Side Projects
Open projects built in my free time. See more at: https://github.com/vietanhdev.
- Description: Effortless data labeling with AI support from YOLO, Segment Anything, MobileSAM.
- Website: https://anylabeling.nrl.ai/
- Github: https://github.com/vietanhdev/anylabeling
- Demo: https://www.youtube.com/watch?v=5qVJiYNX5Kk
- Description: Daisykit is an open source AI toolkit, aiming to provide an easy way to use AI in software projects on multiple platform. Now we have C++, Python and Android demos.
- Techstack (Current): OpenCV, NCNN, C++, Bindings for Python
- My role: Founder and Developer
- Project Website: https://daisykit.nrl.ai/
- Github: https://github.com/DaisyLabSolutions/daisykit
- Demo: https://youtu.be/zKP8sgGoFMc
- Description: Push-up Counter using camera (MoveNet pretrained model) or proximity sensor. Tracking workout by day.
- Techstack: OpenCV, NCNN, C++, Android.
- Description: VIA Project is an open source for self-driving cars, including source code and tutorials for learning image processing and computer vision by building autonomous vehicles, VIA Simulation - a highly customizable simulation for self-driving car testing and VIA Makerbot - PCB for your mini self-driving car.
- My role: AI & Firmware Developer.
- Project Website (In Vietnamese): https://via.makerviet.org/
- Github: https://github.com/makerhanoi
- Demo: https://youtu.be/N0HzDScBAxo
- Description: VN AIDr project is an open source medical image processing solution for AI learners and hobbyists. On this platform, we design, train and evaluate machine learning models and algorithms for medical image analysis and medical report autocompletion.
- My role: Leader + Build deep learning models.
- Project Website: https://vnopenai.github.io/ai-doctor/
- Github: https://github.com/VNOpenAI/vn-aidr
- Description: This project uses BlazePose - a SOTA model for real-time human pose detection, a single frame action recognition model, and some signal processing algorithms to count pushups from a video stream or webcam. I reimplemented BlazePose using Keras (source).
- My role: Leader + Build BlazePose model.
- Github: https://github.com/VNOpenAI/pushup-counter-app
- Demo: https://www.youtube.com/watch?v=pm2mGmgwSZo
- Description: A driver assitant system that uses Jetson Nano as the hardware with four main functions: forward collision warning, lane departure warning, traffic sign recognition and overspeed warning. I won The NVIDIA Jetson Project Of the Month Prize with this project and received a Jetson AGX Xavier Developer Kit.
- Techstack: Python, C++, Tensorflow, Pytorch, TensorRT, object detection (CenterNet), segmentation (U-Net) and classification (ResNet-18)
- Github: https://github.com/vietanhdev/car-smart-cam
- Blog posts:
- Description: This project helped my group achieving The First Prize in FPT Self-driving Car challenge 2020 - University round at Hanoi University of Science and Technology. In this challenge, we built a ROS node with deep neural networks to control a autonomous car in a simulation environment. My team used E-Net and U-Net for lane segmentation and customized FaceBoxesfor a light-weight traffic sign detection networks. I was the leader of this team, worked on the architecture, semantic segmentation model and car controlling.
- Languages: Python.
- Technologies: ROS (Robot Operating System), OpenCV, segmentation models (U-Net, ENet), object detection (FaceBoxes), Docker.
- Github: https://github.com/vietanhdev/autonomous-car-2020
- Blog post: https://aicurious.io/posts/chung-toi-da-xay-dung-xe-tu-hanh-tren-gia-lap-the-nao/
- Description: I led a 4-member team to build a paper streaming solution for remote education. Our project got Second Place in SoICT - IBM Hackathon 2020 at HUST. I was responsible for algorithms to capture drawing strokes and handwritten text from a phone camera, filter and create video streaming.
- Languages: Python.
- Technologies: ARUCO, Color-based segmentation, ReactJS, NodeJS, CI-CD.
- Github: https://github.com/vietanhdev/paper_stream
- Blog post: https://aicurious.io/blog/2020-09-02-xay-dung-giai-phap-stream-giay-viet-ibm-hackathon-2020
- Demo: https://www.youtube.com/watch?v=pmRSfHSfrco
- Description: A modified Deep Head Pose model by adding new backbones(ShuffleNetV2, EfficientNet), and face landmark estimation.
- Languages: Python.
- Technologies: Deep Head Pose, ShuffleNetV2, EfficientNet, Landmark Estimation.
- Demo: https://youtu.be/SNHnsuNkBkQ
- Github: https://github.com/vietanhdev/deep-head-pose-2
- Description: A camera desktop application with funny face decorations and filters. In this project, I also integrated LBP Cascade and Haar Cascade models trained by myself to detect faces. This project supports both Linux and Windows.
- Languages: C++.
- Technologies: Qt, OpenCV, face detection and alignment algorithms.
- Github: https://github.com/vietanhdev/facecam
- Description: This is a group project for FPT self-driving car challenge 2018. We used Watershed and Floodfill algorithms for lane segmentation, a color-based method for traffic sign detection andHOG + SVM for sign classification. I worked on the architecture, algorithms for lane segmentation, a method for traffic sign detection and car control algorithm.
- Languages: C++.
- Technologies: OpenCV, Image processing, Color-based Object detection, Traffic Sign detection using HOG SVM.
- Github: https://github.com/vietanhdev/autonomous-car-2018
- Demo: https://www.youtube.com/watch?v=Obv53r7UV34.
- Description: We built a completed store management solution with a lot of features such asbilling, management UI for bills, warehouse, suppliers, customers, finance and employees. I worked on the desktop application.
- Languages: Desktop App: Javascript, HTML CSS; Server: Java
- Technologies: Desktop App: Electron; Server: Java Spring Boot.
- Github: https://github.com/vietanhdev/e-store-manager
- Demo: Youtube Video.
- Description: My funny IoT project for our environment. This trash bin can classify bottles and other kinds of garbage into different compartments. I finished this project in only 1 day. Most of the time was spent for the mechanical part, sensors, servo. I integrated and run a pre-trainedSSD-MobileNet V2 model on a Raspberry Pi computer to detect bottles.
- Technologies: Desktop App: Electron; Server: Java Spring Boot.
- Demo: https://www.youtube.com/watch?v=s1KHGU8nuBM
- Blog post (Vietnamese): Thiết kế thùng rác thông minh tự phân loại rác với Raspberry Pi 3.
- Description: Online BattleShip game using ReactJS for frontend, Flask for backend and Websocket for realtime communication. We also implemented a chatting system and friend list. I worked mostly on frontend part (ReactJS).
- Github: https://github.com/vietanhdev/online-battleship