This is an unusual visualisation of haarcascades. Often, only haarcascade features are drawn. This visualisation however, adds up all matching features in an image. Resulting in a sort of lense which shows the contrasts in the image that the algorithm picks up on most.
* The visual_haarcascades binary ([main.rs](src/main.rs)) uses V4L to capture webcam input and renders to a canvas.
* [test.rs](src/test.rs) binary is an ugly program that looks hard-coded for `haarcascade_frontalface_alt2.xml` and `test.png`. It renders the output to `test-output.png`.
* The library is made for use with eg. Python through cffi. See eg. [this repo](https://git.rubenvandeven.com/r/face_recognition)
It _could_ be that the code in commit `f9b066a166fb0d2f042c6f745fa0ffbcce100666` is actually faster than the current master. While this is certainly not the case in a `debug` build (HEAD is way faster!), a `release` build seems to bring it up to higher speeds... confusing :-)
