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        "author": "Rob McDiarmid",
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        "description": "# Keras MRI\nKeras MRI is a neural network visualization tool for Keras. This is still in Beta and some networks (e.g. RNNs and 3D CNNs) and types of layers are not yet supported.\n\n# Install\n\n```sh\npip install keras-mri\n```\n\n# Usage\n\n```python\nimport kmri\n\nfrom keras.models import Sequential\nfrom keras.layers import Dense\n\nmodel = Sequential([\n    Dense(8, input_shape=(3,))\n])\n\ninput_batch = [[1,2,3], [7,8,9]]\nkmri.visualize_model(model, input_batch)\n```\n\nOnce this is running navigate to [http://127.0.0.1:5000/](http://127.0.0.1:5000/)\n\n# Examples\n\nThe examples folder contains models that demonstrate keras-mri usage. To run one of the examples run the following from one of the example folders\n\n```sh\npip install -r requirements.txt\npython main.py\n```\n\n[**chrome-dino**](examples/chrome-dino/main.py)\n\nSimple reinforcement learning model that learned to play the dinosaur game in chrome. Demonstrates visualizing a convolutional neural network with multiple inputs. This is based on [chrome-dino-ai](https://github.com/robianmcd/chrome-dino-ai).\n\n ![network](examples/chrome-dino/network.gif)\n\n\n[**img-classifier**](examples/img-classifier/main.py)\n\nDemonstrates using keras-mri to visualize standard image classifieres (VGG, MobileNet, and ResNet). \n\n ![network](examples/img-classifier/network.png)\n\n# Development\n\n**Install package locally**\n\n```\npip install -e .\n```\n\n**Deploy**\n\n```\n# increase version number in setup.py\n# Move unrelease changes to next version in changelog.md\n# commit, tag with vx.x.x, and push\n# Delete build, dist, and egg-info\npython setup.py sdist bdist_wheel\npython -m twine upload dist/*\n```\n\n\n",
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