Object Detection project created to detect face mask using YOLOv7 trained on a custom dataset
https://www.kaggle.com/datasets/andrewmvd/face-mask-detection
All 853 images were manually annotated using labelimg, two labels were used to classify the images, "Mask" and "No Mask".
The dataset containing the images and labels was split into train/test/val using
python split_dataset.py --folder face_mask --train 80 --validation 10 --test 10 --dest face_mask_dataset
split_dataset.py provided by https://github.com/pHidayatullah/yolov7
Training was performed over 300 epochs and a batch size of 8 using google colab in the YOLOv7 Training.ipynb file.
# Train
!python train.py --batch-size 8 --device 0 --data data/face-mask.yaml --img 640 640 --cfg cfg/training/yolov7-face_mask.yaml --weights yolov7_training.pt --name yolov7-face-mask --hyp data/hyp.scratch.custom.yaml --epochs 300
python test.py --weights runs/train/yolov7-face-mask4/weights/best.pt --batch-size 2 --device 0 --data data/face-mask.yaml --img 640 --conf-thres 0.01 --iou 0.5 --name yolov7-face-mask-val --task val
python test.py --weights runs/train/yolov7-face-mask4/weights/best.pt --batch-size 2 --device 0 --data data/face-mask.yaml --img 640 --conf-thres 0.01 --iou 0.5 --name yolov7-face-mask-test --task test
