Fixed HashTSDF expand bug #27801
HashTSDF should expand volume units during integration. It didn't happen in fact because of wrong Mat passing.
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Added nonmaxsuppression (NMS) layer to new DNN engine #27674
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Added fully functional resize layer to new DNN engine #27586
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Added unique layer to new DNN engine #27676
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Use MatShape instead of MatSize inside cv::Mat/cv::UMat #27757
**Merge together with https://github.com/opencv/opencv_contrib/pull/3996**
---
This PR continues cv::Mat/cv::UMat refactoring. See #26056, where `MatShape` was introduced. Now it's put inside cv::Mat/cv::UMat instead of a weird `MatSize`. MatSize is now an alias for MatShape:
**before:**
```
struct MatShape { ... };
struct MatSize { ... };
struct Mat {
...
int dims;
int rows;
int cols;
...
MatShape shape() const { ... /* constructs MatShape out of MatSize and returns it;
layout is always 'unknown', because we don't store it */ }
MatSize size; // size is not valid without the parent cv::Mat,
// because size.p may point to Mat::rows or to Mat::cols,
// depending on the dimensionality, and dims() returns Mat::dims.
MatStep step; // may allocate memory, depending on the dimensionality.
...
};
```
**after:**
```
struct MatShape { ... };
typedef MatShape MatSize; // they are now synonyms
struct Mat {
...
int dims;
int rows;
int cols;
...
MatShape shape() const { return size; } // just return the embedded shape (including the proper layout information)
MatSize size; // size is self-contained data structure that can be used without the parent cv::Mat.
// size.dims is now a copy of dims; size.p[*] contains copies of Mat::rows and Mat::cols when dims <= 2.
MatStep step; // does not allocate extra memory buffers.
...
};
```
There are several reasons to do that:
1. the main reason is to be able to store data layout (MatShape::layout) inside each cv::Mat/cv::UMat. This is necessary for the proper shape inference in DNN module. In particular, it's necessary for the next step of DNN inference optimization where we introduce block-layout-optimized convolution and other operations. Later on, we can use layout information to support non-interleaved images (e.g. RRR...GGG...BBB...) or even batches of such images in core/imgproc modules.
2. the other reason is to represent 3D/4D/5D etc. tensors as cv::Mat/cv::UMat instances more conveniently, without extra dynamic memory allocation. Before this patch we allocated some memory buffers dynamically to store shape & steps for more than 2D arrays. Now the whole cv::Mat/cv::UMat header can be stored completely on stack/in a container. Creating another copy of Mat/UMat header is now done more efficiently.
3. the third reason is to introduce the new coding pattern: `dst.create(src.size, <dst_type>);`. The pattern is suitable for most of element-wise (including cloning) and filtering operations. This pattern does not only look crisp and self-documenting, it will also automatically copy shape (including layout) from the source tensor into the destination matrix/tensor.
4. in the future we might add `colorspace` member to MatShape that will allow to distinguish RGB from BGR or NV12. `dst.create(src.size, <dst_type>);` will then copy the colorspace information as well.
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Added nonzero layer to new DNN engine #27701
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Added Pow layer to new DNN engine #27710
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Added gridsample layer to new DNN engine #27700
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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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Set limitation to IPP Bilateral Filter tiles number to avoid too small tiles #27720
### Pull Request Readiness Checklist
This PR fixes the following issue in Bilateral Filter tiling in IPP integration: image ROI can't be closer to the image border than the filter window radius. This issue shows itself during separation of the image to tiles for multithreaded processing. If the tile size small enough, the second tile is closer to the upper image border than the bilateral filter radius, which leads to the incorrect result. To fix this, we need a limitation to the tile size - done in this PR.
_Note: red build status looks like unrelated to the current change_
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[videoio][VideoWriter] Fix return code from CvVideoWriter_FFMPEG::writeFrame() when encapsulating encoded video #27737
Currently the return code from `CvVideoWriter_FFMPEG::writeFrame()` when `encode_video==true` (encapsulating raw encoded video) is wrong and results in the following warning implying it has been unsuccessful
> [ WARN:0@15.551] global cap_ffmpeg.cpp:198 write FFmpeg: Failed to write frame
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doc: fix doxygen warnings for imgcodecs, flann and objdetect #27730
Close https://github.com/opencv/opencv/issues/27729
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libpng upgrade to 1.6.45 and cICP metadata support for PNG imwrite #27741
### Pull Request Readiness Checklist
resolves#24185
libpng docs: https://www.w3.org/TR/png-3/#cICP-chunk
similar code from ffmpeg: https://github.com/FFmpeg/FFmpeg/blob/a700f0f72d1f073e5adcfbb16f4633850b0ef51c/libavcodec/pngenc.c#L452-L456
So issue #24185 can be solved by replacing `cv.imwrite` in user's code to `cv.imwriteWithMetadata`:
```python
cv.imwriteWithMetadata("frame.png", frame, [cv.IMAGE_METADATA_CICP], np.array([[9, 18, 0, 1]], np.uint8))
```
```
$ exiftool /home/d.kurtaev/opencv_build/frames_pr/image_38.png
ExifTool Version Number : 12.76
File Name : image_38.png
Directory : /home/d.kurtaev/opencv_build/frames_pr
File Size : 3.8 MB
File Modification Date/Time : 2025:09:02 20:48:22+03:00
File Access Date/Time : 2025:09:02 20:48:22+03:00
File Inode Change Date/Time : 2025:09:02 20:48:22+03:00
File Permissions : -rw-r--r--
File Type : PNG
File Type Extension : png
MIME Type : image/png
Image Width : 1080
Image Height : 1920
Bit Depth : 8
Color Type : RGB
Compression : Deflate/Inflate
Filter : Adaptive
Interlace : Noninterlaced
Color Primaries : BT.2020, BT.2100
Transfer Characteristics : BT.2100 HLG, ARIB STD-B67
Matrix Coefficients : Identity matrix
Video Full Range Flag : 1
Image Size : 1080x1920
Megapixels : 2.1
```
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Rostislav Vasilikhin
Alexander Smorkalov
Abhishek Gola
Alexander Smorkalov
Rostislav Vasilikhin
Vadim Pisarevsky
cudawarped
Kavyansh Tyagi
Dmitry Kurtaev
Uilian Ries
Kumataro
Nadezhda Mizonova
Alexander Smorkalov