Update app.py

app.py

@@ -39,7 +39,7 @@ def solve_captcha(data_bytes: bytes = None, file_name: str = None):
         return answ, accuracy
 
 
-    def decode_img_bytes(data_bytes: bytes):
+    def decode_img(data_bytes: bytes):
         # same actions, as for tensorflow
         image = cv2.imdecode(np.asarray(bytearray(data_bytes), dtype=np.uint8), 1)
         image: "np.ndarray" = image.astype(np.float32) / 255.
@@ -50,7 +50,7 @@ def solve_captcha(data_bytes: bytes = None, file_name: str = None):
         image = np.array([image])
         return image
         
-    def decode_img(nump_array):
+    def decode_img_array(nump_array):
         # same actions, as for tensorflow
         #image = cv2.imdecode(nump_array, 1)
         image: "np.ndarray" = nump_array.astype(np.float32) / 255.
@@ -79,11 +79,13 @@ def solve_captcha(data_bytes: bytes = None, file_name: str = None):
 def image_classifier(inp):
     if inp is None:
         return "Не загружена картинка"
-    print('INPUT GOT>>>', inp.dtype)
+    print('INPUT GOT>>>', inp)
     #gradio img inp - numpy ndarray
-    
-    result = solve_captcha(inp)
+    img_byte_arr = io.BytesIO()
+    inp.save(img_byte_arr, format='PNG')
+    img_byte_arr = img_byte_arr.getvalue
+    result = solve_captcha(img_byte_arr)
     return result
 #gr.Image(type="pil"),
-demo = gr.Interface(fn=image_classifier, inputs="image", outputs="label")
+demo = gr.Interface(fn=image_classifier, inputs= gr.Image(type="pil"), outputs="label")
 demo.launch()