摘要：将分辨率大的图片分割成图片切片，然后对每一小图片切片进行模型预测，再将得到的结果进行合并。 import cv2 as cv import supervision as sv from ultralytics import YOLO model_path=r'F:\python\yolov8\yol 阅读全文

摘要：使用supervision追踪 import supervision as sv from ultralytics import YOLO model_path=r'F:\python\yolov8\yolov8n.pt' model=YOLO(model_path) box_annotator=s 阅读全文

摘要：过滤Dections有多种过滤方法。包括指定类，类集合，置信度，物体面积，边框面积，相对面积，边框维度和区域。 import numpy as np import supervision as sv import cv2 as cv from ultralytics import YOLO mode 阅读全文

摘要：保存detections为csv文件和json文件。 import cv2 as cv import supervision as sv from ultralytics import YOLO model_path=r'F:\python\yolov8\yolov8n.pt' model=YOLO 阅读全文

摘要：supervision 提供了无缝处理注释多种目标检测和语义分割模型生成的预测。 注释目标检测的图片 import cv2 as cv import supervision as sv from ultralytics import YOLO model_path=r'F:\python\yolov 阅读全文