Human tracking implementation in python using YOLOv3. Example video here: miss_dior_hd_output
git clone [email protected]:Baiame/aive_test.git
cd aive_testHave Python >=3.9 installed with conda.
Have make installed. For example using brew:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
)
brew install makeInstall requirements:
make installSometimes the environment is not properly activated. Try to run:
conda activate aiveDownload YOLOv3 and tiny-YOLOv3 and place them in the models folder.
To run the test with the default video and default mode, run:
make runOtherwise, you can use the following command:
python src/main.py -i <VIDEO_PATH> -m <MODEL> -s <SPEED>For the model choice, it can be:
- yolo
- tiny-yolo
For the speed, you can choose:
- normal
- fast
- faster
- flash
For code formatting, install black and run the formatting with make:
brew install black
make format