Create app.py

app.py

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+import gradio as gr
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+from PIL import Image
+
+# Load processor + model
+processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
+model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwritten")
+
+def ocr_image(image):
+    # Convert to PIL Image if uploaded
+    if not isinstance(image, Image.Image):
+        image = Image.fromarray(image)
+
+    pixel_values = processor(images=image, return_tensors="pt").pixel_values
+    generated_ids = model.generate(pixel_values)
+    text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    return text
+
+demo = gr.Interface(
+    fn=ocr_image,
+    inputs=gr.Image(type="pil"),     # Image upload box
+    outputs=gr.Textbox(label="Extracted Text")  # Show extracted text
+)
+
+if __name__ == "__main__":
+    demo.launch()