| PROJECT DESCRIPTION: | |
| This project is a web application that performs Optical Character Recognition (OCR) For the uploaded images. It supports English and Hindi language. And a Keyword search is available and the word is highlighted. | |
| SOFTWARE REQUIREMENTS: | |
| Python: The program requires Python to run, ideally Python 3.8 or later. | |
| Libraries to be installed: | |
| pip install gradio | |
| pip install transformers | |
| pip install torch | |
| pip install safetensors | |
| pip install pillow | |
| pip install verovio | |
| pip install tiktoken | |
| MODEL INFO: | |
| This application leverages the CPU version of the GOT (General OCR Theory) model for Optical Character Recognition (OCR). The model and tokenizer are sourced from the Hugging Face model hub: | |
| Model: ucaslcl/GOT-OCR2_0 Tokenizer: ucaslcl/GOT-OCR2_0 While the code includes provisions for running the model on a GPU, this implementation exclusively uses the CPU version due to the constraints of the Hugging Face deployment environment. As a result, processing times may be slower compared to a GPU-enabled setup. However, using the CPU ensures compatibility across a broader range of systems, particularly those without access to a GPU | |
| USEAGE: | |
| 1.Set the code in the Google colab and download the prerequisites libraries and run the code. Then upload the image and type the search keyword and output is visible. | |
| 2.Clone the GitHub repository |