{ "info": { "author": "Gate6", "author_email": "vijay.bharati@gate6.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7" ], "description": "# Gate6 Iris Recognition Package\n G6_iris_recognition is a module for eye iris recognition.\n\n## Installation needs before installing package module \n ```\n python \n numpy\n opencv-python\n matplotlib\n opencv-contrib-python\n requests\n scikit-image\n scipy\n imutils==0.5.2\n ``` \n - Create a encodingModel directory & in that directory create a file name irisEncodings.pickle on your project folder (encodingModel/irisEncodings.pickle).\n - Create a Input_database directory & in that directory put person's eye iris images under person's name directory.\n\n\n```shell\n\n Project/\n \u251c\u2500\u2500 encodingModel/\n \u2502 \u251c\u2500\u2500 irisEncodings.pickle/ # train model\n | \n \u251c\u2500\u2500 Input_database/ \n \u2502 \u251c\u2500\u2500 person1 name/ # person1 directory\n | \u2502 \u251c\u2500\u2500 eye iris images of person1 / # images of person eye iris\n \u2502 \u251c\u2500\u2500 person2 name/ # person2 directory\n | \u2502 \u251c\u2500\u2500 eye iris images of person2 / # images of person eye iris\n \u2502 \u251c\u2500\u2500 person3 name/ # person3 directory\n | \u2502 \u251c\u2500\u2500 eye iris images of person3 / # images of person eye iris \n\n```\n## Installation\n\n##### - Install Python\n\n[Windows](http://timmyreilly.azurewebsites.net/python-flask-windows-development-environment-setup/), [Mac](http://docs.python-guide.org/en/latest/starting/install/osx/), [Linux](https://docs.aws.amazon.com/cli/latest/userguide/awscli-install-linux-python.html)\n\n\n##### - Install package module using ``pip``::\n ```\n $ pip install -i https://test.pypi.org/simple/ G6-iris-recognition\n ``` \n\n## Run Project\n\nOnce all the settings of project are configured, you are ready to run your project. To start import G6_iris_recognition module.\n\n```shell\n import G6_iris_recognition\n```\n\nAfter import, need to train existing images and create encoding module once on start :\n\n```shell\n G6_iris_recognition.iris_model_train(train_database_path,train_encoding_model_path)\n train_database_path ===> Input_database/\n train_encoding_model_path ===> encodingModel/irisEncodings.pickle\n```\n\nOnce model is trained then its ready to test with real-time images:\n\n```shell\n iris_name = G6_iris_recognition.iris_model_test(test_encoding_model_path,real_time_image_path) \n test_encoding_model_path ===> encodingModel/irisEncodings.pickle\n real_time_image_path ===> real-time_image_path\n iris_name ===> it returns predicted person name if image matches with trained image model person image & if not then it returns name as unmatch.\n```\n\n\n## Requirements :\n\n * Need clearer images from the scanner.\n * Images shouldn't capture on direct sunlight.\n * Person shouldn't use glass or lens on eye scanning.\n * All scanned images need to be on same shapes/size(eg - 320x240).\n * As per image size and quality/noise, need to change parameter of filters according.\n * 90% above eye iris need to be capture on image taken from scanner.\n * Need min 5 clearer images to train a model.\n * After all this done according, set threshold of Hamming Distance to recognize.\n\n\n\n## Support\n\nIf you face any issue in configuration or usage with Gate6 Iris Recognition Package as per the instruction documented above. 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