cam-pos-system is a Rust library with an example app that reads a video stream and detects moving objects within a coordinate system using computer vision algorithms.
The cam-pos-system library uses the following computer vision algorithms for object detection:
- HOG detector: This algorithm detects the presence of objects in an image by looking for their Histogram of Oriented Gradients (HOG) features.
- MosseTracker: This algorithm tracks a moving object in a video stream using adaptive correlation filters to estimate the object's position and scale. The library combines these algorithms to detect moving objects in a video stream and estimate their positions within a coordinate system.
wasm-pack build --no-default-features --target web
python3 -m http.serverIn the folder res/training are images. For each image exists a txt file containing labels in format "name x y" The label names can be found in res/labels.txt.
You can create the training data with this simple tool on Hog-Detector.