Installation of target detection yolov5

learn better from others,

be the better one.

—— "Weika Zhixiang"

The length of this article is 1108 words , and it is expected to read for 4 minutes

foreword

Target detection yolov5 is still used more, this article is a brief introduction to the installation of yolov5.

Installation Environment

System: Windows

Environment: MiniConda

Download the source code of yolov5

Source address: https://github.com/ultralytics/yolov5

Created a yolov5 folder locally and downloaded it directly.

Create and activate a virtual environment

Open Anaconda Powershell Prompt (miniconda3)

Create a virtual environment, here I have created it before, so only the creation code is listed

conda create -n your_env_name python=x.x -y  
# 我的是
conda create -n yolov5 python=3.9 -y

Activate the current virtual environment

conda activate yolov5

As you can see from the above picture, after activation, the front becomes yolov5

Install required third-party libraries

First enter the folder where we downloaded yolov5

Then enter at the command line

pip install -r requirement.txt

It can also be the installation of the mirror image below, which will be faster, but my network speed is problematic, I have installed it many times, and finally it is finished

pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple

Download the pretrained model file

Model file address:

https://github.com/ultralytics/yolov5/releases/tag/v7.0

It has been updated to the latest version 7.0, but it still comes back to the problem of network speed. The network in the hotel outside is really not working, and the download is incomplete after a long time. Finally, I found a way and recommended a website:

https://d.serctl.com/

For files on Github, you can directly enter the link here, and then download it from here.

Copy the downloaded pre-trained model files to the yolov5 folder. In this way, the installation environment of Yolov5 is completely completed.

Micro card Zhixiang

Test Yolov5

Use VS Code to open the yolov5 folder

Find the detect.py file. In the above figure, parse_opt is a default parameter that can be set using command line operations. But I still prefer to run with a compiler.