Update utils.py

utils/utils.py

@@ -6,6 +6,8 @@ import keras.backend as K
 from functools import reduce
 from PIL import Image
 from matplotlib.colors import rgb_to_hsv, hsv_to_rgb
+import cv2
+
 def compose(*funcs):
     if funcs:
         return reduce(lambda f, g: lambda *a, **kw: g(f(*a, **kw)), funcs)
@@ -142,15 +144,16 @@ def get_random_data_with_Mosaic(annotation_line, input_shape, max_boxes=50, hue=
         hue = rand(-hue, hue)
         sat = rand(1, sat) if rand()<.5 else 1/rand(1, sat)
         val = rand(1, val) if rand()<.5 else 1/rand(1, val)
-        x = rgb_to_hsv(np.array(image)/255.)
-        x[..., 0] += hue
+        x = cv2.cvtColor(np.array(image,np.float32)/255, cv2.COLOR_RGB2HSV)
+        x[..., 0] += hue*360
         x[..., 0][x[..., 0]>1] -= 1
         x[..., 0][x[..., 0]<0] += 1
         x[..., 1] *= sat
         x[..., 2] *= val
-        x[x>1] = 1
+        x[x[:,:, 0]>360, 0] = 360
+        x[:, :, 1:][x[:, :, 1:]>1] = 1
         x[x<0] = 0
-        image = hsv_to_rgb(x)
+        image = cv2.cvtColor(x, cv2.COLOR_HSV2RGB) # numpy array, 0 to 1
 
         image = Image.fromarray((image*255).astype(np.uint8))
         # 将图片进行放置，分别对应四张分割图片的位置
@@ -237,15 +240,16 @@ def get_random_data(annotation_line, input_shape, max_boxes=50, jitter=.3, hue=.
     hue = rand(-hue, hue)
     sat = rand(1, sat) if rand()<.5 else 1/rand(1, sat)
     val = rand(1, val) if rand()<.5 else 1/rand(1, val)
-    x = rgb_to_hsv(np.array(image)/255.)
-    x[..., 0] += hue
+    x = cv2.cvtColor(np.array(image,np.float32)/255, cv2.COLOR_RGB2HSV)
+    x[..., 0] += hue*360
     x[..., 0][x[..., 0]>1] -= 1
     x[..., 0][x[..., 0]<0] += 1
     x[..., 1] *= sat
     x[..., 2] *= val
-    x[x>1] = 1
+    x[x[:,:, 0]>360, 0] = 360
+    x[:, :, 1:][x[:, :, 1:]>1] = 1
     x[x<0] = 0
-    image_data = hsv_to_rgb(x) # numpy array, 0 to 1
+    image_data = cv2.cvtColor(x, cv2.COLOR_HSV2RGB) # numpy array, 0 to 1
 
     # 将box进行调整
     box_data = np.zeros((max_boxes,5))