Changed level of brightness augmentation

helper.py

@@ -67,7 +67,7 @@ def augment_brightness_camera_images(image):
     image1 = cv2.cvtColor(image,cv2.COLOR_RGB2HSV)
     # randomly generate the brightness reduction factor
     # Add a constant so that it prevents the image from being completely dark
-    random_bright = .25+np.random.uniform()
+    random_bright = np.random.uniform(low=0.7, high=1.2)
     # Apply the brightness reduction to the V channel
     image1[:,:,2] = image1[:,:,2]*random_bright
     # convert to RBG again
@@ -105,8 +105,7 @@ def get_batches_fn(batch_size):
                     gt_image = scipy.misc.imresize(scipy.misc.imread(gt_image_file), image_shape)
 
                     if augment:
-                        # image = augment_brightness_camera_images(image)
-
+                        image = augment_brightness_camera_images(image)
                         flip_prob = np.random.random()
                         if flip_prob > 0.5:
                             # flip the images

main.py

@@ -302,7 +302,7 @@ def run():
     print("learning rate:", LEARNING_RATE)
     print("Keep prob:", KEEP_PROB)
     print("Batch size:", batch_size)
-    print("Training mode:", "True" if testing_mode else "False")
+    print("Training mode:", "False" if testing_mode else "True")
     print("Trasfer learning mode:", "True" if TRANSFER_LEARNING_MODE else "False")
     print("Continue training?:", "True" if CONTINUE_TRAINING else "False")