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darwin/cli.py

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@@ -43,7 +43,7 @@ def run(args, parser):
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f.list_teams()
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# Version
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elif args.command == "version":
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print("0.5.4")
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print("0.5.5")
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elif args.command == "convert":
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f.convert(args.format, args.files, args.output_dir)

docs/index.md

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@@ -7,7 +7,7 @@ Typical use cases for Darwin include:
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- Create/remove/list datasets
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- Upload/download data to/from remote datasets
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- Convert between annotations formats
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- Direct integration with PyTorch DataLoaders (See [torch/README.md](darwin/torch/README.md))
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- Direct integration with PyTorch DataLoaders (See [torch](torch.md))
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Darwin-py can both be used from the [command line](commandline.md) and as a [python library](library.md).
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docs/torch.md

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```
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## Darwin છ Torchvision
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## Darwin ✕ Torchvision
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This tutorial shows how to train an instance segmentaion model on a Darwin dataset using Pytorch's [Torchvsion](https://github.com/pytorch/vision) and `darwin-py`. If you do not have Pytorch and Torchvision installed yet, you can follow these [installation instructions](https://pytorch.org/get-started/locally/).
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setup.py

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setuptools.setup(
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name="darwin-py",
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version="0.5.4",
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version="0.5.5",
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author="V7",
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author_email="[email protected]",
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description="Library and command line interface for darwin.v7labs.com",

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