Object Detection
ultralytics
yolo
agriculture
livestock
cattle
calving
animal-welfare
computer-vision
Instructions to use CowcatcherAI/Calvingcatcher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use CowcatcherAI/Calvingcatcher 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/Calvingcatcher", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
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| `calvingcatcherV8.pt` | `yolo26m` | 1024 / 150 | 44 MB | Our previous main model |
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| `CalvingcatcherV7.pt` | `yolo26m` | 960 / 150 | 44 MB | Older 960 px generation, fewer false positives than V8 |
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All three are Ultralytics 8.4.14 `yolo26m` detection models.
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and the small/large variants show up in the benchmark below for context, but we don't publish them.
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| `calvingcatcherV8.pt` | `yolo26m` | 1024 / 150 | 44 MB | Our previous main model |
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| `CalvingcatcherV7.pt` | `yolo26m` | 960 / 150 | 44 MB | Older 960 px generation, fewer false positives than V8 |
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All three are Ultralytics 8.4.14 `yolo26m` detection models.
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