Update HTML

app.py

@@ -1,6 +1,8 @@
 import io
 from typing import Any, List, Union
 
+from networkx import center
+
 import cv2
 import gradio as gr
 import matplotlib.pyplot as plt
@@ -185,10 +187,29 @@ def analyze_page(
 
 
 with gr.Blocks(fill_height=True) as demo:
-    #gr.Image("/file=data/logo.jpg", height=400, label=None, show_label=False, show_download_button=False)
-    gr.HTML("<h1>OnnxTR OCR Demo</h1>")
-    gr.HTML("<h2>GitHub: <a href='https://github.com/felixdittrich92/OnnxTR'>OnnxTR</a></h2>")
-    gr.HTML("</div>")
+    gr.Markdown(
+        """
+        <p align="center">
+            <img src="https://github.com/felixdittrich92/OnnxTR/raw/main/docs/images/logo.jpg" width="15%">
+        </p>
+
+        <div align="center">
+
+        # OnnxTR OCR Demo
+
+        [![GitHub OnnxTR](https://img.shields.io/badge/GitHub-blue?logo=github)](https://github.com/felixdittrich92/OnnxTR)
+
+        [![PyPI](https://img.shields.io/pypi/v/onnxtr?color=blue)](https://pypi.org/project/onnxtr/)
+
+        </div>
+
+        ## To use this interactive demo for OnnxTR:
+
+        ### 1. Upload a document (PDF, JPG, or PNG)
+        ### 2. Select the model architectures for text detection and recognition you want to use
+        ### 3. Press the "Analyze page" button to process the uploaded document
+        """
+    )
     with gr.Row():
         with gr.Column(scale=1):
             upload = gr.File(label="Upload File [JPG | PNG | PDF]", file_types=["pdf", "jpg", "png"])