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Parent(s):
7ff0dba
add ultralytics model card
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README.md
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---
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tags:
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- ultralyticsplus
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- yolov8
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- ultralytics
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- yolo
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- vision
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- object-detection
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- pytorch
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library_name: ultralytics
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library_version: 8.0.239
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inference: false
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datasets:
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- chanelcolgate/yenthienviet
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model-index:
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- name: chanelcolgate/chamdiemgianhang-vsk
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results:
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- task:
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type: object-detection
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dataset:
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type: chanelcolgate/yenthienviet
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name: yenthienviet
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split: validation
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metrics:
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- type: precision # since mAP@0.5 is not available on hf.co/metrics
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value: 0.97141 # min: 0.0 - max: 1.0
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name: mAP@0.5(box)
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---
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<div align="center">
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<img width="640" alt="chanelcolgate/chamdiemgianhang-vsk" src="https://huggingface.co/chanelcolgate/chamdiemgianhang-vsk/resolve/main/thumbnail.jpg">
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</div>
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### Supported Labels
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```
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['bom_gen', 'bom_jn', 'bom_knp', 'bom_sachet', 'bom_vtgk', 'bom_ytv', 'hop_dln', 'hop_jn', 'hop_vtg', 'hop_ytv', 'lo_kids', 'lo_ytv', 'loc_dln', 'loc_jn', 'loc_kids', 'loc_ytv', 'pocky', 'tui_gen', 'tui_jn', 'tui_sachet', 'tui_vtgk']
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```
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### How to use
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- Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus):
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```bash
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pip install ultralyticsplus==0.1.0 ultralytics==8.0.239
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```
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- Load model and perform prediction:
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```python
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from ultralyticsplus import YOLO, render_result
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# load model
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model = YOLO('chanelcolgate/chamdiemgianhang-vsk')
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# set model parameters
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model.overrides['conf'] = 0.25 # NMS confidence threshold
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model.overrides['iou'] = 0.45 # NMS IoU threshold
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model.overrides['agnostic_nms'] = False # NMS class-agnostic
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model.overrides['max_det'] = 1000 # maximum number of detections per image
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# set image
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image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'
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# perform inference
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results = model.predict(image)
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# observe results
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print(results[0].boxes)
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render = render_result(model=model, image=image, result=results[0])
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render.show()
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```
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