Object Detection
ultralytics
TensorBoard
PyTorch
v8
ultralyticsplus
yolov8
yolo
vision
awesome-yolov8-models
Eval Results (legacy)
Instructions to use bob12345677/yolov8m-protective-equipment-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use bob12345677/yolov8m-protective-equipment-detection with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("bob12345677/yolov8m-protective-equipment-detection") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 316019f04cda4c5521b58ce0babcb2c7f21e793f3cd9d516e580b334283f79b4
- Size of remote file:
- 52 MB
- SHA256:
- ddc564fc57d9e8be0eb5bd1eec83cbd9d8aaca66b843ef0ccfdb4a4240c655a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.