Installation Guide

We strongly recommend you to run the following commands from the system shell or terminal.

DO NOT RUN these commands from any IDE terminal. There are some strange issues especially from PyCharm Terminal

1. Clone Repository (if you clone from github, use this step)

1.1 Clone the repository from github

 git clone git@github.com:YiweiC1W/pedestrians_detection.git

 git clone  https://github.com/YiweiC1W/pedestrians_detection.git

1.2 cd to the directory

 cd pedestrians_detection

1. Unzip Folder (if you downloaded the zip file, use this step)

Unzip the folder

cd into the project root folder (where the README.md is)

2. Create virtual environment

2.1 Create virtual environment

 conda create --name 9517gp python==3.8.13

2.2 Activate the virtual environment

 conda activate 9517gp

3.Run this All-in-One script to install dependencies, YOLOX, Download datasets and pre-trained weights (choose one according to your system)

 sh install_linux.sh # For Linux (Ubuntu 20.04 is recommended) (maybe works on macOS too)

 install_win64.bat # For Windows (not tested)

If you encounter any installation issues, please contact me at yiwei.chen2@student.unsw.edu.au

Run

Arguments

please edit IMAGE_FOLDER_PATH in task1.py

or you can use args '--path' to choose your image folder

'--task' to choose your task eg: '--task 1' or '--task 2'

'--conf' to choose your confidence threshold

'--device' to choose your device 'cpu' or 'gpu'

'--video' bool(true or false), if you want to save video

'--picture' bool(true or false), if you want to save picture

run example

python main.py --task 1 --device cpu

Code Reference

[1] https://github.com/nwojke/deep_sort

[2] https://github.com/Megvii-BaseDetection/YOLOX