模型:
keremberke/yolov8s-protective-equipment-detection
['glove', 'goggles', 'helmet', 'mask', 'no_glove', 'no_goggles', 'no_helmet', 'no_mask', 'no_shoes', 'shoes']
pip install ultralyticsplus==0.0.23 ultralytics==8.0.21
from ultralyticsplus import YOLO, render_result # load model model = YOLO('keremberke/yolov8s-protective-equipment-detection') # 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()
更多可用模型请访问: awesome-yolov8-models