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:
- cfc0fe73a55089790cb83ebbd9900b363e41b5bdb9435880fcd96b64484e5f75
- Size of remote file:
- 2.04 MB
- SHA256:
- 239aa3e8261b3fce999330e483dcebcac928c8bf87a215327460c3e694758e11
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.