Instructions to use lanseria/yolov8n-hard-hat-detection_web_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use lanseria/yolov8n-hard-hat-detection_web_model with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("lanseria/yolov8n-hard-hat-detection_web_model") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
add tfjs init model
Browse files- group1-shard1of3.bin +3 -0
- group1-shard2of3.bin +3 -0
- group1-shard3of3.bin +3 -0
- metadata.yaml +13 -0
- model.json +0 -0
group1-shard1of3.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b1c6a54138c5ab35860f93e6a2882419f536466af43849f5ee07f59df8536d30
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size 4194304
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group1-shard2of3.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:342df8987e3e48b9b28ed8414bbe0887161cf5cba2b5681cd86d7d946cd59c54
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size 4194304
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group1-shard3of3.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:5bfa58595c8b36ccf42518f619e2ae014dd8c05edbe1af251ab57db45ffca13c
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size 3804936
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metadata.yaml
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description: Ultralytics YOLOv8n-hard-hat-detection model trained on data.yaml
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author: Ultralytics
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license: AGPL-3.0 https://ultralytics.com/license
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version: 8.0.91
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stride: 32
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task: detect
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batch: 1
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imgsz:
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- 640
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- 640
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names:
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0: Hardhat
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1: NO-Hardhat
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model.json
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