Helment and Mask Detection

I have used Yolov3 as an object detection model to train 4 classes -

• head,
• helmet and mask,
• mask,
• helmet

I have chosen yolo, because it is quite fast on par with mobilenet-SSD, gives a median accuracy with less data and training time.

Dependencies - refer requirement.txt

• cycler==0.10.0
• kiwisolver==1.2.0
• matplotlib==3.2.1
• numpy==1.18.4
• opencv-python==4.2.0.34
• pandas==1.0.3
• pyparsing==2.4.7
• python-dateutil==2.8.1
• pytz==2020.1
• six==1.15.0

Model Params

• batch=64
• width=416
• height=416
• channels=3
• momentum=0.9
• decay=0.0005
• learning_rate=0.001
• classes=4

Inference

• To Run Inference: python3 inference.py --image images/0.jpg --config yolov3-helmet.cfg --weights ../backup/yolov3-helmet_20000.weights --names data.names