Upload app.py

app.py

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+import os,torch
+import gradio as gr
+from PIL import Image
+from torchvision import transforms as T
+from huggingface_hub import hf_hub_download
+from tokenizer import Tokenizer
+
+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"
+_tokenizer = Tokenizer(charset)
+
+def get_transform(img_size=(32,128)):
+    transforms = []
+    transforms.extend([
+        T.Resize(img_size, T.InterpolationMode.BICUBIC),
+        T.ToTensor(),
+        T.Normalize(0.5, 0.5)
+    ])
+    return T.Compose(transforms)
+
+transform = get_transform()
+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
+    with torch.no_grad():
+         probs   = model(input)
+         preds,_ =  _tokenizer.decode(probs,beam_width=2)
+    return preds[0]
+
+iface = gr.Interface(
+    fn=recognize_captcha,
+    inputs=image,
+    outputs=text,
+    title="Character Sequence Recognition from Scene-Image (Captcha)",
+    description="Recognize captchas using different models",
+    examples=['examples/251615.png']
+)
+
+iface.launch()