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import cv2
from tqdm import tqdm
from ultralytics import YOLO
from ultralytics . yolo . utils . plotting import Annotator
import os
def analysis_yolov8 ( images , model_coco , confidence ) :
frame = images
# 第一步：
results_coco = model_coco ( frame )
# print(results_coco)
if results_coco :
for r in results_coco :
boxes = r . boxes
re_list = [ ]
for box in boxes :
b = box . xyxy [ 0 ] # get box coordinates in (top, left, bottom, right) format
c = box . cls
# 保存标签和坐标值作为返回结果
blist = b . tolist ( )
labels_name = model_coco . names [ int ( c ) ]
confidence = float ( box . conf )
confidence = round ( confidence , 2 )
# 过滤置信度0.5以下目标
if confidence < confidence :
continue
re_dict = { labels_name : blist }
re_list . append ( re_dict )
return re_list
# if __name__ == '__main__':
# model_coco = YOLO("model_files/bk1.pt")
# frame = cv2.imread("E:/BANK_XZ/data_file/0000162.jpg")
# analysis_video(frame, model_coco,confidence=0.5)