https://github.com/arnabd64/pytesseract-api
Microservice for Tesseract OCR service
https://github.com/arnabd64/pytesseract-api
computer-vision machine-learning microservice pytesseract-ocr tesseract
Last synced: 5 months ago
JSON representation
Microservice for Tesseract OCR service
- Host: GitHub
- URL: https://github.com/arnabd64/pytesseract-api
- Owner: arnabd64
- License: apache-2.0
- Created: 2025-01-10T06:40:41.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-10T10:35:55.000Z (about 1 year ago)
- Last Synced: 2025-01-30T02:16:13.783Z (about 1 year ago)
- Topics: computer-vision, machine-learning, microservice, pytesseract-ocr, tesseract
- Language: Python
- Homepage:
- Size: 10.7 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# PyTesseract Microservice
## Objective
The objective of this project is to create a robust and scalable microservice for Optical Character Recognition (OCR) using PyTesseract. This microservice is designed to be easily deployable using Docker, making it suitable for any cloud environment.
## Deploy
To deploy this microservice, follow these steps:
1. **Clone the Git Repository:**
First, clone the git repository to your server:
```sh
git clone https://github.com/arnabd64/PyTesseract-API.git
cd PyTesseract-API
```
2. **Build and Run the Docker Container:**
You can build the Docker container and run it using the following commands:
```sh
docker build -t pytesseract:latest .
docker run -itd --name=pytesseract -p 8000:8000 pytesseract:latest
```
This will build the Docker image with the tag `pytesseract:latest` and run a container named `pytesseract` that maps port 8000 of the container to port 8000 of the host.
3. **Use Docker Compose:**
Alternatively, you can use Docker Compose to build and run the microservice. Ensure you have Docker Compose installed, then run:
```sh
docker compose up --build -d
```
This command will build the Docker image and start the container in detached mode using the configurations specified in the `docker-compose.yml` file.
## Additional Information
- **Dependencies:** Ensure that Docker and Docker Compose are installed on your server.
- **Configuration:** You can customize the microservice by modifying the configuration files within the repository.
- **Scalability:** This microservice is designed to be scalable. You can deploy multiple instances behind a load balancer for high availability and performance.
For any issues or enhancements, feel free to open an issue or submit a pull request.
Happy coding!