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
Update README.md
Browse files
README.md
CHANGED
|
@@ -15,7 +15,7 @@ tags:
|
|
| 15 |
|
| 16 |
# Cowcatcher
|
| 17 |
|
| 18 |
-
Cowcatcher is a
|
| 19 |
Mounting is one of the clearest visual signals that a cow is in heat, so a reliable detector lets a barn
|
| 20 |
camera flag oestrus automatically instead of relying on someone watching the herd.
|
| 21 |
|
|
|
|
| 15 |
|
| 16 |
# Cowcatcher
|
| 17 |
|
| 18 |
+
Cowcatcher is a vision model that detects **mounting behaviour** in cattle from camera images.
|
| 19 |
Mounting is one of the clearest visual signals that a cow is in heat, so a reliable detector lets a barn
|
| 20 |
camera flag oestrus automatically instead of relying on someone watching the herd.
|
| 21 |
|