From 8580972ec6e3ebee1897901968df196608b3b50e Mon Sep 17 00:00:00 2001 From: Zhedong Zheng Date: Thu, 26 Sep 2024 00:26:04 +0800 Subject: [PATCH] Update README.md --- tutorial/README.md | 23 +++++++++++++++++------ 1 file changed, 17 insertions(+), 6 deletions(-) diff --git a/tutorial/README.md b/tutorial/README.md index a71f1c6..a918c94 100644 --- a/tutorial/README.md +++ b/tutorial/README.md @@ -16,21 +16,32 @@ We could use this tech to help people. Check the great video by Nvidia. (https:/ 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 ## Prerequisites -- Python 3.6 -- GPU Memory >= 4G -- Numpy -- Pytorch 0.3+ (http://pytorch.org/) -- Torchvision from the source +- Install Pytorch from http://pytorch.org/ +- Install required packages +```bash +pip install -r requirements.txt ``` +- [Optional] You may skip it. Usually it comes with pytorch. Install Torchvision from the source +```bash git clone https://github.com/pytorch/vision cd vision python setup.py install ``` +- [Optional] You may skip it. Install apex from the source +```bash +git clone https://github.com/NVIDIA/apex.git +cd apex +python setup.py install --cuda_ext --cpp_ext +``` +Because pytorch and torchvision are ongoing projects. + +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 . + ## Getting started Check the Prerequisites. The download links for this practice are: -- Code: [Practical-Baseline](https://github.com/layumi/Person_reID_baseline_pytorch) +- Code: [ReID-Baseline](https://github.com/layumi/Person_reID_baseline_pytorch) - 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) A quick command line to download Market-1501 is: