Fix loading of ONNX models with Resize operation with Opset 11 for newer versions of Pytorch
* Add reproducer for Resize operation from newer versions of Pytorch
* Fix loading of scales parameter for Resize layer
* Change check type for better diagnostic messages
Fix KD Tree kNN Implementation
* Make KDTree mode in kNN functional
remove docs and revert change
Make KDTree mode in kNN functional
spacing
Make KDTree mode in kNN functional
fix window compilations warnings
Make KDTree mode in kNN functional
fix window compilations warnings
Make KDTree mode in kNN functional
casting
Make KDTree mode in kNN functional
formatting
Make KDTree mode in kNN functional
* test coding style
Bit exact gaussian blur for 16bit unsigned int
* bit-exact gaussian kernel for CV_16U
* SIMD optimization
* template GaussianBlurFixedPoint
* remove template specialization
* simd support for h3N121 uint16
* test for u16 gaussian blur
* remove unnecessary comments
* fix return type of raw()
* add typedef of native internal type in fixedpoint
* update return type of raw()
Bit-exact Nearest Neighbor Resizing
* bit exact resizeNN
* change the value of method enum
* add bitexact-nn to ResizeExactTest
* test to compare with non-exact version
* add perf for bit-exact resizenn
* use cvFloor-equivalent
* 1/3 scaling is not stable for floating calculation
* stricter test
* bugfix: broken data in case of 6 or 12bytes elements
* bugfix: broken data in default pix_size
* stricter threshold
* use raw() for floor
* use double instead of int
* follow code reviews
* fewer cases in perf test
* center pixel convention
* Fix ONNX loading in issues opencv#17516, opencv#17531
* Add tests for Linear and Matmul layers
* Disable tests for IE versions lower than 20.4
* Skip unstable tests with OpenCL FP16 on Intel GPU
* Add correct test filtering for OpenCL FP16 tests
- OpenCL kernel cleanup processing is asynchronous and can be called even after forced clFinish()
- buffers are released later in asynchronous mode
- silence these false positive cases for asynchronous cleanup
reformatting
Improve initialization performance of Brisk
fix formatting
Improve initialization performance of Brisk
formatting
Improve initialization performance of Brisk
make a lookup table for ring
use cosine/sine lookup table for theta in brisk and utilize trig identity
fix ring lookup table
use cosine/sine lookup table for theta in brisk and utilize trig identity
formatting
use cosine/sine lookup table for theta in brisk and utilize trig identity
move scale radius product to ring loop to ensure it's not recomputed for each rot
revert change
move scale radius product to ring loop to ensure it's not recomputed for each rot
remove rings lookup table
move scale radius product to ring loop to ensure it's not recomputed for each rot
fix formatting of for loop
move scale radius product to ring loop to ensure it's not recomputed for each rot
use sine/cosine approximations for brisk lookup table.
add documentation for sine/cosine lookup tables
Improve initialization performance of BRISK
* 8-bit SIFT descriptors
* use clearer parameter
* update docs
* propagate type info
* overload function for avoiding ABI-break
* bugfix: some values are undefined when CV_SIMD is absent
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
* hopefully, eliminated compile warnings, errors, as well as failure in one test
* * fixed a few typos
* decreased buffer size in some cases
* added more optimal im2row branch in the case of 1x1 convolutions
* tuned fastConv to reduce the number of passes over arrays
backport of commit 77b01deb80
add relu option
add relu as activation option in darknet
simplify the setParams if-else ladder
add relu as activation option in darknet
correct activation_param type
format
format
add relu as activation option in darknet
spacing
spacing
add relu as activation option in darknet
* Possibility to set more than one tree for the hierarchical KMeans (default is still 1 tree).
This particularly improves NN retrieval results with binary vectors, allowing better quality
compared to LSH for similar processing time when speed is the criterium.
* Add explanations on the FLANN's hierarchical KMeans for binary data.
DNN: OpenCL/slice update
* dnn(ocl/slice): make slice kernel VTune friendly
- more unique names
- inline code of copy functions
* dnn(ocl/slice): prefer to spawn more work groups
- even in case with 1D copy
- perf improvement up to 2x of kernel time (due to changed configuration 128x1x1 => 128x32x1)
* dnn(ocl/slice): cache kernel exec info
* Implement ASIFT in C++
* '>>' should be '> >' within a nested template
* add a sample for asift usage
* bugfix empty keypoints cause crash
* simpler initialization for mask
* suppress the number of lines
* correct tex document
* type casting
* add descriptorsize for asift
* smaller testdata for asift
* more smaller test data
* add OpenCV short license header
libjasper has recently changed `jas_matrix_get` from a macro to an inline function
(389951d071 in https://github.com/jasper-software/jasper), causing the build to fail.
- Added test for automated rotation for MP4 videos with metadata
- Fix 180 degrees rotation bug
- Moved rotation logic to cv::VideoCapture implementation for FFmpeg and restore binary compatibility with FFmpeg wrapper.
- Add VideoCapture camera orientation property for mp4 videos with camera orientation meta.
