During the cluster-based detection of circle grids, the detected circle
pattern has to be mapped to 3D-points. When doing this the width (i.e.
more circles) and height (i.e. less circles) of the pattern need to
be identified in image coordinates.
Until now this was done by assuming that the shorter side in image
coordinates (length in pixels) corresponds to the height in 3D.
This assumption does not hold if we look at the pattern from
a perspective where the projection of the width is shorter
than the projection of the height. This in turn lead to misdetections in
although the circle pattern was clearly visible.
Instead count how many circles have been detected along two edges of the
projected quadrangle and use the one with more circles as width and the
one with less as height.
* integrated the new C++ persistence; removed old persistence; most of OpenCV compiles fine! the tests have not been run yet
* fixed multiple bugs in the new C++ persistence
* fixed raw size of the parsed empty sequences
* [temporarily] excluded obsolete applications traincascade and createsamples from build
* fixed several compiler warnings and multiple test failures
* undo changes in cocoa window rendering (that was fixed in another PR)
* fixed more compile warnings and the remaining test failures (hopefully)
* trying to fix the last little warning
* Fix reading of black-and-white (thresholded) TIFF images
I recently updated my local OpenCV version to 3.4.3 and found out that
I could not read my TIFF images related to my project. After debugging I
found out that there has been some static analysis fixes made
that accidentally have broken reading those black-and-white TIFF images.
Commit hash in which reading of mentioned TIFF images has been broken:
cbb1e867e5
Basically the fix is to revert back to the same functionality that has been there before,
when black-and-white images are read bpp (bitspersample) is 1.
Without the case 1: this TiffDecoder::readHeader() function always return false.
* Added type and default error message
* Added stdexcept include
* Use CV_Error instead of throw std::runtime_error
* imgcodecs(test): add TIFF B/W decoding tests
G-API: Introduce new `reshape()` API (#12990)
* Moved initFluidUnits, initLineConsumption, calcLatency, calcSkew to separate functions
* Added Fluid::View::allocate method (moved allocation logic from constructor)
* Changed util::zip to util::indexed, utilized collectInputMeta in GFluidExecutable constructor
* Added makeReshape method to FluidExecutable
* Removed m_outputRoi from GFluidExecutable
* Added reshape feature
* Added switch of resize mapper if agent ratio was changed
* Added more TODOs and renamed a function
* G-API reshape(): add missing `override` specifiers
Fix warnings on all platforms
Made scale parameter optional for mul kernel wrapper (#12949)
* Added missed operator*(GMat, GMat). Made scale parameter optional for mul kernel.
* Fixed perf test for mul(GMat, GMat) kernel
* Removed operator*(GMat, GMat) as not needed
* RGB2RGB initially rewritten
* NEON impl removed
* templated version added for ushort, float
* data copying allowed for RGB2RGB
* inplace processing fixed
* fields to local vars
* no zeroupper until it's fixed
* vx_cleanup() added back
- initialize arithmetic dispatcher
- add new universal intrinsic v_absdiffs
- add new universal intrinsic v_pack_b
- add accumulate version of universal intrinsic v_round
- fix sse/avx2:uint8 multiplication overflow
- reimplement arithmetic, logic and comparison operations into wide universal intrinsics
with full support for all types
- reimplement IPP arithmetic, logic and comparison operations in a sperate file arithm_ipp.hpp
- avoid scalar multiplication if scaling factor eq 1 and use integer multiplication
- move C arithmetic operations to precomp.hpp and delete [arithm_simd|arithm_core].hpp
- add compatibility with new opencv4 divide policy
* 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.htmlhttps://vulkan.lunarg.com/doc/sdk/latest/windows/getting_started.htmlhttps://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.
This is a fix to the signature of static function
collectCalibrationData() and clean-up for #12772. Since fallback scheme
in calibration method selection is not used anymore. As an input
parameter, iFixedPoint should be passed by value according to the OpenCV
coding style guide.
