Update README.md

README.md

@@ -65,25 +65,6 @@ import cv2
 import os
 
 
-
-def HWC3(x):
-    assert x.dtype == np.uint8
-    if x.ndim == 2:
-        x = x[:, :, None]
-    assert x.ndim == 3
-    H, W, C = x.shape
-    assert C == 1 or C == 3 or C == 4
-    if C == 3:
-        return x
-    if C == 1:
-        return np.concatenate([x, x, x], axis=2)
-    if C == 4:
-        color = x[:, :, 0:3].astype(np.float32)
-        alpha = x[:, :, 3:4].astype(np.float32) / 255.0
-        y = color * alpha + 255.0 * (1.0 - alpha)
-        y = y.clip(0, 255).astype(np.uint8)
-        return y
-
 def nms(x, t, s):
     x = cv2.GaussianBlur(x.astype(np.float32), (0, 0), s)
 
@@ -137,7 +118,7 @@ if random.random() > 0.5:
 
   image_path = Image.open("your image path, the image can be real or anime, HED detector will extract its edge boundery")
   processor = HEDdetector.from_pretrained('lllyasviel/Annotators')
-  controlnet_img = processor(image_path, scribble=True)
+  controlnet_img = processor(image_path, scribble=False)
   controlnet_img.save("a hed detect path for an image")
 
   # following is some processing to simulate human sketch draw, different threshold can generate different width of lines