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deployed [here](https://ocrweb.herokuapp.com)soon.\n\nThe basic functionality of the application is demonstrated in [this video](https://drive.google.com/open?id=0B2KDY9irUBbcbGlpc2tRRkJFR3c)\n\n## Usage Instructions\n### Prerequisites\n* leptonica\n\n* tesseract\n\n* node\n\n* npm\n\nInstructions for contributing can be found -\u003e [CONTRIBUTING.md](https://github.com/pvgupta24/OCR-Web-App/blob/master/CONTRIBUTING.md) file.\n\n### Installing Dependencies\n* Clone this repository .\n\n* Run `npm install` in the root directory to install the dependencies.\n\n* Change to `public` directory and build the Angular app.\n\n* Run `npm start` from the root directory.\n\n* The app is now available at `http://localhost:3000`\n\n## Tools and Frameworks used\n### Front end\n* Bootstrap\n\n* AngularJS\n\n### Server side\n* Nodejs (with Express)\n\n* Node Tesseract : Used as a wrapper for using the tesseract API's for the Node Platform\n\n* Fred's ImageMagicks textcleaner `Bash` scripts : To enhancing the image and reducing noisefor better read.\n\n* Tesseract OCR Engine\n\n* Multer : For managing the uploaded image files (Node)\n\n## Limitations\n* As of now, it is implemented to recognize only English characters.\n\n* Though the Tesseract-OCR engine is powerful, there is a limitation to its performance.\n\n\n## Future additions\n- [x] Reduce noise in the uploaded image (Clean).\n- [ ] Display the cleaned image in front-end.\n- [ ] Use multipart formdata to upload files through Angular HTTP Request(and add other processing functionalities).\n- [ ] Copy text to be implemented using ngClipboard angular directive.\n- [ ] Retrieve text from multiple images in a single request.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpvgupta24%2Focr-web-app","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpvgupta24%2Focr-web-app","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpvgupta24%2Focr-web-app/lists"}