Create app.py

app.py

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+import gradio as gr
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+from PIL import Image
+import torch
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Load the model
+processor = TrOCRProcessor.from_pretrained("microsoft/trocr-large-handwritten")
+model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-large-handwritten").to(device)
+
+def ocr_infer(image):
+    pixel_values = processor(images=image, return_tensors="pt").pixel_values.to(device)
+    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=ocr_infer,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Image to Text (OCR)",
+    description="Upload a handwritten or printed image to extract text using TrOCR."
+)
+
+iface.launch()