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@ -1,50 +0,0 @@
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import cv2
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from tqdm import tqdm
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from ultralytics import YOLO
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from ultralytics.yolo.utils.plotting import Annotator
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import os
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def analysis_yolov8(images, model_coco,confidence):
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frame = images
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# 第一步：用COCO数据集推理
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results_coco = model_coco(frame)
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# print(results_coco)
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if results_coco:
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for r in results_coco:
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boxes = r.boxes
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re_list = []
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for box in boxes:
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b = box.xyxy[0] # get box coordinates in (top, left, bottom, right) format
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c = box.cls
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# 保存标签和坐标值作为返回结果
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blist = b.tolist()
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labels_name = model_coco.names[int(c)]
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confidence = float(box.conf)
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confidence = round(confidence, 2)
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# 过滤置信度0.5以下目标
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if confidence < confidence:
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continue
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re_dict = {labels_name:blist}
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re_list.append(re_dict)
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return re_list
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# if __name__ == '__main__':
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# model_coco = YOLO("model_files/bk1.pt")
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# frame = cv2.imread("E:/BANK_XZ/data_file/0000162.jpg")
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# analysis_video(frame, model_coco,confidence=0.5)
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