and tutorial
* Minor changes in vectorized implementation of 1-D and 2-D convolution
* Minor changes to univ_intrin tutorial. Added new tutorials to the table of contents
* Minor changes
* Removed variable sized array initializations
* Fixed conversion warnings
* Added doxygen references, minor fixes
* Added jpg image for parallel_for_ doc
AArch64 semihosting
* [ts] Disable filesystem support in the TS module.
Because of this change, all the tests loading data will file, but tat
least the core module can be tested with the following line:
opencv_test_core --gtest_filter=-"*Core_InputOutput*:*Core_globbing.accuracy*"
* [aarch64] Build OpenCV for AArch64 semihosting.
This patch provide a toolchain file that allows to build the library
for semihosting applications [1]. Minimal changes have been applied to
the code to be able to compile with a baremetal toolchain.
[1] https://developer.arm.com/documentation/100863/latest
The option `CV_SEMIHOSTING` is used to guard the bits in the code that
are specific to the target.
To build the code:
cmake ../opencv/ \
-DCMAKE_TOOLCHAIN_FILE=../opencv/platforms/semihosting/aarch64-semihosting.toolchain.cmake \
-DSEMIHOSTING_TOOLCHAIN_PATH=/path/to/baremetal-toolchain/bin/ \
-DBUILD_EXAMPLES=ON -GNinja
A barematel toolchain for targeting aarch64 semihosting can be found
at [2], under `aarch64-none-elf`.
[2] https://developer.arm.com/tools-and-software/open-source-software/developer-tools/gnu-toolchain/gnu-a/downloads
The folder `samples/semihosting` provides two example semihosting
applications.
The two binaries can be executed on the host platform with:
qemu-aarch64 ./bin/example_semihosting_histogram
qemu-aarch64 ./bin/example_semihosting_norm
Similarly, the test and perf executables of the modules can be run
with:
qemu-aarch64 ./bin/opecv_[test|perf]_<module>
Notice that filesystem support is disabled by the toolchain file,
hence some of the test that depend on filesystem support will fail.
* [semihosting] Remove blank like at the end of file. [NFC]
The spurious blankline was reported by
https://pullrequest.opencv.org/buildbot/builders/precommit_docs/builds/31158.
* [semihosting] Make the raw pixel file generation OS independent.
Use the facilities provided by Cmake to generate the header file
instead of a shell script, so that the build doesn't fail on systems
that do not have a unix shell.
* [semihosting] Rename variable for semihosting compilation.
* [semihosting] Move the cmake configuration to a variable file.
* [semihosting] Make the guard macro private for the core module.
* [semihosting] Remove space. [NFC]
* [semihosting] Improve comment with information about semihosting. [NFC]
* [semihosting] Update license statement on top of sourvce file. [NFC]
* [semihosting] Replace BM_SUFFIX with SEMIHOSTING_SUFFIX. [NFC]
* [semihosting] Remove double space. [NFC]
* [semihosting] Add some text output to the sample applications.
* [semihosting] Remove duplicate entry in cmake configuration. [NFCI]
* [semihosting] Replace `long` with `int` in sample apps. [NFCI]
* [semihosting] Use `configure_file` to create the random pixels. [NFCI]
* [semihosting][bugfix] Fix name of cmakedefine variable.
* [semihosting][samples] Use CV_8UC1 for grayscale images. [NFCI]
* [semihosting] Add readme file.
* [semihosting] Remove blank like at the end of README. [NFC]
This fixes the failure at
https://pullrequest.opencv.org/buildbot/builders/precommit_docs/builds/31272.
without rounding the composed image sizes (variable "sz") they will be odly fractions of a pixel (e.g. (5300.965, 3772.897)) and therefore cause a "TypeError: integer argument expected, got float" in line
456 roi = warper.warpRoi(sz, K, cameras[i].R)
* Added PaddlePaddle classification model conversion case
* Modify cv2 import as cv
* Modify documents in dnn_conversion/paddlepaddle
* Modify documents in dnn_conversion/paddlepaddle
Stitching Detailed Tutorial Improvements
* Add Vertical Wave Correction
The user has the possibility to pass "vert" as wave_correct parameter. However, in the code "cv.detail.WAVE_CORRECT_HORIZ" ist fixed. This change proposes changes so that the wave correction is done vertically if the user passes "vert" as wave_correct parameter. The variable "do_wave_correct" is replaced by None which is passed to the variable "wave_correct" if the user chooses "no" for wave correction.
