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docs/INSTALL.md
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# Installation
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### Requirements
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All the codes are tested in the following environment:
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* Linux (tested on Ubuntu 14.04/16.04/18.04/20.04/21.04)
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* Python 3.6+
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* PyTorch 1.1 or higher (tested on PyTorch 1.1, 1,3, 1,5~1.10)
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* CUDA 9.0 or higher (PyTorch 1.3+ needs CUDA 9.2+)
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* [`spconv v1.0 (commit 8da6f96)`](https://github.com/traveller59/spconv/tree/8da6f967fb9a054d8870c3515b1b44eca2103634) or [`spconv v1.2`](https://github.com/traveller59/spconv) or [`spconv v2.x`](https://github.com/traveller59/spconv)
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### Install `pcdet v0.5`
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NOTE: Please re-install `pcdet v0.5` by running `python setup.py develop` even if you have already installed previous version.
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a. Clone this repository.
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```shell
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git clone https://github.com/open-mmlab/OpenPCDet.git
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```
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b. Install the dependent libraries as follows:
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[comment]: <> (* Install the dependent python libraries: )
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[comment]: <> (```)
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[comment]: <> (pip install -r requirements.txt )
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[comment]: <> (```)
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* Install the SparseConv library, we use the implementation from [`[spconv]`](https://github.com/traveller59/spconv).
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* If you use PyTorch 1.1, then make sure you install the `spconv v1.0` with ([commit 8da6f96](https://github.com/traveller59/spconv/tree/8da6f967fb9a054d8870c3515b1b44eca2103634)) instead of the latest one.
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* If you use PyTorch 1.3+, then you need to install the `spconv v1.2`. As mentioned by the author of [`spconv`](https://github.com/traveller59/spconv), you need to use their docker if you use PyTorch 1.4+.
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* You could also install latest `spconv v2.x` with pip, see the official documents of [spconv](https://github.com/traveller59/spconv).
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c. Install this `pcdet` library and its dependent libraries by running the following command:
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```shell
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python setup.py develop
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```
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