V4L (V4L2): Refactoring. Added missed camera properties. Fixed getting `INF` for some properties. Singlethread as always (#12893)
* cap_v4l:
1 Added cap_properties verbalization.
2 Set Get of properties elementary refactoring.
3 Removed converting parameters to/from [0,1] range.
4 Added all known conversion from V4L2_CID_* to CV_CAP_PROP_*
* cap_v4l:
1. Removed all query for parameters range.
2. Refactored capture initialization.
3. Added selecting input channel by CV_CAP_PROP_MODE. Default value -1 the channels not changed.
* cap_v4l:
1. Refactoring of Convert To RGB
* cap_v4l:
1. Fixed use of video buffer index.
2. Removed extra memcopy for grab image.
3. Removed device closing from autosetup_capture_mode_v4l2
* cap_v4l:
1. The `goto` was eliminated
2. Fixed use of temporary buffer index for V4L2_PIX_FMT_SN9C10X
3. Fixed use of the bufferIndex
4. Removed trailing spaces and unused variables.
* cap_v4l:
1. Alias for capture->buffers[capture->bufferIndex]
2. Reduced size of data for memcpy: bytesused instead of length
3. Refactoring. Code duplication. More info for debug
* cap_v4l:
1. Added the ability to grab and retrieveFrame independently several times
* cap_v4l:
1. Not need to close/open device for new capture parameters applying.
2. Removed using of device name as a flag that the capture is closed. Added sufficient function.
3. Refactoring. Added requestBuffers and createBuffers
* cap_v4l:
1. Added tryIoctl with `select` like was in mainloop_v4l2.
2. Fixed buffer request for device without closing the device.
3. Some static function moved to CvCaptureCAM_V4L
4. Removed unused defines
* cap_v4l:
1. Thread-safe now
* cap_v4l:
1. Fixed thread-safe destructor
2. Fixed FPS setting
* Missed brake
* Removed thread-safety
* cap_v4l:
1. Reverted conversion parameters to/from [0,1] by default for backward compatibility.
2. Added setting for turn off compatibility mode: set CV_CAP_PROP_MODE to 65536
3. Most static functions moved to CvCaptureCAM_V4L
4. Refactoring of icvRetrieveFrameCAM_V4L and using of frame_allocated flag
* cap_v4l:
1. Added conversion to RGB from NV12, NV21
2. Refactoring. Removed wrappers for known format conversions.
* Added `CAP_PROP_CHANNEL` to the enum VideoCaptureProperties.
CAP_V4L migrated to use VideoCaptureProperties.
* 1. Update comments.
2. Environment variable `OPENCV_VIDEOIO_V4L_RANGE_NORMALIZED` for setting default backward compatibility mode.
3. Revert getting of `CAP_PROP_MODE` as fourcc code in backward compatibility mode.
* videoio: update cap_v4l - compatibilityMode => normalizePropRange
* videoio(test): V4L2 MJPEG test
`v4l2-ctl --list-formats` should have 'MJPG' entry
* videoio: fix buffer initialization
to avoid "munmap: Invalid argument" messages
* Updated boxFilter implementations to use wide universal intrinsics
* boxFilter implementation moved to separate file
* Replaced ROUNDUP macro with roundUp() function
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.
* 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
* 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
"as opposed to" is a phrase of opposed meaning distinguished from or in contrast with. e.g., "an approach that is theoretical as opposed to practical"
synonyms: in contrast with, as against, as contrasted with, rather than, instead of, as an alternative to
example: "we use only steam, as opposed to chemical products, to clean our house"
Exceptions caught by value incur needless cost in C++, most of them can
be caught by const-reference, especially as nearly none are actually
used. This could allow compiler generate a slightly more efficient code.