- Add auto rotation for 90, 180, 270 degrees using cv::rotate
Pev binary kmeans
* Ongoing work transposing kmeans clustering method for bitfields: the computeClustering method
Ongoing work transposing kmeans clustering method for bitfields: interface computeBitfieldClustering
Fix genericity of computeNodeStatistics
Ongoing work transposing kmeans clustering method for bitfields: adapt computeNodeStatistics()
Ongoing work transposing kmeans clustering method for bitfields: adapt findNN() method
Ongoing work transposing kmeans clustering method for bitfields: allow kmeans with Hamming distance
Ongoing work transposing kmeans clustering method for bitfields: adapt distances code
Ongoing work transposing kmeans clustering method for bitfields: adapt load/save code
Ongoing work transposing kmeans clustering method for bitfields: adapt kmeans hierarchicalClustring()
PivotType -> CentersType Renaming
Fix type casting for ARM SIMD implementation of Hamming
Fix warnings with Win32 compilation
Fix warnings with Win64 compilation
Fix wrong parenthesis position on rounding
* Ensure proper rounding when CentersType is integral
double area = moms.m00;
is same as
double area = contourArea(contours[contourIdx]);
Not to mention
"moms" already calculated here,"contourArea" should not apply
* Clean: replace C style asserts by CV_Assert and CV_DbgAssert
* Try fixing warning on Windows compilation
* Another way trying to fix warnings on Win
* Fixing warnings with some compilers:
Some compilers warn on systematic exit preventing to execute the code that follows.
This is why assert(0) that exits only in debug was working, but not CV_Assert or CV_Error
that exit both in release and debug, even if with different behavior.
In addition, other compilers complain when return 0 is removed from getKey(),
even if before we have a statement leading to systematic exit.
* Disable "unreachable code" warnings for Win compilers so we can use proper CV_Error
Before, when maxCheck was reached in the first descent of a tree, time was still wasted parsing
the next trees till their best leaves whose points were not used at all.
Clarify component statistics documentation
* Change ConnectedComponentsTypes documentation
Change from "algorithm output formats" to "statistics" because it specifies types of statistics, not formats.
* Documentation: clarify component statistics
Explain that ConnectedComponentTypes selects a statistic.
Argument "a" is of type ElementType* that is either int* or float*, while b was double*.
Mixing types prevents the possibility to use SSE or AVX instructions.
On implementation without SIMD instructions, this doesn't show any impact on performance.
* Clean: make the use of the indices array length consistent
Either we don't want this method to be used in the future for any other node
than the root node, and so we replace indices_length by size_ and remove it as
argument, or we want to be able to use it potentially for other nodes, and
so using size_ instead of indices_length would have lead to a bug.
* Fix: b was not an address
* Fix: transpose the Flann repo commit "Fixes in accum_dist methods" from Adil Ibragimov
Avoids trying to compute log(ratio) with ratio = 0
* Fix: transpose the Flann repo commit "result_set bugfix" from Jack Rae
* Fix Jack Rae commit as the initial i - 1 index was decremented before entering the loop body
* Clean: transpose the Flann repo commit "Updated comments in lsh_index" from Richard McPherson
* Fix: Transpose the Flann repo commit "Fixing unreachable code in lsh_table.h" from hypevr
* Fix warning the same way it was done in flann standalone repo
* Change the return value in case of unsupported type
Instead of using the current dimension for which we just got a big span,
we were computing Min and Max for the previous dimension stored in cutfeat
(and using 0 instead of the dimension indice for the very first dimension
with "span > (1-eps)max_span")
* Add documentation about usage of cv2eigen functions in eigen.hpp
* Fixed Doxygen syntax.
Co-authored-by: Alexander Smorkalov <smorkalov.a.m@gmail.com>
* improved fitEllipse and fitEllipseDirect accuracy in singular or close-to-singular cases (see issue #9923)
* scale points using double precision
* added normalization to fitEllipseAMS as well; fixed Java test case by raising the tolerance (it's unclear what is the correct result in this case).
* improved point perturbation a bit. make the code a little bit more clear
* trying to fix Java fitEllipseTest by slightly raising the tolerance threshold
* synchronized C++ version of Java's fitEllipse test
* removed trailing whitespaces
* fixed#17044
1. fixed Python part of the tutorial about using OpenCV XML-YAML-JSON I/O functionality from C++ and Python.
2. added startWriteStruct() and endWriteStruct() methods to FileStorage
3. modifed FileStorage::write() methods to make them work well inside sequences, not only mappings.
* try to fix the doc builder
* added Python regression test for FileStorage I/O API ([TODO] iterating through long sequences can be very slow)
* fixed yaml testing
Fix Test Case: in latest version, window.cv is a promise instance that makes most test case failed.
* Fix Browser Test Case: In latest version, window.cv is a promise instance
In latest version of opencv.js, window.cv is promise instance.
So that most of the test cases is run failed.
This commit is to fix browser test case.
* Add comment for backward compatible
Add comments for backward compatible