Update process_automated_droplet.py

classes/droplet/process_automated_droplet.py

@@ -289,6 +289,7 @@ images_mean_pixel = []
 images_path = glob.glob(DATASET_DIR + "/*.jpg")
 for img_path in images_path:
     img = cv2.imread(img_path)
+    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
     if CONTRAST == 1:
         # adaptive Equalization
         img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
@@ -583,8 +584,6 @@ def pre_processing(image, crop=None, size_y=1024, size_x=1024, contrast=0):
         # contrast stretching
         p2, p98 = np.percentile(image, (2, 98))
         image = exposure.rescale_intensity(image, in_range=(p2, p98))
-    if CONTRAST != 0:        
-        image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
     
     return image
 
@@ -598,6 +597,7 @@ counter_1 = SAVE_NTH_IMAGE
 for filename in os.listdir(DATASET_DIR):
     if not filename.endswith('.json'):
         image = cv2.imread(os.path.join(DATASET_DIR, filename))
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
         # pre process image
         if IMAGE_CROP or CONTRAST != 0:
             image = pre_processing(image, crop=IMAGE_CROP, contrast=CONTRAST)