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        "author": "Rickard Sjoegren",
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            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
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        "description": "# darwin-pytorch\n\nThis is a small package for interfacing [V7Lab](https://www.v7labs.com/)'s annotation tool \n[Darwin](https://darwin.v7labs.com) with [Pytorch](https://pytorch.org/). \n\n## Quick start\n\n### Install Pytorch\n\nFirst [install your preferred version of Pytorch](https://pytorch.org/get-started/locally/) including `torchvision`.\n\n### Install darwin-pytorch\nThen use pip to install `darwin-pytorch`:\n\n```\npip install darwin_pytorch\n```\n\n## Examples\n\n### Loading annotations\n\n`darwin-pytorch` provides a high-level wrapper around \n[`darwin-cli`](https://github.com/v7labs/darwin-cli) for \nloading datasets from Darwin. \n\nExample of authenticating and downloading an annotated dataset:\n\n```\nimport darwin_pytorch\n# Checks for DARWIN_PASSWORD environment variable, if this is not found the user\n# will be prompted for password.\nclient = darwin_pytorch.DarwinClient('me@email.com')\ndata_path = client.download_dataset('dataset-name')  # Downloads data and returns root-path.\n```\n\n### Dataset\n\n`darwin-pytorch` also provides a Pytorch `Dataset` wrapping a dataset downloaded from Darwin. Example use:\n\n```\nds = darwin_pytorch.DarwinDataset(data_path)\nds[0]       # --> (PIL.Image, target-int)\nds[:2]      # --> [(PIL.Image, target-int), (PIL.Image, target-int))]\nds[[0, 3]]  # --> [(PIL.Image, target-int), (PIL.Image, target-int)]\n```\n\n**Please note**, so far only binary classification datasets are supported.\n\n## License\n\n`darwin-pytorch` is MIT-style license as found in the LICENSE file.",
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