Welcome to the Shop Sign Detection project! This Python script helps you detect shop signs in videos using advanced computer vision techniques. Whether you're monitoring foot traffic in a mall or analyzing street scenes, this tool can assist you in identifying shop signs accurately.
- AI-Powered Detection: Leveraging cutting-edge deep learning models like YOLO and PaddleOCR, our script can detect shop signs with high accuracy.
- Real-time Processing: Process videos in real-time, allowing you to monitor shop signage dynamically.
- Efficient Entry Tracking: Automatically tracks entry and exit times for each shop, providing valuable insights into customer behavior.
To get started, follow these steps:
-
Installation: Ensure you have Python installed on your system along with the required dependencies listed in
requirements.txt
. -
Configuration: Update the paths to your YOLO model (
best.pt
), YouTube video link, and output Excel file in the script. -
Execution: Run the
main.py
script to start processing your video and detecting shop signs.
- Python 3.x
- OpenCV
- Pafy
- Ultralytics YOLO
- PaddleOCR
- Pandas
python main.py
This project is licensed under the MIT License.
Contributions are welcome! Feel free to submit bug reports, feature requests, or pull requests.
- Thanks to the contributors of Ultralytics YOLO and PaddleOCR for their excellent open-source projects.
- Special thanks to the Python community for their continuous support and inspiration.