Is there a way to use Cuda version of fastNlMeansDenoising in python?

Is there a way to use Cuda version of fastNlMeansDenoising in python?

It doesn’t look like it at the moment, the funciton is not wrapped, which OS are you using?

If its linux, you can try the bindings here

they are working for me on WSL ubuntu 20.04 with mambafoge (python 3.9.13)

Help on built-in function fastNlMeansDenoising:

fastNlMeansDenoising(src, h[, dst[, search_window[, block_size[, stream]]]]) → dst
. @brief Perform image denoising using Non-local Means Denoising algorithm
. with several computational
. optimizations. Noise expected to be a gaussian white noise
. @param src Input 8-bit 1-channel, 2-channel or 3-channel image.
. @param dst Output image with the same size and type as src .
. @param h Parameter regulating filter strength. Big h value perfectly removes noise but also
. removes image details, smaller h value preserves details but also preserves some noise
. @param search_window Size in pixels of the window that is used to compute weighted average for
. given pixel. Should be odd. Affect performance linearly: greater search_window - greater
. denoising time. Recommended value 21 pixels
. @param block_size Size in pixels of the template patch that is used to compute weights. Should be
. odd. Recommended value 7 pixels
. @param stream Stream for the asynchronous invocations.
. This function expected to be applied to grayscale images. For colored images look at
. FastNonLocalMeansDenoising::labMethod.
. @sa
. fastNlMeansDenoising

This is now fixed on the master branch.