Create app.py

app.py

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+import gradio as gr
+from transformers import VisionEncoderDecoderModel, TrOCRProcessor
+from PIL import Image
+
+# Load the model and processor from Hugging Face
+model = VisionEncoderDecoderModel.from_pretrained("paudelanil/devnagari-TrOCR")
+processor = TrOCRProcessor.from_pretrained("paudelanil/devnagari-TrOCR")
+
+def predict(image):
+    # Preprocess the image
+    image = Image.open(image).convert("RGB")
+    pixel_values = processor(image, return_tensors="pt").pixel_values
+    
+    # Generate text from the image
+    generated_ids = model.generate(pixel_values)
+    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    
+    return generated_text
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="filepath"),
+    outputs="text",
+    title="Devanagari OCR with TrOCR",
+    description="Upload an image with Devanagari script and get the text prediction using a pre-trained Vision-Text model."
+)
+
+# Launch the interface
+interface.launch()