4

app.py

@@ -31,8 +31,9 @@ class Pipe:
             image_tensor = torch.from_numpy(img).permute(2, 0, 1).float().unsqueeze(0)
             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=self.net_c(image_tensor.cuda())
+            image_tensor = torch.nn.functional.interpolate(image_tensor, size=(h, w), mode='bilinear').cuda()
+            
+            ipt=self.net_c(image_tensor)
             image_tensor = image_tensor.half()
             ipt = ipt.half()
             output_i, output_j=self.net_i(image_tensor,ipt,prompt=True)