labelGo
A graphical Semi-automatic annotation tool based on labelImg and Yolov5
Semi-automatic annotation of datasets by existing yolov5 pytorch models
Attention
If there is a problem, please put it forward in the issue
Please put classes.txt under the marked dataset folder in advance
The annotation file is saved in the same location as the picture folder
Recommended version of python: python 3.8
Recommended for conda environments
Installation and use
1.Fetching projects from git
git clone https://github.com/cnyvfang/labelGo-Yolov5AutoLabelImg.git
2.Switching the operating directory to the project directory
cd labelGo-Yolov5AutoLabelImg
3.Installation environment
pip install -r requirements.txt
4.Launching applications
python labelGo.py
5. Click on the "Open directory" button to select the folder where the images are stored
6. Click on the "Auto Annotate" button to confirm that the information is correct and then select the trained yolov5 pytorch model to complete the auto annotation
7. Adjust the automatic annotation results according to the actual requirements and save them
