[FOLLOW UP] : Documentation optimizations for the new Sphinx structure #29220
### Pull Request Readiness Checklist
This PR serves as a follow-up to the new documentation system introduced in [#29206](https://github.com/opencv/opencv/pull/29206)
Co-authored by: @abhishek-gola @kirtijindal14 @Akansha-977 @Prasadayus @varun-jaiswal17
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Added image super-resolution samples using seemoredetails model #27592
Based on "See More Details: Efficient Image Super-Resolution by Experts Mining" (ICML 2024)
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This pull request adds a new sample named seemore_superres under samples/dnn/, implemented in both Python and C++.
The sample demonstrates image super-resolution using the Seemoredetails model with OpenCV’s DNN module.
### Files Added:
- samples/dnn/seemore_superres.cpp
- samples/dnn/seemore_superres.py
- Updated samples/dnn/models.yml
### Functionality:
- Performs image upscaling(4x) using a specified Seemoredetails ONNX model.
- Accepts image path and ONNX model path as command-line arguments.
- Outputs the original and super-resolved images side by side for visual comparison.
### Sample Usage:
*C++*
./seemore_superres --input=path/to/image.jpg
`
*Python*
python seemore_superres.py --input=path/to/image.jpg
`
Add Alpha matting samples (C++ and Python) #27593
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Added DNN based deblurring samples #27349
Corresponding pull request adding quantized onnx model to opencv_zoo: https://github.com/opencv/opencv_zoo/pull/295
Model size: 88MB
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* Added mcc to opencv modules
* Removed color correction module
* Updated parameters return type
* Added python sample for macbeth_chart_detection
* Added models.yml support to samples
* Removed unnecessary headers and classes
* fixed datatype conversion
* fixed datatype conversion
* Cleaned headers and added reference/actual colors to samples
* Added mcc tutorial
* fixed datatype and header
* replaced unsigned with int
* Aligned actual and reference color function, added imread
* Fixed shadow variable
* Updated samples
* Added last frame colors prints
* updated detector class
* Added getter functions and useNet function
* Refactoring
* Fixes in test
* fixed infinite divison issue
Extension to PR #26605 ldm inpainting sample #26904
This PR adds and fixes following points in the ldm_inpainting sample on top of original PR #26605 by @Abdurrahheem
DONE:
1. Added functionality to load models from a YAML configuration file, allowing for automatic downloading if models are not found locally.
2. Updated the script usage instructions to reflect the correct command format.
3. Improved user interaction by adding instructions to the image window for inpainting controls.
4. Introduced a new models.yml configuration section for inpainting models weights downloading, including placeholders for model SHA1 checksums.
5. Fixed input types and names of the onnx graph generation.
6. Added links to onnx graphs in models.yml
7. Support added for findModels and standarized the sample usage similar to other dnn samples
8. Fixes issue in download_models.py for downloading models from dl.opencv.org
9. Fixes issue in common.py which used to print duplicated positional arguments in case of samples that use multiple models.
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---------
Co-authored-by: Abdurrahheem <abduragim.shtanchaev@xperience.ai>
Added lama inpainting onnx model sample #26736
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Improved Tracker Samples #26202
Relates to #25006
This sample has been rewritten to track a selected target in a video or camera stream. It combines VIT tracker, Nano tracker and Dasiamrpn tracker into one tracker sample
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Code Fixes and changed post processing based on models.yml in Object Detection Sample #26486
## Major Changes
1. Changes to add findModel support for config file in models like yolov4, yolov4-tiny, yolov3, ssd_caffe, tiny-yolo-voc, ssd_tf and faster_rcnn_tf.
2. Added new model and config download links for ssd_caffe, as previous links were not working.
3. Switched to DNN ENGINE_CLASSIC for non-cpu convig as new engine does not support it.
4. Fixes in python sample related to yolov5 usage.
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Modify DNN Samples to use ENGINE_CLASSIC for Non-Default Back-end or Target #26334
PR resolves#26325 regarding fall-back to ENGINE_CLASSIC if non-default back-end or target is passed by user.
