--- tags: - ultralyticsplus - yolov8 - ultralytics - yolo - vision - object-detection - pytorch library_name: ultralytics library_version: 8.0.239 inference: false datasets: - chanelcolgate/yenthienviet model-index: - name: chanelcolgate/chamdiemgianhang-vsk-v8 results: - task: type: object-detection dataset: type: chanelcolgate/yenthienviet name: yenthienviet split: validation metrics: - type: precision # since mAP@0.5 is not available on hf.co/metrics value: 0.99425 # min: 0.0 - max: 1.0 name: mAP@0.5(box) ---
chanelcolgate/chamdiemgianhang-vsk-v8
### Supported Labels ``` ['BOM_GEN', 'BOM_JUN', 'BOM_KID', 'BOM_SAC', 'BOM_THV', 'BOM_THX', 'BOM_VTG', 'BOM_YTV', 'HAN_GLI', 'HOP_FEJ', 'HOP_FRE', 'HOP_JUN', 'HOP_POC', 'HOP_VTG', 'HOP_YTV', 'LOC_JUN', 'LOC_KID', 'LOC_YTV', 'LOO_DAU', 'LOO_KID', 'LOO_MAM', 'LOO_YTV', 'POS_GLI', 'POS_LON', 'POS_NHO', 'POS_THA', 'TUI_GEN', 'TUI_JUN', 'TUI_KID', 'TUI_SAC', 'TUI_THV', 'TUI_THX', 'TUI_VTG', 'TUI_YTV'] ``` ### How to use - Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus): ```bash pip install ultralyticsplus==0.1.0 ultralytics==8.0.239 ``` - Load model and perform prediction: ```python from ultralyticsplus import YOLO, render_result # load model model = YOLO('chanelcolgate/chamdiemgianhang-vsk-v8') # set model parameters model.overrides['conf'] = 0.25 # NMS confidence threshold model.overrides['iou'] = 0.45 # NMS IoU threshold model.overrides['agnostic_nms'] = False # NMS class-agnostic model.overrides['max_det'] = 1000 # maximum number of detections per image # set image image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg' # perform inference results = model.predict(image) # observe results print(results[0].boxes) render = render_result(model=model, image=image, result=results[0]) render.show() ```