conda compatibility update
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README.md
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@@ -21,7 +21,9 @@ Alternatively, to install from source do:
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pip install git+https://github.com/andreped/livermask.git
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```
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As TensorFlow 2.4 only supports Python 3.6-3.8, so does livermask.
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(Optional) To add GPU inference support for liver vessel segmentation (which uses Chainer and CuPy), you need to install [CuPy](https://github.com/cupy/cupy). This can be easily done by adding `cupy-cudaX`, where `X` is the CUDA version you have installed, for instance `cupy-cuda110` for CUDA-11.0:
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```
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pip install --force-reinstall --no-deps git+https://github.com/andreped/livermask.git
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```
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If you get the issue `ImportError: numpy.core.multiarray failed to import`, it might be because you tried to use [conda](https://docs.conda.io/en/latest/) instead of pip for installing. livermask is not made to be compatible with Conda. Please, use pip. See [this thread](https://github.com/andreped/livermask/issues/12) for more information.
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## Acknowledgements
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If you found this tool helpful in your research, please, consider citing it:
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<pre>
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pip install git+https://github.com/andreped/livermask.git
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```
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As TensorFlow 2.4 only supports Python 3.6-3.8, so does livermask. Software
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is also compatible with Anaconda. However, best way of installing livermask is using `pip`, which
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also works for conda environments.
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(Optional) To add GPU inference support for liver vessel segmentation (which uses Chainer and CuPy), you need to install [CuPy](https://github.com/cupy/cupy). This can be easily done by adding `cupy-cudaX`, where `X` is the CUDA version you have installed, for instance `cupy-cuda110` for CUDA-11.0:
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```
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pip install --force-reinstall --no-deps git+https://github.com/andreped/livermask.git
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```
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## Acknowledgements
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If you found this tool helpful in your research, please, consider citing it:
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<pre>
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