114514

app.py

@@ -26,9 +26,7 @@ net_i.eval().to('cuda')
 net_c.eval().to('cuda')
 
 def align(x1):
-    h, w = x1.shape[-2], x1.shape[-1]
-    h, w = h // 32 * 32, w // 32 * 32
-    x1 = torch.nn.functional.interpolate(x1, size=(h, w), mode='bilinear')
+
     return x1
 
 
@@ -37,7 +35,9 @@ def align(x1):
 def predict(img):
     with torch.no_grad():
         image_tensor = torch.from_numpy(img).permute(2, 0, 1).float().unsqueeze(0)
-        image_tensor = align(image_tensor)
+        h, w = image_tensor.shape[-2], image_tensor.shape[-1]
+        h, w = h // 32 * 32, w // 32 * 32
+        image_tensor = torch.nn.functional.interpolate(image_tensor, size=(h, w), mode='bilinear')
         ipt=net_c(image_tensor)
         image_tensor = image_tensor.half()
         ipt = ipt.half()