Object Detection
ultralytics
yolo
yolov11
poultry
chicken
egg
broiler
agriculture
smart-farming
animal-welfare
precision-livestock-farming
Eval Results (legacy)
Instructions to use Williamsanderson/PoultryVision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Williamsanderson/PoultryVision with ultralytics:
from ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("Williamsanderson/PoultryVision") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Initial release: YOLOv11m fine-tuned on PoultryVision dataset (79.3% mAP50-95, beats paper YOLOv11x by +8.5pts)
eacfff4 verified | # PoultryVision Unified Dataset | |
| # Auto-generated by PoultryVision Dataset Builder | |
| # Sources: Dataset Chicken 1-3, Chickens-Eggs v1, chicken eggs 2 v3, MVBroTrack | |
| path: c:/Users/HP/Downloads/Dataset Model Firm/PoultryVision/dataset | |
| train: images/train | |
| val: images/val | |
| test: images/test | |
| nc: 2 | |
| names: | |
| 0: chicken | |
| 1: egg | |
| # Dataset statistics (auto-generated) | |
| # See dataset_card.md for full details | |