- This is to accommodate the variabiilty in floating-point operations in new platforms/compilers
- Specifically due to the error margin found in NVIDIA Jetson TX2
* js: update build script
- support emscipten 1.38.12 (wasm is ON by default)
- verbose build messages
* js: use builtin Math functions
* js: disable tracing code completelly
* Make cocoa windows draw faster
* Use a CALayer for rendering when possible Uses GPU to scale images, which is important because retina macs will want window sizes much larger (in pixels) than the image
* Fix mouse logic for cocoa windows
* Only halve resolution on retina if image is larger than display
- improve cpu dispatching calls to allow more SIMD extentions
(SSE4.1, AVX2, VSX)
- wide universal intrinsics
- replace dummy v_expand with v_expand_low
- replace v_expand + v_mul_wrap with v_mul_expand for product accumulate operations
- use FMA for accumulate operations
- add mask and more types to accumulate's performance tests
The `codec_tag` is only available when opening a file from disk. If `AVStream` is a network stream then `fourcc` must be obtained using `codec_id`. I have tested the following scenarios:
1) Open a `.mp4` file and verify that `codec_tag` is returned (old behavior)
2) Open a `rtsp` stream and verify that `codec_fourcc` is returned (Tested with a MJPEG, H264 and H265 stream)
Fixes for instrumentation of IPP and OCL (#12637)
* fixed warning about re-declaring variable when both IPP and instrumentation are enabled
* fixed segfault when no funName provided
* compilation fixed when both OCL and instrumentation are enabled
* Remove isIntel check from deep learning layers
* Remove fp16->fp32 fallbacks where it's not necessary
* Fix Kernel::run to prevent localsize > globalsize
Support asymmetric padding in pooling layer (#12519)
* Add Inception_V1 support in ONNX
* Add asymmetric padding in OpenCL and Inference engine
* Refactoring
Feature/region layer batch mode (#12249)
* Add batch mode for Darknet networks.
Swap variables in test_darknet.
Adapt reorg layer to batch mode.
Adapt region layer.
Add OpenCL implementation.
Remove trailing whitespace.
Bugifx reorg opencl implementation.
Fix bug in OpenCL reorg.
Fix modulo bug.
Fix bug.
Reorg openCL.
Restore reorg layer opencl code.
OpenCl fix.
Work on openCL reorg.
Remove whitespace.
Fix openCL region layer implementation.
Fix bug.
Fix softmax region opencl bug.
Fix opencl bug.
Fix openCL bug.
Update aff_trans.cpp
When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results.
core(libva): support YV12 too
Added to CPU path only.
OpenCL code path still expects NV12 only (according to Intel OpenCL extension)
cmake: allow to specify own libva paths
via CMake:
- `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2`
android: NDK17 support
tested with NDK 17b (17.1.4828580)
Enable more deep learning tests using Intel's Inference Engine backend
ts: don't pass NULL for std::string() constructor
openvino: use 2018R3 defines
experimental version++
OpenCV version++
OpenCV 3.4.3
OpenCV version '-openvino'
openvino: use 2018R3 defines
Fixed windows build with InferenceEngine
dnn: fix variance setting bug for PriorBoxLayer
- The size of second channel should be size[2] of output tensor,
- The Scalar should be {variance[0], variance[0], variance[0], variance[0]}
for _variance.size() == 1 case.
Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
Fix lifetime of networks which are loaded from Model Optimizer IRs
Adds a small note describing BUILD_opencv_world (#12332)
* Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial.
* Made slight changes in BUILD_opencv_world documentation.
* Update windows_install.markdown
improved grammar
Update opengl_interop.cpp
resolves#12307
java: fix LIST_GET macro
fix typo
Added option to fail on missing testdata
Fixed that object_detection.py does not work in python3.
