Update app.py

app.py

@@ -9,9 +9,7 @@ TOKEN = os.getenv('hf_read_token')
 repo_id    = "Nischay103/captcha_recognition"
 model_file = 'captcha_model.pt'
 model_path = hf_hub_download(repo_id=repo_id, filename=model_file, token=TOKEN)
-# model = torch.jit.load(model_path)
-
-charset = r"0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+charset    = r"0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 _tokenizer = Tokenizer(charset)
 
 def get_transform(img_size=(32,128)):
@@ -24,9 +22,8 @@ def get_transform(img_size=(32,128)):
     return T.Compose(transforms)
 
 transform = get_transform()
-image = gr.Image(type="filepath", label="captcha image")
-text = gr.Textbox(label="recognized character sequence")
-
+image = gr.Image(type="pil", label="captcha image")
+text  = gr.Textbox(label="recognized character sequence")
 
 def recognize_captcha(image_path):
     input = Image.open(image_path)
@@ -38,13 +35,13 @@ def recognize_captcha(image_path):
     return preds[0]
 
 iface = gr.Interface(
-    fn=recognize_captcha,
-    inputs=image,
-    outputs=text,
-    title="character sequence recognition from scene-image (captcha)",
-    description="recognize captchas ",
-    examples=['examples/251615.png','examples/e7dx2r.jpg','examples/980209.png','examples/2DMM4.png',
-              'examples/H1GQD.png','examples/Sv5Cwm.jpg','examples/Wwx7.png','examples/qw7vr.png']
+    fn = recognize_captcha,
+    inputs = image,
+    outputs= text,
+    title  = "character sequence recognition from scene-image (captcha)",
+    description = "recognize captchas ",
+    examples = ['examples/251615.png','examples/e7dx2r.jpg','examples/980209.png','examples/2DMM4.png',
+               'examples/H1GQD.png','examples/Sv5Cwm.jpg','examples/Wwx7.png','examples/qw7vr.png']
 )
 
 iface.launch()