This repository is created on top of two repository
- Create Virutal Environment of Python, Recommended python version
3.9.0
, incase you dont have3.9.0
, seepyenv
guide. - Activate the Environment using
python -m venv your_env_name/Scripts/activate
- install required libraries using
pip install -r requirements
- (Optional) If you want to use GPU, you have to install additional requirements i.e,
pip install -r requirements_gpu.txt
Models:
Models | Test Size | Easy | Medium | Hard | FLOPs (B) @640 | Baidu | |
---|---|---|---|---|---|---|---|
yolov7-lite-t | 640 | 88.7 | 85.2 | 71.5 | 0.8 | gsmn | |
yolov7-lite-s | 640 | 92.7 | 89.9 | 78.5 | 3.0 | 3sp4 | |
yolov7-tiny | 640 | 94.7 | 92.6 | 82.1 | 13.2 | aujs | |
yolov7s | 640 | 94.8 | 93.1 | 85.2 | 16.8 | w72z | |
yolov7 | 640 | 96.9 | 95.5 | 88.0 | 103.4 | jrj6 | |
yolov7+TTA | 640 | 97.2 | 95.8 | 87.7 | 103.4 | jrj6 | |
yolov7-w6 | 960 | 96.4 | 95.0 | 88.3 | 89.0 | - | |
yolov7-w6+TTA | 1280 | 96.9 | 95.8 | 90.4 | 89.0 | - |
--weights
contains your downloaded model from the above table--bluurratio
to determine the strength of blurring, default value is20
--device
eithercpu
or0
in case ofgpu
.--source
containes your images (png, jpg etc) or video (mp4 etc)
# Example with detected accuracy (usng CPU)
python detect.py --weights yolov7-tiny.pt --blurratio 50 --device cpu --source myimage.jpg
# Example with hiding detected area, only blur (usng CPU)
python detect.py --weights yolov7-tiny.pt --blurratio 50 --hidedetarea --device cpu --source myimage.jpg
# Example on video (usng CPU)
python detect.py --weights yolov7-tiny.pt --blurratio 50 --hidedetarea --device cpu --source myvideo.mp4