Create python app.py

python app.py

@@ -0,0 +1,40 @@
+from flask import Flask, request
+import gradio as gr
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+from PIL import Image
+import requests
+import io
+
+# Initialize Flask app
+app = Flask(__name__)
+
+# Load the processor and model
+processor = TrOCRProcessor.from_pretrained('microsoft/trocr-large-handwritten')
+model = VisionEncoderDecoderModel.from_pretrained('microsoft/trocr-large-handwritten')
+
+def recognize_handwritten_text(image):
+    # Preprocess the image
+    pixel_values = processor(images=image, return_tensors="pt").pixel_values
+
+    # Generate text
+    generated_ids = model.generate(pixel_values)
+    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+
+    return generated_text
+
+def capture_image(image):
+    # Convert the image to PIL format
+    image = Image.open(io.BytesIO(image))
+    # Recognize handwritten text
+    text = recognize_handwritten_text(image)
+    return text
+
+# Create Gradio interface
+iface = gr.Interface(fn=capture_image, inputs="image", outputs="text", live=True)
+
+@app.route('/capture', methods=['GET'])
+def capture():
+    return iface.launch(share=True)
+
+if __name__ == '__main__':
+    app.run(debug=True)