Update README.md

README.md

@@ -1,12 +1,24 @@
-# ocrd
-Optical Character Recognition Digitization
-
-## Acknowledgements and Attributions
-
-This project makes use of significant components from the following open-source projects:
-
-- **eynollah**: An automated layout analysis tool for historical documents, developed as part of the QURATOR project. The eynollah tool is instrumental in facilitating the preprocessing of document images in our project. For more details on eynollah, visit their GitHub repository: [qurator-spk/eynollah](https://github.com/qurator-spk/eynollah). The tool is used under the Apache License 2.0.
-
-- **Microsoft trocr**: I utilize Microsoft's trocr models for optical character recognition tasks. The trocr models are highly effective in recognizing text from a variety of document types. For more information on trocr and its usage, please see [Microsoft's trocr repository](https://github.com/microsoft/unilm) under the MIT License.
-
-I appreciate the efforts of the developers and the community in providing these high-quality open-source resources.
+---
+title: OCDR Demo
+emoji: 🧐
+colorFrom: blue
+colorTo: red
+sdk: gradio
+sdk_version: 4.26.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+---
+
+# ocrd
+Optical Character Recognition Digitization
+
+## Acknowledgements and Attributions
+
+This project makes use of significant components from the following open-source projects:
+
+- **eynollah**: An automated layout analysis tool for historical documents, developed as part of the QURATOR project. The eynollah tool is instrumental in facilitating the preprocessing of document images in our project. For more details on eynollah, visit their GitHub repository: [qurator-spk/eynollah](https://github.com/qurator-spk/eynollah). The tool is used under the Apache License 2.0.
+
+- **Microsoft trocr**: I utilize Microsoft's trocr models for optical character recognition tasks. The trocr models are highly effective in recognizing text from a variety of document types. For more information on trocr and its usage, please see [Microsoft's trocr repository](https://github.com/microsoft/unilm) under the MIT License.
+
+I appreciate the efforts of the developers and the community in providing these high-quality open-source resources.