Update app.py

app.py

@@ -204,14 +204,17 @@ def model_process(input):
     torch.cuda.empty_cache()
 
     if alpha_channel is not None:
+        print(f"liuyz_here_10_: {alpha_channel.shape}")
         if alpha_channel.shape[:2] != res_np_img.shape[:2]:
+            print(f"liuyz_here_20_: {alpha_channel.shape} / {res_np_img.shape}")
             alpha_channel = cv2.resize(
                 alpha_channel, dsize=(res_np_img.shape[1], res_np_img.shape[0])
             )
+            print(f"liuyz_here_30_: {alpha_channel.shape} / {res_np_img.shape}")
         res_np_img = np.concatenate(
             (res_np_img, alpha_channel[:, :, np.newaxis]), axis=-1
         )
-    print(f"process time_2_: {(time.time() - start) * 1000}ms, {res_np_img.shape} / {res_np_img[250][250]}")
+    print(f"process time_2_: {(time.time() - start) * 1000}ms, {alpha_channel.shape}, {res_np_img.shape} / {res_np_img[250][250]}")
     image = Image.fromarray(res_np_img)
     image.save(f'./result_image.png')
     return image