opencv-rust VS oxipng

https://github.com/twistedfall/opencv-rust makes it evident that they do try to support using a prebuild system-opencv. Maybe it is not correctly recognized?

opencv

The de facto solution for smart image processing is to use a computer vision library, such as opencv, which has experimental rust bindings: https://github.com/twistedfall/opencv-rust

There is an OpenCV bindings crate. This example might be what you're after https://github.com/twistedfall/opencv-rust/blob/master/examples/video_capture.rs

For example, this is the build script of the opencv bindings: https://github.com/twistedfall/opencv-rust/blob/master/build.rs

I’m trying to get around a known build issue—it would be great for it to be fixed upstream, but I don’t have any control over it except for setting OUT_DIR during its compilation.

I've been using https://github.com/twistedfall/opencv-rust a lot lately and it's really fantastic, they've done a great job matching up with how C++ works, so there are definitely good examples out there.

I never tried it, but the OpenCV bindings might work.

I thought it was going to be unsafe because of how Mat is implemented (more information here). ... I tested it and it should be fine memory-wise. My thought was that the code below was going to be allowed to compile.

I have had good experiences with https://github.com/shssoichiro/oxipng . Although, I suspect this wouldn't give you nearly enough space savings as jpg.

If you do want the file as a PNG (for transparency and a common format that's well supported), but don't want it so huge, consider something like oxipng. https://github.com/shssoichiro/oxipng

oxipng, pngquant and svgcleaner — optimizing images

I wonder how `pngcrush` compares to `oxipng` (https://github.com/shssoichiro/oxipng).

Personally, I use `oxipng` if I want lossless compression. However, most of the time, I use `pngquant` instead, since it gives significant size reduction even at `99%` (I can't even distinguish between the original and reduced image).

    pngquant --quality=99 --ext=.png --force file.png

Depending on your workflow it might make sense to export PNGs directly from Affinity and then reduce their size with a utility like Oxipng, which uses all your cores to find the best algorithm for each particular image.

Assuming your frames are PNG files, you could use a lossless optimizer like optipng to try if their size can be reduced. I prefer oxipng, which is faster and multithreaded, and seems to have more active development.

Not sure what extensions of images you use, but if they’re PNG you could use oxipng: https://github.com/shssoichiro/oxipng