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3.6](https://img.shields.io/badge/python-3.6-blue.svg)\n\nA real time digit recognizer using machine learning and OpenCV\n\n\n\nWe will first create single digit rercognition in ```RealTimeDigitRecognition.ipynb``` and then multidigit recognition in ```RealTimeMultiDigitRecognition.ipynb```\n\n# Final output in ```RealTimeMultiDigitRecognition.ipynb``` will be\n\n\u003cp align=\"center\"\u003e\n  \u003cimg width=\"460\" height=\"300\" src=\"https://user-images.githubusercontent.com/42001739/82968228-71e1ab80-9fea-11ea-8c55-53d5cdcc97d8.gif\"\u003e\n\u003c/p\u003e\n\n\n\n\nFirst we need to train the model in ```RealTimeDRTraining.ipynb```.\n\nWe required the dataset for training which is ```Data.zip``` extract it in the same folder where you have all the files.\n\nAnd Train the model.\n\nBut if you dont want to train and directly test,the model is still provided to be used directly.\n\nTo test the model use ```RealTimeDigitRecognition.ipynb```\n\nFirst we will create a normal real time detection without bounded boxes\n\n\u003cp align=\"center\"\u003e\n  \u003cimg width=\"460\" height=\"300\" src=\"https://user-images.githubusercontent.com/42001739/82623233-47b07800-9bfd-11ea-9c97-ebe53a8d4a09.PNG\"\u003e\n\u003c/p\u003e\n\nThen we will add bounded boxes and ouput will be as shown below.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg width=\"460\" height=\"300\" src=\"https://user-images.githubusercontent.com/42001739/82623109-061fcd00-9bfd-11ea-9879-eb3437e5b5f3.png\"\u003e\n\u003c/p\u003e\n\n## Changes Required:\n~~- Bounded Boxes accuracy needs to be increased~~\n\n## All changes updated and created MultiDigit Recognition ipynb file\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharshoza36%2Frealtime_digitrecognizer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fharshoza36%2Frealtime_digitrecognizer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharshoza36%2Frealtime_digitrecognizer/lists"}