* Renamed Sobel operator GAPI kernel to match with OpenCV naming rules
* Fixed perf tests
* Small refactoring to check CI issue
* Refactored alignment for kernel wrappers in imgproc.hpp
* Update videoio.hpp
add VideoCapturePropertie for clossbar input pin setting
* Update cap_dshow.cpp
For some kind of capture card, such as "avermedia cv710 " , it use SerialDigital as input pin and so it can not work.
Here added new PhysicalConnectorType enumeration: PhysConn_Video_YRYBY and PhysConn_Video_SerialDigital to support it.
And also provide new property parameter CAP_CROSSBAR_INPIN_TYPE to set the crossbar input pin type which will be used in videoInput::start(int deviceID, videoDevice *VD):
" if(VD->useCrossbar)
{
DebugPrintOut("SETUP: Checking crossbar\n");
routeCrossbar(&VD->pCaptureGraph, &VD->pVideoInputFilter, VD->connection, CAPTURE_MODE);
}
"
And at last ,fixed one issue for function setSizeAndSubtype, added code
pVih->rcSource.top = pVih->rcSource.left = pVih->rcTarget.top =pVih->rcTarget.left=0;
pVih->rcSource.right = pVih->rcTarget.right= attemptWidth;
pVih->rcSource.bottom = pVih->rcTarget.bottom = attemptHeight;
without these code , rcSource and rcTarget will keeping use default resolution and cause fail in hr = VD->streamConf->SetFormat(VD->pAmMediaType) and cannot find suitable MediaType.
Tested with python3 and mfc (Avermedia cv710)
Python3 code:
import cv2
print("test cv")
cap=cv2.VideoCapture(0)
cap.set(5,60)
cap.set(3,1920)
cap.set(4,1080)
cap.set(31,6)
ret,img=cap.read()
cv2.namedWindow("cap",cv2.WINDOW_NORMAL)
cv2.resizeWindow("cap",960,640);
while True:
ret,img=cap.read()
if ret==False:
continue
cv2.imshow("cap",img)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
MFC code:
void CcvtestDlg::OnBnClickedButton1()
{
VideoCapture cap(0);
cap.set(CAP_PROP_FRAME_WIDTH, 1920);
cap.set(CAP_PROP_FRAME_HEIGHT, 1080);
cap.set(CAP_CROSSBAR_INPIN_TYPE , 6);
Mat img;
namedWindow("test", WINDOW_NORMAL);
resizeWindow("test", 960, 640);
while (1)
{
if (cap.read(img))
{
imshow("test", img);
if ('q' ==waitKey(1))
break;
}
}
destroyAllWindows();
cap.release();
}
* Update cap_dshow.cpp
* Update videoio.hpp
move enum value of CAP_CROSSBAR_INPIN_TYPE to the end of list
* Update videoio.hpp
* Update cap_dshow.cpp
removed trailing whitespace
* Update test_camera.cpp
Add test for capture device using PhysConn_Video_SerialDigital as crossbar input pin
* Update test_camera.cpp
Correction of misunderstanding about how to add test case.
More accurate pinhole camera calibration with imperfect planar target (#12772)
43 commits:
* Add derivatives with respect to object points
Add an output parameter to calculate derivatives of image points with
respect to 3D coordinates of object points. The output jacobian matrix
is a 2Nx3N matrix where N is the number of points.
This commit introduces incompatibility to old function signature.
* Set zero for dpdo matrix before using
dpdo is a sparse matrix with only non-zero value close to major
diagonal. Set it to zero because only elements near major diagonal are
computed.
* Add jacobian columns to projectPoints()
The output jacobian matrix of derivatives with respect to coordinates of
3D object points are added. This might break callers who assume the
columns of jacobian matrix.
* Adapt test code to updated project functions
The test cases for projectPoints() and cvProjectPoints2() are updated to
fit new function signatures.
* Add accuracy test code for dpdo
* Add badarg test for dpdo
* Add new enum item for new calibration method
CALIB_RELEASE_OBJECT is used to whether to release 3D coordinates of
object points. The method was proposed in: K. H. Strobl and G. Hirzinger.
"More Accurate Pinhole Camera Calibration with Imperfect Planar Target".
