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With using YOLOv7 on video cameras detecting the occupancy time (with belongings, without human) of the seats in the library

SeatWatch: Advanced Library Seat Occupancy Detection 📚

teaser
Open In Colab

🌟 Project Description

With using YOLOv7 on video cameras detecting the occupancy time (with belongings, without human) of the seats in the library

image

Detailed explanation about the project is in this document: Document

🛠️ System Architecture

image

📜 Installation

git clone https://github.com/asumansaree/Library-Seat-Occupancy-Detection
cd Library-Seat-Occupancy-Detection
pip install -r requirements.txt

🤗 Usage

python detect_and_track.py \
    --weights yolov7.pt \
    --source "test.mp4" \
    --conf-thres 0.4 \
    --classes 0 56 \
    --name "YOLOV7_Library_Seat_Detection" \

🚀 Sample Output

Output file will be created in the

"/content/Library-Seat-Occupancy-Detection/runs/detect/YOLOV7_Library_Seat_Detection/{video.mp4}"

Output is in the mp4 format. For demonstration purposes in pdf document, it is included as image

ImageProcessing_ProjectReport_AsumanSareERGUT-09

💬 Contact

Contact me for any problem and question [email protected]

🙏 References

  • https://github.com/RizwanMunawar/yolov7-object-tracking
  • Anish Aralikatti et al 2020 J. Phys.: Conf. Ser. 1706 012149
  • Redmon J, Divvala S, Girshick R and Farhadi A You Only Look Once: Unified, Real-Time Object Detection 2016IEEE Conference on Computer Vision and Pattern Recognition (Las Vegas) pp 779-788
  • COCO 2017 dataset: http://cocodataset.org