Update app.py

app.py

@@ -9,7 +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)
+# model = torch.jit.load(model_path)
 
 charset = r"0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 _tokenizer = Tokenizer(charset)
@@ -24,14 +24,14 @@ 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="filepath", label="captcha image")
+text = gr.Textbox(label="recognized character sequence")
 
 
 def recognize_captcha(image_path):
     input = Image.open(image_path)
     input = transform(input.convert('RGB')).unsqueeze(0)
-    model = model
+    model = torch.jit.load(model_path)
     with torch.no_grad():
          probs   = model(input)
          preds,_ =  _tokenizer.decode(probs,beam_width=2)
@@ -41,8 +41,8 @@ iface = gr.Interface(
     fn=recognize_captcha,
     inputs=image,
     outputs=text,
-    title="Character Sequence Recognition from Scene-Image (Captcha)",
-    description="Recognize captchas using different models",
+    title="character sequence recognition from scene-image (captcha)",
+    description="recognize captchas ",
     examples=['examples/251615.png']
 )