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：用COCO数据集推理
    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)