Update docstring of ColorJitter, adjust_hue,_rgb2hsv (#5695)

* Update docstring of adjust_hue
Signed-off-by: Behrooz <3968947+drbeh@users.noreply.github.com>

* Update docstring of ColorJitter
Signed-off-by: Behrooz <3968947+drbeh@users.noreply.github.com>

* Minor corrections
Signed-off-by: Behrooz <3968947+drbeh@users.noreply.github.com>

torchvision/transforms/functional.py

@@ -880,6 +880,9 @@ def adjust_hue(img: Tensor, hue_factor: float) -> Tensor:
             If img is torch Tensor, it is expected to be in [..., 1 or 3, H, W] format,
             where ... means it can have an arbitrary number of leading dimensions.
             If img is PIL Image mode "1", "I", "F" and modes with transparency (alpha channel) are not supported.
+            Note: the pixel values of the input image has to be non-negative for conversion to HSV space;
+            thus it does not work if you normalize your image to an interval with negative values,
+            or use an interpolation that generates negative values before using this function.
         hue_factor (float):  How much to shift the hue channel. Should be in
             [-0.5, 0.5]. 0.5 and -0.5 give complete reversal of hue channel in
             HSV space in positive and negative direction respectively.

torchvision/transforms/transforms.py

@@ -1156,6 +1156,9 @@ class ColorJitter(torch.nn.Module):
         hue (float or tuple of float (min, max)): How much to jitter hue.
             hue_factor is chosen uniformly from [-hue, hue] or the given [min, max].
             Should have 0<= hue <= 0.5 or -0.5 <= min <= max <= 0.5.
+            To jitter hue, the pixel values of the input image has to be non-negative for conversion to HSV space;
+            thus it does not work if you normalize your image to an interval with negative values,
+            or use an interpolation that generates negative values before using this function.
     """
 
     def __init__(self, brightness=0, contrast=0, saturation=0, hue=0):