Update app.py

app.py

@@ -570,11 +570,25 @@ def rectify_image(distorted_image):
 # --- Gradio Interface ---
 
 DESCRIPTION = """
-# DocScanner: Robust Document Image Rectification with Progressive Learning
-This is a Gradio demo for the DocScanner model. 
-1. Upload a distorted document image.
-2. The model will process it and display the rectified (unwarped) image.
-This demo uses the **DocScanner-L** model as described in the paper. Make sure the pretrained models (`seg.pth`, `DocScanner-L.pth`) are located in the `./model_pretrained/` directory.
+#  DocScanner: Document Image Rectification
+This Space demonstrates DocScanner, a deep learning model that automatically corrects geometric distortions in document images. 
+If you have a photo of a document that is warped, skewed, or has curled edges, this tool can transform it into a flat, 
+top-down, scanner-like image.
+
+This application is an implementation of the research paper: DocScanner: Robust Document Image Rectification with Progressive Learning 
+(https://arxiv.org/abs/2110.14968).
+
+# How to Use
+
+1. Upload an Image: Drag and drop a distorted document image into the input box, or click to browse your files.
+2. Submit: Click the "Submit" button to begin the rectification process.
+3. View the Result: The corrected, flattened document will appear in the output box on the right.
+
+#Technical Details
+
+* Model: This demo uses the DocScanner-L model, as described in the paper.
+* Technology: The application is built with Python, PyTorch, and the Gradio library.
+
 """
 
 if __name__ == "__main__":