colour-science/colour-checker-detection-dataset
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How to use colour-science/colour-checker-detection-models with ultralytics:
from huggingface_hub import hf_hub_download
from ultralytics import YOLO
# pick the weights file from this repo's "Files and versions" tab
weights = hf_hub_download("colour-science/colour-checker-detection-models", "<weights>.pt")
model = YOLO(weights)
source = 'http://images.cocodataset.org/val2017/000000039769.jpg'
model.predict(source=source, save=True)Various YOLOv8 colour rendition charts detection models.
The models obtained by training YOLOv8 segmentation with the colour-science/colour-checker-detection-model dataset are supporting colour rendition charts detection in the Colour Checker Detection Python package.
| Name | Size | mAP50 | mAP50-95 |
|---|---|---|---|
| colour-checker-detection-l-seg.pt | 92.6 MB | 0.995 | 0.992 |
The Colour Developers can be reached via different means:
Colour - Checker Detection - Models by Colour Developers
Copyright 2024 Colour Developers – mailto:colour-developers@colour-science.org
This software is released under terms of CC-BY-4.0: https://creativecommons.org/licenses/by/4.0/
https://huggingface.co/colour-science/colour-checker-detection-models