Update config.py

config.py

@@ -1,9 +1,10 @@
 import albumentations as A
-import cv2
+#import cv2
 import torch
 
 from albumentations.pytorch import ToTensorV2
-from utils import seed_everything
+
+#from utils import seed_everything
 
 DATASET = 'PASCAL_VOC'
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
@@ -41,7 +42,7 @@ train_transforms = A.Compose(
         A.PadIfNeeded(
             min_height=int(IMAGE_SIZE * scale),
             min_width=int(IMAGE_SIZE * scale),
-            border_mode=cv2.BORDER_CONSTANT,
+            #border_mode=cv2.BORDER_CONSTANT,
         ),
         A.Rotate(limit = 10, interpolation=1, border_mode=4),
         A.RandomCrop(width=IMAGE_SIZE, height=IMAGE_SIZE),
@@ -49,7 +50,7 @@ train_transforms = A.Compose(
         A.OneOf(
             [
                 A.ShiftScaleRotate(
-                    rotate_limit=20, p=0.5, border_mode=cv2.BORDER_CONSTANT
+                    rotate_limit=20, p=0.5, #border_mode=cv2.BORDER_CONSTANT
                 ),
                 # A.Affine(shear=15, p=0.5, mode="constant"),
             ],
@@ -70,7 +71,7 @@ test_transforms = A.Compose(
     [
         A.LongestMaxSize(max_size=IMAGE_SIZE),
         A.PadIfNeeded(
-            min_height=IMAGE_SIZE, min_width=IMAGE_SIZE, border_mode=cv2.BORDER_CONSTANT
+            min_height=IMAGE_SIZE, min_width=IMAGE_SIZE, #border_mode=cv2.BORDER_CONSTANT
         ),
         A.Normalize(mean=[0, 0, 0], std=[1, 1, 1], max_pixel_value=255,),
         ToTensorV2(),