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Improved person reid cpp and python sample #25667#25006
This sample has been rewritten to track a selected target in a video or camera stream. Person detection has been integrated using yolov8 and the user can provide a target image via command line or interactively select the target at start of the execution
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Add support for downloading DNN config files in download_models.py #26186
PR resloves #26160 related to downloading DNN config files using download_models.py
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Merged yolo_detector and object detection sample #25710
Relates to #25006
This pull request merges the yolo_detector.cpp sample with the object_detector.cpp sample. It also beautifies the bounding box display on the output images
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Added and tested yolov5l model. #26154
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Improved and refactored text detection sample in dnn module #25326
Clean up samples: #25006
This pull requests merges and simplifies different text detection samples in dnn module of opencv in to one file. An option has been provided to choose the detection model from EAST or DB
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#25006#25314
This pull request removes hed_pretrained caffe model to the SOTA dexined onnx model for edge detection. Usage of conventional methods like canny has also been added
The obsolete cpp and python sample has been removed
TODO:
- [ ] Remove temporary hack for quantized models. Refer issue https://github.com/opencv/opencv_zoo/issues/273
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Improved classification sample #25519#25006#25314
This pull requests replaces the caffe model for classification with onnx versions. It also adds resnet in model.yml.
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[BUG FIX] Segmentation sample u2netp model results #25756
PR resloves #25753 related to incorrect output from u2netp model in segmentation sample
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Add yolov8l.onnx to samples #25775
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Hello, I noticed that the /samples/dnn/models.yml said it should be used for all yolov8 models, but the YOLOv8l is not included in the file, so I added it to the file, thanks.
Improved segmentation sample #25559#25006
This pull request replaces caffe models with onnx for the dnn segmentation sample in cpp and python
fcnresnet-50 and fcnresnet-101 has been replaced
u2netp (foreground-background) segmentation onnx model has been added [U2NET](https://github.com/xuebinqin/U-2-Net)
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Change opencv_face_detector related tests and samples from caffe to onnx #25463
Part of https://github.com/opencv/opencv/issues/25314
This PR aims to change the tests related to opencv_face_detector from caffe framework to onnx. Tests in `test_int8_layer.cpp` and `test_caffe_importer.cpp` will be removed in https://github.com/opencv/opencv/pull/25323
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Added and tested yolov8m model. #25357
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Added and tested yolov8s and yolov8n model #25176
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Added and tested yolov8x model #25095
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Using cv2 dnn interface to run yolov8 model #24396
This is a sample code for using opencv dnn interface to run ultralytics yolov8 model for object detection.
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Add weights yolov3 in models.yml #24496
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I don't know if this action is necessary, or the previous PR scale for the brach master.
Thanks.
Added PyTorch fcnresnet101 segmentation conversion cases #24397
We write a sample code about transforming Pytorch fcnresnet101 to ONNX running on OpenCV.
The input source image was shooted by ourself.
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Remove torch (old torch7) from dnn in 5.x #24294
Merge with https://github.com/opencv/opencv_extra/pull/1097
Completely removed torch (old torch7) from dnn:
- removed modules/dnn/src/torch directory that contained torch7 model parser
- removed readNetFromTorch() and readTorchBlob() public functions
- removed torch7 references from comments and help texts
- replaced links to t7 models by links to similar onnx models in js_style_transfer turtorial (similar to https://github.com/opencv/opencv/pull/24245/files)
Scripts for downloading models in DNN samples
* Initial commit. Utility classes and functions for downloading files
* updated download script
* Support YAML parsing, update download script and configs
* Fix problem with archived files
* fix models.yml
* Move download utilities to more appropriate place
* Fix script description
* Update README
* update utilities for broader range of files
* fix loading with no hashsum provided
* remove unnecessary import
* fix for Python2
* Add usage examples for downloadFile function
* Add more secure cache folder selection
* Remove trailing whitespaces
* Fix indentation
* Update function interface
* Change function for temp dir, change entry name in models.yml
* Update getCacheDirectory function call
* Return python implementation for cache directory selection, use more specific env variable
* Fix whitespace
omrope79
MykhailoTrushch
Naresh M L
Harii Sankar S
Abhishek Gola
Gursimar Singh
Alexander Smorkalov
Alessandro de Oliveira Faria (A.K.A.CABELO)
richard28039
Wanli
Chia-Hsiang Tsai
alexlyulkov
Sergei Slashchinin
berak
Dmitry Kurtaev