Exploring the unknown color-spatial space continuum with 3D visualizations and unsupervised machine learning, one pixel at a time.
- Supports 7 different color spaces to visualize
- All common image formats supported (JPG, PNG, etc.)
- 3D color space scatterplot for color distribution
- 3D spatial-color scatterplot (X and Y as pixel coordinates and Z as channel value)
- Basic cropping and thresholding supported
- Color/gray histogram visualization
- Color/spatial space clustering w/ visualization using
scikit-learn(WIP) - Dataset mode: Open a folder and quickly scroll through images via left/right arrow keys
- Export high quality screenshots of visualizations
- Clone this repo
- Create virtual environment from
requirements.txt - Run
python main_app.py
- Implement Clustering w/ visualization based on
scikit-learn: https://scikit-learn.org/stable/modules/clustering.html - Implement PCA analysis (probably) based on
scikit-learn