cleanup: IPP Async (IPP_A)
except header file with conversion routines (will be removed in OpenCV 4.0)
imgcodecs: add null pointer check
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
countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics
resolve#5788
imgcodecs(webp): multiple fixes
- don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR)
- avoid memory DDOS
- avoid reading of whole file during header processing
- avoid data access after allocated buffer during header processing (missing checks)
- use WebPFree() to free allocated buffers (libwebp >= 0.5.0)
- drop unused & undefined `.close()` method
- added checks for channels >= 5 in encoder
ml: fix adjusting K in KNearest (#12358)
dnn(perf): fix and merge Convolution tests
- OpenCL tests didn't run any OpenCL kernels
- use real configuration from existed models (the first 100 cases)
- batch size = 1
dnn(test): use dnnBackendsAndTargets() param generator
Bit-exact resize reworked to use wide intrinsics (#12038)
* Bit-exact resize reworked to use wide intrinsics
* Reworked bit-exact resize row data loading
* Added bit-exact resize row data loaders for SIMD256 and SIMD512
* Fixed type punned pointer dereferencing warning
* Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize
Bit-exact GaussianBlur reworked to use wide intrinsics (#12073)
* Bit-exact GaussianBlur reworked to use wide intrinsics
* Added v_mul_hi universal intrinsic
* Removed custom SSE2 branch from bit-exact GaussianBlur
* Removed loop unrolling for gaussianBlur horizontal smoothing
doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214)
* doc: fix English gramma in tutorial out-of-focus-deblur filter
* Update out_of_focus_deblur_filter.markdown
slightly modified one sentence
doc: add new tutorial motion deblur filter (#12215)
* doc: add new tutorial motion deblur filter
* Update motion_deblur_filter.markdown
a few minor changes
Replace Slice layer to Crop in Faster-RCNN networks from Caffe
js: use generated list of OpenCV headers
- replaces hand-written list
imgcodecs(webp): use safe cast to size_t on Win32
* Put Version status back to -dev.
follow the common codestyle
Exclude some target engines.
Refactor formulas.
Refactor code.
* Remove unused variable.
* Remove inference engine check for yolov2.
* Alter darknet batch tests to test with two different images.
* Add yolov3 second image GT.
* Fix bug.
* Fix bug.
* Add second test.
* Remove comment.
* Add NMS on network level.
* Add helper files to dev.
* syntax fix.
* Fix OD sample.
Fix sample dnn object detection.
Fix NMS boxes bug.
remove trailing whitespace.
Remove debug function.
Change thresholds for opencl tests.
* Adapt score diff and iou diff.
* Alter iouDiffs.
* Add debug messages.
* Adapt iouDiff.
* Fix tests
* Add Squeezenet support in ONNX
* Add AlexNet support in ONNX
* Add Googlenet support in ONNX
* Add CaffeNet and RCNN support in ONNX
* Add VGG16 and VGG16 with batch normalization support in ONNX
* Add RCNN, ZFNet, ResNet18v1 and ResNet50v1 support in ONNX
* Add ResNet101_DUC_HDC
* Add Tiny Yolov2
* Add CNN_MNIST, MobileNetv2 and LResNet100 support in ONNX
* Add ONNX models for emotion recognition
* Add DenseNet121 support in ONNX
* Add Inception v1 support in ONNX
* Refactoring
* Fix tests
* Fix tests
* Skip unstable test
* Modify Reshape operation
* may be an typo fix
* remove identical branch,may be paste error
* add parentheses around macro parameter
* simplify if condition
* check malloc fail
* change the condition of branch removed by commit 3041502861
* rewrote Mat::convertTo() and convertScaleAbs() to wide universal intrinsics; added always-available and SIMD-optimized FP16<=>FP32 conversion
* fixed compile warnings
* fix some more compile errors
* slightly relaxed accuracy threshold for int->float conversion (since we now do it using single-precision arithmetics, not double-precision)
* fixed compile errors on iOS, Android and in the baseline C++ version (intrin_cpp.hpp)
* trying to fix ARM-neon builds
* trying to fix ARM-neon builds
* trying to fix ARM-neon builds
* trying to fix ARM-neon builds
* trying to fix the custom AVX2 builder test failures (false alarms)
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* seemingly disabled false alarm warning in surf.cpp; increased tolerance thresholds in the tests for SolvePnP and in DNN/ENet
* 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
