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tutorial/README.md

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@@ -16,21 +16,32 @@ We could use this tech to help people. Check the great video by Nvidia. (https:/
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Person re-identification, 行人重识别, 人の再識別, 보행자 재 식별, Réidentification des piétons, Ri-identificazione pedonale, Fußgänger-Neuidentifizierung, إعادة تحديد المشاة, Re-identificación de peatones
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## Prerequisites
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- Python 3.6
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- GPU Memory >= 4G
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- Numpy
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- Pytorch 0.3+ (http://pytorch.org/)
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- Torchvision from the source
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- Install Pytorch from http://pytorch.org/
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- Install required packages
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```bash
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pip install -r requirements.txt
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```
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- [Optional] You may skip it. Usually it comes with pytorch. Install Torchvision from the source
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```bash
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git clone https://github.com/pytorch/vision
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cd vision
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python setup.py install
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```
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- [Optional] You may skip it. Install apex from the source
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```bash
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git clone https://github.com/NVIDIA/apex.git
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cd apex
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python setup.py install --cuda_ext --cpp_ext
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```
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Because pytorch and torchvision are ongoing projects.
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Here we noted that our code is tested based on Pytorch 0.3.0/0.4.0/0.5.0/1.0.0 and Torchvision 0.2.0/0.2.1 .
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## Getting started
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Check the Prerequisites. The download links for this practice are:
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- Code: [Practical-Baseline](https://github.com/layumi/Person_reID_baseline_pytorch)
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- Code: [ReID-Baseline](https://github.com/layumi/Person_reID_baseline_pytorch)
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- Data: [Market-1501](http://188.138.127.15:81/Datasets/Market-1501-v15.09.15.zip) [[Google]](https://drive.google.com/file/d/0B8-rUzbwVRk0c054eEozWG9COHM/view) [[Baidu]](https://pan.baidu.com/s/1ntIi2Op)
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A quick command line to download Market-1501 is:

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