Refactor: Remove cv2 depedency

test.py

+import os
 import argparse
 
-import torch
-import cv2
+from PIL import Image
 import numpy as np
-import os
+
+import torch
+from torchvision.transforms.functional import to_tensor, to_pil_image
 
 from model import Generator
 
+
 torch.backends.cudnn.enabled = False
 torch.backends.cudnn.benchmark = False
 torch.backends.cudnn.deterministic = True
-    
+
+
 def load_image(image_path, x32=False):
-    img = cv2.imread(image_path).astype(np.float32)
-    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-    h, w = img.shape[:2]
+    img = Image.open(image_path).convert("RGB")
 
-    if x32: # resize image to multiple of 32s
+    if x32:
         def to_32s(x):
-            return 256 if x < 256 else x - x%32
-        img = cv2.resize(img, (to_32s(w), to_32s(h)))
+            return 256 if x < 256 else x - x % 32
+        w, h = img.size
+        img = img.resize((to_32s(w), to_32s(h)))
 
-    img = torch.from_numpy(img)
-    img = img/127.5 - 1.0
     return img
 
 
@@ -43,22 +44,22 @@ def test(args):
         image = load_image(os.path.join(args.input_dir, image_name), args.x32)
 
         with torch.no_grad():
-            input = image.permute(2, 0, 1).unsqueeze(0).to(device)
-            out = net(input, args.upsample_align).squeeze(0).permute(1, 2, 0).cpu().numpy()
-            out = (out + 1)*127.5
-            out = np.clip(out, 0, 255).astype(np.uint8)
-            
-        cv2.imwrite(os.path.join(args.output_dir, image_name), cv2.cvtColor(out, cv2.COLOR_BGR2RGB))
+            image = to_tensor(image).unsqueeze(0) * 2 - 1
+            out = net(image.to(device), args.upsample_align).cpu()
+            out = out.squeeze(0).clip(-1, 1) * 0.5 + 0.5
+            out = to_pil_image(out)
+
+        out.save(os.path.join(args.output_dir, image_name))
         print(f"image saved: {image_name}")
 
-    
+
 if __name__ == '__main__':
 
     parser = argparse.ArgumentParser()
     parser.add_argument(
         '--checkpoint',
         type=str,
-        default='./pytorch_generator_Paprika.pt',
+        default='./weights/paprika.pt',
     )
     parser.add_argument(
         '--input_dir', 
@@ -79,12 +80,13 @@ if __name__ == '__main__':
         '--upsample_align',
         type=bool,
         default=False,
+        help="Align corners in decoder upsampling layers"
     )
     parser.add_argument(
         '--x32',
         action="store_true",
+        help="Resize images to multiple of 32"
     )
     args = parser.parse_args()
     
     test(args)
-