Fix string property bindings in JS generator #27726Fixes#27712
This PR fixes the binding generation logic in embindgen.py to correctly handle enum and string properties:
Enum properties now use binding_utils::underlying_ptr(&Class::property).
Standard string properties are bound directly with &Class::property.
Other properties continue to use the default template.
Testing:
Verified generated bindings locally to ensure the expected output for enums and strings.
imgproc: add minEnclosingConvexPolygon #27369
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core: ARM64 loop unrolling in kmeans to improve Weighted Filter performance #27596
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- This PR improves the performance of the Weighted Filter function from the ximgproc module on Windows on ARM64.
- The optimization is achieved by unrolling two performance-critical loops in the generateCentersPP function in modules/core/src/kmeans.cpp, which is internally used by the Weighted Filter function.
- The unrolling is enabled only for ARM64 builds using #if defined(_M_ARM64) guards to preserve compatibility and maintain performance on other architectures.
**Performance Improvements:**
- Improves execution time for Weighted Filter performance tests on ARM64 without affecting other platforms.
<img width="772" height="558" alt="image" src="https://github.com/user-attachments/assets/ae28c0af-97d3-460b-ad5a-207d3fc6936f" />
Improved Gaussian Blur #27795
- Horizontal and vertical kernels of 3N131 and 5N14641 are combined for non-border(inner) regions.
- Temporary storage of intermediate results are avoided by combining the kernels.
- Further refinement of other 3N, 5N to be added later.
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imgcodecs: bmp: relax decoding size limit to over 1GiB #27811
Close https://github.com/opencv/opencv/issues/27789
Close https://github.com/opencv/opencv/issues/23233
### Pull Request Readiness Checklist
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libtiff upgrade to version 4.7.1 #27806
close https://github.com/opencv/opencv/issues/27784
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stitching: enable loop unrolling in fast.cpp to improve ARM64 performance #27642
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- This PR introduces an ARM64-specific performance optimization in the FAST_t function by applying loop unrolling.
- The optimization is guarded with #if defined(_M_ARM64) to ensure it only affects ARM64 builds.
- This optimizations lead to performance improvements in stitching module functions.
**Performance Improvements:**
- This change significantly improved the performance on Windows ARM64 targets.
<img width="935" height="579" alt="image" src="https://github.com/user-attachments/assets/a03833d1-ac9b-408f-916b-243fd6ae2d53" />
dnn: improve performance of softmax_3d with loop unrolling #27777
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- This PR applies loop unrolling in the softmax function.
- The change does not affect functional correctness.
**Performance Improvements**
- The optimization significantly improves the performance of softmax_3d on Windows ARM64 targets.
<img width="703" height="203" alt="image" src="https://github.com/user-attachments/assets/85997c15-f543-432c-95e5-69099d71fe71" />
dnn: Tune CONV_NR_FP32 size for WASM #27773
We can see ~20% inference time reduction on local benchmark.
The local benchmark includes face detection with res10_300x300_ssd_iter_140000_fp16.caffemodel and image classification with squeezenet.onnx .
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features2d: performance optimization of detect function on Windows-ARM64 #27776
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- This PR improves the performance of the detect function on Windows ARM64 targets.
- Added the defined(_M_ARM64) macro in agast.cpp and agast_score.cpp files, aligning ARM64 behavior with how x64 selects internal functions for computation.
- As a result, ARM64 now executes the same internal functions as x64 where applicable, leading to measurable performance improvements in detect function.
- This changes is limited to Windows ARM64 and does not affect other architectures
**Performance impact:**
- Detect function shows improved runtime on ARM64 targets due to reuse of existing efficient computation paths.
<img width="1419" height="408" alt="image" src="https://github.com/user-attachments/assets/feab411a-d256-4bff-bec2-22b2583f63d1" />
Skip ARM assembly file on QNX #27774
This fixes build failures on QNX caused by unsupported ARM NEON assembly in arm/filter_neon.S. The QNX environment does not handle this assembly source correctly, resulting in compilation errors.
Build and test instruction for QNX:
https://github.com/qnx-ports/build-files/blob/main/ports/opencv/README.md
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Add strict validation for encoding parameters for APNG, Animation WebP #27769
Extra fix for https://github.com/opencv/opencv/issues/27557
- Fix for build errors with libspng library.
- Add strict validation for APNG.
- Add strict validation for Animation WebP.
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Fix Python Scalar typing issue #27528#27620
- Add ScalarInput and ScalarOutput types for better type safety
- ScalarInput: Union[Sequence[float], float] for function parameters
- ScalarOutput: Sequence[float] for function return values
- Keep original Scalar type for backwards compatibility (deprecated)
- Add refinement functions to apply new types to specific functions
- Functions returning scalars now use ScalarOutput (mean, sumElems, trace)
- Drawing functions now use ScalarInput for color parameters
- Resolves MyPy compatibility issues with scalar return values
- Maintains full backwards compatibility
closes#27528
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Optimize FFmpeg VideoCapture with swscale threads option #27755
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/21969
* Switch to `sws_scale_from` for `libswscale >= 6.4.100` (FFmpeg >= 5.0)
* Use new context init API with threads option (`libswscale >= 8.12.100`: https://github.com/FFmpeg/FFmpeg/commit/2a091d4f2ee1e367d05a6bbbe96b204257cbda87)
* Replicate `sws_getCachedContext` with threads option for `libswscale < 8.12.100`
1 hour mp4 video every frame reading
| HW | sws_scale | sws_scale_frame + 16 threads | sws_scale_frame + 24 threads (#cpus) |
|---|---|---|---|
| Intel Core i9-12900 CPU | 45.1 sec | 25.4 sec (x1.77) | 30 sec (x1.50) |
| NVIDIA GPU 4090 | 232 sec | 89.4 sec (x2.59) | 77 sec (x3.01) |
```
import time
import numpy as np
import os
import cv2 as cv
# os.environ["OPENCV_FFMPEG_CAPTURE_OPTIONS"] = "hwaccel;cuvid|video_codec;h264_cuvid|vsync;0"
start = time.time()
video = "test.mp4"
cap = cv.VideoCapture(video, cv.CAP_FFMPEG)
while True:
has_frame, frame = cap.read()
if not has_frame:
break
print(time.time() - start)
```
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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imgcodecs: bmp: support to write 32bpp BMP with BI_BITFIELDS #27559
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Alexander Smorkalov
Alexander Smorkalov
Timi
Marius Wachtler
SaraKuhnert
pratham-mcw
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Madan mohan Manokar
Alexander Smorkalov
underdevelopedprefrontalcortex
Alexander Alekhin
Jie Pan
hyarasi13
Maksim Shabunin
Quaylyn Rimer
Vadim Levin
cudawarped
Kavyansh Tyagi
Dmitry Kurtaev
Uilian Ries