Update RGB2LAB to optimize time

src/utils.py

@@ -13,6 +13,7 @@ from numba import cuda, jit
 import math
 import torchvision.utils as vutils
 from torch.autograd import Variable
+import cv2
 
 rgb_from_xyz = np.array(
     [
@@ -318,7 +319,9 @@ class RGB2Lab(object):
         pass
 
     def __call__(self, inputs):
-        return color.rgb2lab(inputs)
+        normed_inputs = np.float32(inputs) / 255.0
+        rgb_inputs = cv2.cvtColor(normed_inputs, cv2.COLOR_RGB2LAB)
+        return rgb_inputs
 
 
 class ToTensor(object):
@@ -846,4 +849,4 @@ def print_num_params(model, is_trainable=False):
         num_params = sum(p.numel() for p in model.parameters())
         print(f"|  GENERAL  | {model_name} | {('{:,}'.format(num_params)).rjust(10)} |")
 
-    return num_params
+    return num_params