FoodDetector is a real-time web-based application for detecting and recognizing Vietnamese dishes using a custom YOLOv10 model trained on the VietFood67 - the largest Vietnamese food dataset. This system empowers users with instant nutritional feedback, aiding in dietary awareness and health-conscious decision-making.
- Real-time Vietnamese dish detection via images, videos, webcam input and IP camera (RTSP).
- Nutritional breakdown for each detected dish: Calories, Fat, Saturates, Sugar, Salt.
- Traffic light system for nutrient awareness.
- Powered by a custom-trained YOLOv10 model on our largest Vietnamese food image dataset VietFood67 dataset.
- Developed using Python, Streamlit, and OpenCV.
This project has been the foundation of two published research papers:
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"Now I Know What I am Eating: Real-time Tracking and Nutritional Insights Using VietFood67 to Enhance User Experience"
🏆 Best Paper Runner-up Award at SOICT 2024
🔗 View Paper -
"It’s Yummy: Real-Time Detection and Recognition of Vietnamese Dishes"
📌 Presented at ICCIT 2024, British University Vietnam (BUV)
🔗 View Paper
- Nguyen Viet Hoang Nam (Project Lead, Web Developer, YOLOv10 Trainer, VietFood Dataset Gathering)
- Tran Bao Tu (UI/UX Designer, Poster, Slides Creator)
- Ton That Minh Vu (Dataset Gathering)
- Dr. Vi Chi Thanh (Research Supervisor & Guidance)
| Area | Tech Stack |
|---|---|
| Model Training | Python, YOLOv10 |
| Deployment | Streamlit |
| Nutritional Data | Custom JSON + Traffic Light System |
| Visualization | Matplotlib, Streamlit Components |
We created and released the VietFood67 dataset for training and evaluation, containing 68 classes (an extra class for human face detection) and 33k images of common Vietnamese dishes with annotated bounding boxes.
If you find FoodDetector or the VietFood67 dataset helpful in your research or projects:
- 🌟 Please consider giving this repository a star on GitHub.
- 📊 Star the VietFood67 dataset on Kaggle to show your support.
- 📄 Cite our papers in your publications to help us continue our research and development.
🆓 The FoodDetector and VietFood67 dataset are free to use for research and educational purposes with proper citation. Commercial use or redistribution is not permitted.
- Upload or stream food media (image, video, webcam, IP camera via RTSP).
- Real-time detection with bounding boxes and labels.
- Nutritional values shown per dish and total per meal.
- User-friendly nutrient traffic light indicators.
- Designed for low-resource environments (runs without GPU).
🚀 Latest Version: Please use the
v2branch before proceeding, as it includes all the newest features and improvements.
- Python 3.8+
- Streamlit
- OpenCV
- ONNX Runtime
- Pandas, Numpy, etc.
git clone https://github.com/nvhnam/FoodDetector.git cd FoodDetector git checkout v2 pip install -r requirements.txt streamlit run app.py
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📱 Mobile App with AR: Building a mobile version featuring AR overlays that display 3D real-time nutrient values directly on detected dishes.
🔍 Currently seeking passionate collaborators with experience in Unity and AR development to bring this vision to life! And be the co-author of this new paper.
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🧠 Integration with AI nutritionist agents (CrewAI, LangChain) for personalized meal recommendations.
🔍 Research is currently in progress.
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🏥 Real-time health feedback based on user demographics (age, gender, height, weight, eating patterns).
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🍲 Expand the VietFood67 dataset with more regional Vietnamese dishes for greater diversity and recognition accuracy.
📩 Contact
For questions or collaborations:
- 📧 Email: [email protected]
- 👨💻 Portfolio: https://nguyenviethoangnam.vercel.app/
- 📝 LinkedIn: https://www.linkedin.com/in/nvhnam01/