merge brightness contrast and hue adjustment together

Author: justincdavis

test/test_transforms_v2.py

@@ -6259,10 +6259,8 @@ def test_correctness_image(self, make_input, hue_factor):
         actual = F.adjust_hue(image, hue_factor=hue_factor)
 
         if make_input is make_image_cvcuda:
-            actual = F.cvcuda_to_tensor(actual).to(device="cpu")
-            actual = actual.squeeze(0)
-            image = F.cvcuda_to_tensor(image)
-            image = image.squeeze(0)
+            actual = cvcuda_to_pil_compatible_tensor(actual)
+            image = cvcuda_to_pil_compatible_tensor(image)
 
         expected = F.to_image(F.adjust_hue(F.to_pil_image(image), hue_factor=hue_factor))
 

torchvision/transforms/v2/functional/_color.py

@@ -471,9 +471,12 @@ def _adjust_hue_cvcuda(image: "cvcuda.Tensor", hue_factor: float) -> "cvcuda.Ten
         return image
 
     # no native adjust_hue, use CV-CUDA for color converison, use torch for elementwise operations
+    # CV-CUDA accelerates the HSV conversion
     hsv = cvcuda.cvtcolor(image, cvcuda.ColorConversion.RGB2HSV)
+    # then use torch for elementwise operations
     hsv_torch = torch.as_tensor(hsv.cuda()).float()
     hsv_torch[..., 0] = (hsv_torch[..., 0] + hue_factor * 180) % 180
+    # convert back to cvcuda tensor and accelerate the HSV2RGB conversion
     hsv_modified = cvcuda.as_tensor(hsv_torch.to(torch.uint8), "NHWC")
     return cvcuda.cvtcolor(hsv_modified, cvcuda.ColorConversion.HSV2RGB)