In Proceedings of the IEEE International Conference on Computer Vision
(ICCV 2011), 1st IEEE Workshop on Challenges and Opportunities in Robot
Perception, Barcelona, Spain, pp. 1068-1075, November 2011.
* Add releasing object method into internal function
It's a simple extension of the standard calibration scheme. We choose to
fix the first and last object point and a user-selected fixed point.
* Add interfaces for extended calibration method
* Refine document for calibrateCamera()
When releasing object points, only the z coordinates of the
objectPoints[0].back is fixed.
* Add link to strobl2011iccv paper
* Improve documentation for calibrateCamera()
* Add implementations of wrapping calibrateCamera()
* Add checking for params of new calibration method
If input parameters are not qualified, then fall back to standard
calibration method.
* Add camera calibration method of releasing object
The current implementation is equal to or better than
https://github.com/xoox/calibrel
* Update doc for CALIB_RELEASE_OBJECT
CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with
potentially less precise and less stable in some rare cases.
* Add RELEASE_OBJECT calibration to tutorial code
To select the calibration method of releasing object points, a command
line parameter `-d=<number>` should be provided.
* Update tutorial doc for camera_calibration
If the method of releasing object points is merged into OpenCV. It will
be expected to be firstly released in 4.1, I think.
* Reduce epsilon for cornerSubPix()
Epsilon of 0.1 is a bigger one. Preciser corner positions are required
with calibration method of releasing object.
* Refine camera calibration tutorial
The hypothesis coordinates are used to indicate which distance must be
measured between two specified object points.
* Update sample calibration code method selection
Similar to camera_calibration tutorial application, a command line
argument `-dt=<number>` is used to select the calibration method.
* Add guard to flags of cvCalibrateCamera2()
cvCalibrateCamera2() doesn't accept CALIB_RELEASE_OBJECT unless overload
interface is added in the future.
* Simplify fallback when iFixedPoint is out of range
* Refactor projectPoints() to keep compatibilities
* Fix arg string "Bad rvecs header"
* Read calibration flags from test data files
Instead of being hard coded into source file, the calibration flags will
be read from test data files.
opencv_extra/testdata/cv/cameracalibration/calib?.dat must be sync with
the test code.
* Add new C interface of cvCalibrateCamera4()
With this new added C interface, the extended calibration method with
CALIB_RELEASE_OBJECT can be called by C API.
* Add regression test of extended calibration method
It has been tested with new added test data in xoox:calib-release-object
branch of opencv_extra.
* Fix assertion in test_cameracalibration.cpp
The total number of refined 3D object coordinates is checked.
* Add checker for iFixedPoint in cvCalibrateCamera4
If iFixedPoint is out of rational range, fall back to standard method.
* Fix documentation for overloaded calibrateCamera()
* Remove calibration flag of CALIB_RELEASE_OBJECT
The method selection is based on the range of the index of fixed point.
For minus values, standard calibration method will be chosen. Values in
a rational range will make the object-releasing calibration method
selected.
* Use new interfaces instead of function overload
Existing interfaces are preserved and new interfaces are added. Since
most part of the code base are shared, calibrateCamera() is now a
wrapper function of calibrateCameraRO().
* Fix exported name of calibrateCameraRO()
* Update documentation for calibrateCameraRO()
The circumstances where this method is mostly helpful are described.
* Add note on the rigidity of the calibration target
* Update documentation for calibrateCameraRO()
It is clarified that iFixedPoint is used as a switch to select
calibration method. If input data are not qualified, exceptions will be
thrown instead of fallback scheme.
* Clarify iFixedPoint as switch and remove fallback
iFixedPoint is now used as a switch for calibration method selection. No
fallback scheme is utilized anymore. If the input data are not
qualified, exceptions will be thrown.
* Add badarg test for object-releasing method
* Fix document format of sample list
List items of same level should be indented the same way. Otherwise they
will be formatted as nested lists by Doxygen.
* Add brief intro for objectPoints and imagePoints
* Sync tutorial to sample calibration code
* Update tutorial compatibility version to 4.0
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