Update app.py

app.py

@@ -234,6 +234,8 @@ def model_process_filepath(input): #image, mask):
     print(f'origin_image_bytes = ', type(origin_image_bytes), len(origin_image_bytes))
 
     image, alpha_channel = load_img(origin_image_bytes)
+    
+    alpha_channel = (np.ones((image.shape[0],image.shape[1]))*255).astype(np.uint8)
     original_shape = image.shape
     interpolation = cv2.INTER_CUBIC
 
@@ -284,7 +286,7 @@ def model_process_filepath(input): #image, mask):
     logger.info(f"Resized image shape: {image.shape} / {type(image)}")
     print(f"Resized image shape: {image.shape} / {image[250][250]}")
 
-    mask, alpha_channel = load_img(read_content(input["mask"]), gray=True)
+    mask, _ = load_img(read_content(input["mask"]), gray=True)
     mask = resize_max_size(mask, size_limit=size_limit, interpolation=interpolation)
     print(f"mask image shape: {mask.shape} / {type(mask)} / {mask[250][250]} / {alpha_channel}")
 
@@ -310,7 +312,8 @@ def model_process_filepath(input): #image, mask):
             (res_np_img, alpha_channel[:, :, np.newaxis]), axis=-1
         )
         print(f"liuyz_here_40_: {alpha_channel.shape} / {res_np_img.shape} / {alpha_channel.dtype} / {res_np_img.dtype}")
-    print(f"process time_2_: {(time.time() - start) * 1000}ms, {alpha_channel.shape}, {res_np_img.shape} / {res_np_img[250][250]} / {res_np_img.dtype}")
+    ext = get_image_ext(origin_image_bytes)
+    print(f"process time_2_: {(time.time() - start) * 1000}ms, {alpha_channel.shape}, {res_np_img.shape} / {res_np_img[250][250]} / {res_np_img.dtype} /{ext}")
   
     image = Image.fromarray(res_np_img)
     image.save(f'./result_image.png')