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app.py

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+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+from PIL import Image
+import torch
+import gradio as gr
+
+# Load model
+processor = TrOCRProcessor.from_pretrained("microsoft/trocr-large-handwritten")
+model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-large-handwritten")
+
+# Define prediction function
+def recognize_text(image):
+    image = Image.fromarray(image).convert("RGB")
+    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
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=recognize_text,
+    inputs=gr.Image(type="numpy", label="Upload Image"),
+    outputs=gr.Textbox(label="Recognized Text"),
+    title="Handwritten Text Recognition",
+    description="Upload an image of handwritten text to recognize it using TrOCR.",
+    server_name="0.0.0.0",  # Ensure compatibility with Hugging Face GPUs
+    server_port=7860       # Default Gradio port
+)
+
+# Launch interface
+interface.launch(share=True)