Update app.py

app.py

@@ -18,7 +18,7 @@ model.load_state_dict(torch.load(weights_path, map_location="cpu"))
 model.eval()
 
 # Preprocessing: same as training
-IMG_HEIGHT, IMG_WIDTH = 128, 128
+IMG_HEIGHT, IMG_WIDTH = 448, 448
 transform = transforms.Compose([
     transforms.Resize((IMG_HEIGHT, IMG_WIDTH)),
     transforms.ToTensor()
@@ -26,7 +26,7 @@ transform = transforms.Compose([
 
 def predict(image):
     orig_w, orig_h = image.size   # original size of uploaded image
-    img = transform(image).unsqueeze(0)  # (1,3,128,128)
+    img = transform(image).unsqueeze(0)  
     with torch.no_grad():
         pred = model(img)