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app.py

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+import gradio as gr
+from transformers import VisionEncoderDecoderModel, TrOCRProcessor
+import torch
+from PIL import Image
+
+def recognize_captcha(input, mdl):
+    
+    # Load model and processor
+    processor = TrOCRProcessor.from_pretrained(mdl)
+    model = VisionEncoderDecoderModel.from_pretrained(mdl)
+    
+    # Prepare image
+    pixel_values = processor(input, return_tensors="pt").pixel_values
+
+    # Generate text
+    generated_ids = model.generate(pixel_values)
+    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    
+    return generated_text
+
+iface = gr.Interface(
+    fn=recognize_captcha,
+    inputs=[
+        gr.Image(),
+        gr.Dropdown(
+            ['anuashok/ocr-captcha-v3','anuashok/ocr-captcha-v2','anuashok/ocr-captcha-v1','microsoft/trocr-base-printed'], label='Model to use'
+        )
+    ],
+    outputs=['text'],
+    title  = "Character Sequence Recognition From Captcha Image",
+    description = "Using some TrOCR models found on the HF Hub to test/break tough text captchas. Will you have to train your own?",
+    article="Created by Neeraj with ❤️ !!!"
+)
+
+iface.queue(max_size=10)
+iface.launch()

gitattributes

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requirements.txt

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+gradio
+torch
+transformers