odegeasslbc / differentiable-rgb-to-hsv-convertion-pytorch

A pytorch implementation that converts image RGB color space into HSV allowing differentiable back-propagate

Differentiable-RGB-to-HSV-convertion-pytorch

A pytorch implementation that converts image RGB color space into HSV allowing differentiable back-propagate

Value range

Each H,S,V are values in the range of [0, 1]

How to use

It comes within a Loss function

from pytorch_hsv import HSVLoss

target_h = 0 #red color
target_s = 0.5
target_v = 0.8
loss_hsv = HSVLoss(h=target_h, s=target_s, v=target_v, threshold_h=0.03, threshold_sv=0.1)

Convert rgb image into hsv space

img_rgb = torch.rand(1,3,256,256)
img_hue, img_saturation, img_value = loss_hsv.get_hsv(img_rgb)
# img_hue, ig_stauration and img_value each has the size of 1*256*256

Compute the loss given an image and target hsv

# you can compute the loss value between img_rgb and target h,s,v directly
loss = loss_hsv(img_rgb)

You can also convert back from hsv to rgb

r,g,b = loss_hsv.get_rgb_from_hsv()

differentiable-rgb-to-hsv-convertion-pytorch's Issues

The HSVLoss return None grad？

it seems that the loss is undifferentiable...

HSV to RGB

Hi,

Thanks for the implementation. I am wondering why HSV to RGB conversion is not implemented as the same as RGB to HSV to recieve an image and converts rather than a pixel?