Update README.md

README.md

@@ -12,9 +12,9 @@ short_description: An OCR application integrated with GOT OCR 2.0
 
 <mark>OCR Model Integration Using Gradio:</mark>
 
-####This project integrates a pre-trained OCR (Optical Character Recognition) model with a Gradio-based web interface. Users can upload an image (JPEG format), extract the text using the model, and search for specific keywords in the extracted text. The keywords are highlighted within the displayed results.
+**This project integrates a pre-trained OCR (Optical Character Recognition) model with a Gradio-based web interface. Users can upload an image (JPEG format), extract the text using the model, and search for specific keywords in the extracted text. The keywords are highlighted within the displayed results.**
 
-###dependencies / libraries required: 
+**dependencies / libraries required:**
 torch
 transformers
 gradio
@@ -27,28 +27,28 @@ accelerate
 
 all these libraries are included in requirements.txt to install them : pip install -r requirements.txt
 
-####ALSO this model requires a GPU to run , so make sure you have NVIDIA CUDA or similar technologies.
+**ALSO this model requires a GPU to run , so make sure you have NVIDIA CUDA or similar technologies.**
 
 The current web page is running on the hugging face space which is using paid GPU that is Nvidia T4 medium. 
 
 
-##Project Overview
+**Project Overview**
 OCR Model: This project uses the GOT-OCR 2.0 model from Hugging Face.
 Frontend: The frontend is built using Gradio, which provides an easy-to-use web interface.
 Keyword Search: Users can search for specific keywords in the extracted text. The search is case-insensitive, and the matching keywords are highlighted using HTML <mark> tags with customizable colors.
 
-##Model Description
+**Model Description**
 The project uses a pre-trained OCR model from Hugging Face:
 
-####Model Name: GOT-OCR 2.0
+**Model Name: GOT-OCR 2.0**
 Architecture: Transformer-based model, fine-tuned for Optical Character Recognition.
 Framework: Hugging Face's transformers library.
 The model is loaded using the AutoTokenizer and AutoModel classes from Hugging Face and runs on a CUDA-enabled device.
 
-##Gradio Web Interface
+**Gradio Web Interface**
 The project uses Gradio to create an easy-to-use web interface for interacting with the model. The interface allows users to upload images, extract text, and search for keywords in the extracted text.
 
-##Gradio Setup
+**Gradio Setup**
 Image Upload: The user uploads an image, and the text is extracted using the OCR model.
 Keyword Search: Users input a keyword to search within the extracted text.
 Highlighting: Keywords found in the text are highlighted with a customizable color using HTML <mark> tags