Computer vision coursework repository with multiple C++ and Python projects covering image processing, feature extraction, recognition, calibration, and neural-network-based experiments.
- Basic image display and interaction
- Color analysis and K-means clustering
- Feature extraction and image matching
- Region segmentation and object recognition
- Camera calibration and pose / feature robustness experiments
- DNN embedding and ONNX-based classification experiments
project1/ # Intro image processing and display utilities
project2/ # Feature extraction and image matching
project3/ # Segmentation, thresholding, denoising, recognition
project4/ # Calibration / robust feature experiments
project5/ # DNN embeddings and learned-feature experiments
hw4/ # Additional color and clustering work
projectFinal/ # Final project assets / experiments
Most directories contain their own CMakeLists.txt, Makefile, and project-specific assets.
- C++
- OpenCV
- CMake / Make
- Python (for selected experiments and preprocessing)
- ONNX / DNN model assets in later projects
Build and run each project independently from its own directory. For example:
cd project3
make
./mainIf you prefer CMake:
cmake -S . -B build
cmake --build build- This repository is organized as a collection of assignments and experiments rather than a single unified application.
- Input images, intermediate data files, and small helper binaries are committed alongside the source for reproducibility.