vaimdev / porcupyne

Image-to-text microservice to easily and effectively extract text from a given image. Built with Tesseract, FastAPI & Docker. 🚀

Porcupyne

Image-to-text OCR microservice built with Python using FastAPI and Tesseract
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Table of Contents

1. About The Project
   • Built With
2. Usage
3. Getting Started
   • Prerequisites
   • Installation
4. Contributing

About The Project

Porcupyne is an image-to-text microservice, powered by Google Tesseract OCR, that can be easily incorporated in any application via a simple-to-use API built with FastAPI. The whole microservice is containerized using Docker, making it easier for anyone to set up a local copy and bend it to their needs.

The microservice also cleans and processes the uploaded images with OpenCV; improving the OCR predictions of the Tesseract model.

Built With

• Python
• FastAPI
• Tesseract OCR
• Docker

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Usage

It's extremely easy to use the Porcupyne OCR service. One simply needs to upload an image file they want converted via an HTTP POST request to https://porcupyne.herokuapp.com/convert/ and a JSON response with the results obtained after applying OCR will be recieved back.

The request body will be of the form of a multipart form.

You can use your preffered API client to test it out. Example Python usage is also provided below:

  python3 -m pip install requests

  import requests

  url = "https://porcupyne.onrender.com/convert"
  img_path = "/downloads/img.png"
  files = {"file": open(img_path, "rb")}

  response = requests.post(url, files=files)

  if response.status_code == 200:
    print(response.json())

Output:

{
	"results": {
		"raw": "It was the best of\ntimes, it was the worst\nof times, it was the age\nof wisdom, it was the\nage of foolishness...\n\f",
		"cleaned": "It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness...",
		"lines": [
			"It was the best of",
			"times, it was the worst",
			"of times, it was the age",
			"of wisdom, it was the",
			"age of foolishness...",
			"\f"
		]
	}
}

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

Install Docker. Instructions can be found here in the official docs.

Installation

1. Clone the repo

   git clone https://github.com/outoflaksh/porcupyne.git

2. Change into the base directory.

   cd porcupyne

3. Build the Docker image.

   docker build -t porcupyne .

4. Run the Docker container.

   docker run porcupyne

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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