We implement a method to count the number of occupants in room, from the given video feed of the room. We use a YOLOv3 model as our backbone. The model detects humans in the room and we count the number of predictions in each frame to give out the final count.
- Download pretrained YOLOv3 weights and it's config files from the below link. https://pjreddie.com/darknet/yolo/
- Install OpenCV
- To run inference on an image, run the below command in your terminal: python inference.py --image <image_path> --config <yolo_config_path> --weights <yolo_weights_path> --classes <no_of_class>
- Currently this model runs just using OpenCV and DNN modules, we can speed it up by using TFLite.
- Using more latest object detection models like YOLOv5 or FRCNN.
- Shrikumaran PB
- Kailash J
- Akshat K
- Hemangani N
- Akesh M
- Sathya Prakash