Instructions to use CowcatcherAI/Cowcatcher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use CowcatcherAI/Cowcatcher 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("CowcatcherAI/Cowcatcher", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signature91ea409 -
Update README.md
Verified signaturef61c93c -
Update README.md
Verified signature9b86d83 -
updated added train script
Verified signatureee469c9 -
Update README.md
Verified signature380e4f0 -
Upload 6 files
Verified signature04baed2 -
Segmentation model for cowcatcher
Verified signatureSegmentation model for cowcatcher, this was a very experimental approach what didn't work in the end the result was worse although the confidence is higher with a higher precision the only downside is that it often mist mountings what the bounding box trained on the same dataset. It can be a nice ladder for someone else to startf18aef8 -
Newest and best model up to 30-8-2026 till newer
Verified signatureNewest and best model up to 30-8-2026 till newer895a999
-
Upload cowcatcherV17.pt
Verified signature7fb597f -
initial commit
Verified signature16adf30