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Clean up installation instructions #10

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README: Keep installation instructions in one list
larryv Feb 3, 2021
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README: Improve example shell commands
larryv Feb 3, 2021
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46 changes: 23 additions & 23 deletions README.md
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Expand Up @@ -10,38 +10,38 @@ Understanding interactions between humans and objects is one of the fundamental
## Installation
- Clone this repository. This repository is mainly based on [CenterNet](https://github.com/xingyizhou/CenterNet) and [iCAN](https://github.com/vt-vl-lab/iCAN).

```Shell
IPNet_ROOT=/path/to/clone/IPNet
git clone https://github.com/vaesl/IP-Net $IPNet_ROOT
```
```Shell
IPNet_ROOT=/path/to/clone/IPNet
git clone https://github.com/vaesl/IP-Net "$IPNet_ROOT"
```
- The code was tested on Ubuntu 18.04, with [Anaconda](https://www.anaconda.com/download) Python 3.6 and [PyTorch]((http://pytorch.org/)) v1.0.1.
NVIDIA GPUs are needed for testing. After install Anaconda, create a new conda environment, activate the environment and install pytorch1.0.1.

```Shell
conda create -n IPNet python=3.6
source activate IPNet
conda install pytorch=1.0.1 torchvision -c pytorch
```
```Shell
conda create -n IPNet python=3.6
source activate IPNet
conda install pytorch=1.0.1 torchvision -c pytorch
```

- Install the requirements.
```Shell
pip3 install -r requirements.txt
```
```Shell
pip3 install -r requirements.txt
```
- Compiling Center Pooling Layers.
```Shell
cd IPNet_ROOT/src/lib/models/networks/py_utils/_cpools/
python setup.py install --user
```
```Shell
cd "$IPNet_ROOT"/src/lib/models/networks/py_utils/_cpools/
python setup.py install --user
```

- Install [COCOAPI](https://github.com/cocodataset/cocoapi):

~~~
# COCOAPI=/path/to/clone/cocoapi
git clone https://github.com/cocodataset/cocoapi.git $COCOAPI
cd $COCOAPI/PythonAPI
make
python setup.py install --user
~~~
```Shell
COCOAPI=/path/to/clone/cocoapi
git clone https://github.com/cocodataset/cocoapi.git "$COCOAPI"
cd "$COCOAPI"/PythonAPI
make
python setup.py install --user
```

## Download
To evaluate the performance reported in the paper, V-COCO and HICO-DET dataset as well as our trained models need to be downloaded.
Expand Down