* Correct fixed conf_thresh
According to the documentation, [cv.detail.leaveBiggestComponent](https://docs.opencv.org/4.5.1/d7/d74/group__stitching__rotation.html#ga855d2fccbcfc3b3477b34d415be5e786) takes features, the pairwise_matches and the conf_threshold as input.
In the tutorial, however, conf_threshold is fixed at 0.3 even though the user can pass conf_thresh as parameter which is 1 by default. Fixing this parameter at 0.3 causes the script to include images into the panorama which are not part of it.
* Error Message for SURF if not implemented
In OpenCV 4.5.1
import cv2 as cv
cv.xfeatures2d_SURF.create
will not create an AttributeError, even if the function is excluded (no nonfree option)
In Line 305 (now 306) however ´finder = FEATURES_FIND_CHOICES[args.features]()´ will raise an
error: OpenCV(4.5.1) ..\opencv_contrib\modules\xfeatures2d\src\surf.cpp:1029: error: (-213:The function/feature is not implemented) This algorithm is patented and is excluded in this configuration; Set OPENCV_ENABLE_NONFREE CMake option and rebuild the library in function 'cv::xfeatures2d::SURF::create'
So we should check with cv.xfeatures2d_SURF.create() correctly if SURF is available
videoio: HW decode/encode in FFMPEG backend; new properties with support in FFMPEG/GST/MSMF
* HW acceleration in FFMPEG backend
* fixes on Windows, remove D3D9
* HW acceleration in FFMPEG backend
* fixes on Windows, remove D3D9
* improve va test
* Copyright
* check LIBAVUTIL_BUILD >= AV_VERSION_INT(55, 78, 100) // FFMPEG 3.4+
* CAP_MSMF test on .mp4
* .mp4 in test
* improve va test
* Copyright
* check LIBAVUTIL_BUILD >= AV_VERSION_INT(55, 78, 100) // FFMPEG 3.4+
* CAP_MSMF test on .mp4
* .mp4 in test
* .avi for GStreamer test
* revert changes around seek()
* cv_writer_open_with_params
* params.warnUnusedParameters
* VideoCaptureParameters in GStreamer
* open_with_params
* params->getUnused
* Reduce PSNR threshold 33->32 (other tests use 30)
* require FFMPEG 4.0+; PSNR 30 as in other tests
* GStreamer AVI-demux plugin not installed in Ubuntu test environment?
* fix build on very old ffmpeg
* fix build on very old ffmpeg
* fix build issues
* fix build issues (static_cast)
* FFMPEG built on Windows without H264 encoder?
* fix for write_nothing test on VAAPI
* fix warnings
* fix cv_writer_get_prop in plugins
* use avcodec_get_hw_frames_parameters; more robust fallback to SW codecs
* internal function hw_check_device() for device check/logging
* two separate tests for HW read and write
* image size 640x480 in encode test
* WITH_VA=ON (only .h headers used in OpenCV, no linkage dependency)
* exception on VP9 SW encoder?
* rebase master; refine info message
* videoio: fix FFmpeg standalone plugin build
* videoio(ffmpeg): eliminate MSVC build warnings
* address review comments
* videoio(hw): update videocapture_acceleration.read test
- remove parallel decoding by SW code path
- check PSNR against the original generated image
* videoio: minor fixes
* videoio(test): disable unsupported MSMF cases (SW and HW)
* videoio(test): update PSNR thresholds for HW acceleration read
* videoio(test): update debug messages
* "hw_acceleration" whitelisting parameter
* little optimization in test
* D3D11VA supports decoders, doesn't support encoders
* videoio(test): adjust PSNR threshold in write_read_position tests
* videoio(ffmpeg): fix rejecting on acceleration device name mismatch
* videoio(ffmpeg): fix compilation USE_AV_HW_CODECS=0, add more debug logging
* videoio: rework VideoAccelerationType behavior
- enum is not a bitset
- default value is backend specific
- only '_NONE' and '_ANY' may fallback on software processing
- specific H/W acceleration doesn't fallback on software processing. It fails if there is no support for specified H/W acceleration.
* videoio(test): fix for current FFmpeg wrapper
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
