OpenCV VS CImg

Note that the 'Jump Flood Algorithm' is O(N log N) where N is the number of pixels. There is a better O(N) algorithm which can be parallelized over the number of rows/columns of an image:

https://news.ycombinator.com/item?id=36809404

Unfortunately, it requires random access writes (compute shaders) if you want to run it on the GPU. But if CPU is fine, here are a few implementations:

JavaScript: https://parmanoir.com/distance/

C: https://github.com/983/df

C++: https://github.com/opencv/opencv/blob/4.x/modules/imgproc/sr...

Python: https://github.com/pymatting/pymatting/blob/afd2dec073cb08b8...

OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision.

This library is used for image and video processing, offering functions for tasks like object detection, filtering, and transformations in computer vision.

Download the Haar cascade XML files for face and smile detection: https://github.com/opencv/opencv/tree/master/data/haarcascades

Let's open the most recent release of opencv to the date of this video capturing: https://github.com/opencv/opencv/releases/tag/4.5.1

First of all, OpenCV, an open-source computer vision library, was used as the main editing tool. This is how NuloApp is able to get the correct aspect ratio for smartphone content, and do other cool things like centering the video on the speaker so that they aren't out of frame when the aspect ratio is changed.

git clone https://github.com/opencv/opencv.git mkdir -p build && cd build cmake ../opencv make -j4 sudo make install

OpenCV: Visión por Computadora para Todos (https://dev-to-uploads.s3.amazonaws.com/uploads/articles/zxyacyoqx4h0lvem6jpj.png)

In addition to installing the YOLO implementation from Ultralytics, this also installs OpenCV for image processing.

It looks promising.

I like the way each algorithm is explained with minimal example and demo images.

I'm looking for such a lightweight vision lib to embed simple image manipulation programs on tiny ESP32-CAM boards.

OpenCV seems too heavy to integrate on such small devices.

So far, I've been able to develop simple image processing programs with CImg[1] (simple filtering, image cropping, adding text).

I'll try to spend some time exploring this SOD lib, thank you for sharing.

[1] https://cimg.eu/

CImg : http://cimg.eu/ (C++)