Extract pathway from climbing wall picture based on holds color. This program was first design to work on Arkose picture from the site https://www.sboulder.com/ and thus by default detect only the colors: yellow, green, blue, red, black and purple.
Inspired from https://www.pyimagesearch.com/2014/08/04/opencv-python-color-detection/
Example::
pip install -r requirements.txt
python extractor.py -i examples/iQnnQ47T9ZnpxWMJf.jpg -e hed
It will create a file examples/iQnnQ47T9ZnpxWMJf_<color>.jpg for each color detected (from the 6 decribed earlier).
There is another parameter -e or --edge-detector which can be canny or hed (see Sources) to specify the edge detector algorithm in the background removal process. If no edge detector is specified, the program will only apply the color filter, and not the background removal part.
If the edge detector chosen is hed, this file must be download and put inside the folder hed_model: hed_pretrained_bsds.caffemodel
You can add or remove color by editing the color range of the global variable ``. It uses the HSV representation (hue, saturation, lightness).
Notes: For the red color, two ranges are used. The ones below and above 0.
A bluring effect is added to ease the readability, for the black holds in particular, but you can easily remove it.
- Cut as much as possible the holds. Then cluster the colors using
BIRCHalgorithm and filter on the closest color in input - Take the full picture and apply
DBSCANalgorithm to partition the picture and filter on the closest color in input