Create app.py

app.py

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+import gradio as gr
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+from PIL import Image
+import requests
+
+# Load the TrOCR model and processor
+processor = TrOCRProcessor.from_pretrained('microsoft/trocr-large-printed')
+model = VisionEncoderDecoderModel.from_pretrained('microsoft/trocr-large-printed')
+
+def extract_text_from_image(image_url):
+    image = Image.open(requests.get(image_url, stream=True).raw).convert("RGB")
+    pixel_values = processor(images=image, return_tensors="pt").pixel_values
+    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
+gr.Interface(
+    fn=extract_text_from_image,
+    inputs=gr.Textbox(label="Enter image URL:"),
+    outputs=gr.Textbox(label="Extracted Text"),
+    title="Text Extraction from Images",
+    description="Extract text from an image using optical character recognition (OCR).",
+).launch()