# Purpose

- It was fun to mess around with :3
- Making this public so cqql can also mess around with it

# Dependencies
- opencv-python
    - all of the image stuff
- matplotlib
    - color lookup table
- (numpy)
    - used internally by opencv, but part of stdlib

# Running
- python -m venv localvenv
- ./localvenv/bin/pip install opencv-python
- ./localvenv/bin/pip install matplotlib
- ./localvenv/bin/python match.py


# Modifications
- If you have more/less images, change MAX global
- If you want to test rotational stuff, uncomment the line in main
- It is assumed that the shape is a darker shape on a ligher background
    - The image gets converted into grayscale and assumes 
    - the shape has an intensity below 200
    - the background has an intensity above 200
- Depending on how dissimilar the shapes are, NormUpperBound should be increased

# Attributions

- The test images were generated using
    - https://moonlit.technology/cqql/frost_patterns

# Build Blog

- pandoc --standalone blog.md -o shape_matching.html --metadata title="Shape Matching"