Welcome to the future of retail! CartVision Nano leverages the blazing-fast and lightweight YOLOv8 Nano model to deliver a seamless, automated, and intelligent shopping experience.
Imagine walking through a store, dropping items into your cart, and walking out—no lines, no waiting, no hassle. This project brings that vision to life by using state-of-the-art object detection to automatically recognize products in real-time as you shop.
- Lightning-Fast Object Detection: Harnesses YOLOv8 Nano for speedy and accurate product recognition.
- Automated Checkout: No more standing in queues—checkout is handled by AI as you shop.
- Edge-Ready: Lightweight and efficient, perfect for running on embedded devices and edge hardware.
- Plug & Play: Designed with modularity in mind for easy setup and integration.
Note: This project is primarily based on Jupyter Notebooks for easy experimentation and visualization.
- Python 3.x
- Jupyter Notebook
- PyTorch
- OpenCV
- Ultralytics YOLOv8
You might need additional dependencies depending on your hardware and use case.
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Clone the repository:
git clone https://github.com/Sayakd915/Smart-Shopping-Cart---Yolov8-nano.git cd Smart-Shopping-Cart---Yolov8-nano -
(Optional) Set up a virtual environment:
python -m venv venv source venv/bin/activate # For Windows: venv\Scripts\activate
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Install dependencies:
pip install -r requirements.txt
- Fire up the main Jupyter Notebook and follow the step-by-step instructions to launch the smart cart demo.
- Tweak camera settings and model weights to suit your retail environment.
- Watch as your cart gets smarter!
Got improvements or new ideas? Contributions are more than welcome!
Fork the repo, make your changes, and open a pull request—we'd love to see your innovations.
- Ultralytics YOLOv8 for their awesome detection framework.
- The open-source computer vision community for making AI accessible to all.