results = self.model_predict(frame) dets = [] if len(results) == 0: pass else: for index, row in results.iterrows(): class_ids = row['class'] scores = float(row['confidence']) x1 = int(row['xmin']) y1 = int(row['ymin']) x2 = int(row['xmax']) y2 = int(row['ymax']) cx = int((x1 + x2)/2) cy = int((y1 + y2)/2) pt_center = (cx,cy) dist = cv2.pointPolygonTest(pts, pt_center, False) if dist > 0: print('在内部') dets.append([x1,y1,x2,y2,scores]) else: print('在外部') 找出为外部的，删除result值

您的问题是如何找出为外部的并删除result值？

在上述代码中，找出为外部的结果是通过计算目标中心点到多边形的距离（dist）来实现的，如果距离大于0，则说明目标不在多边形内部，需要将其删除。可以使用以下代码来实现：

to_delete = []
for index, row in results.iterrows():
    class_ids = row['class']
    scores = float(row['confidence'])
    x1 = int(row['xmin'])
    y1 = int(row['ymin'])
    x2 = int(row['xmax'])
    y2 = int(row['ymax'])
    cx = int((x1 + x2)/2)
    cy = int((y1 + y2)/2)
    pt_center = (cx,cy)
    dist = cv2.pointPolygonTest(pts, pt_center, False)
    if dist > 0:
        print('在外部')
        to_delete.append(index)
    else:
        print('在内部')

results = results.drop(to_delete)

这段代码会遍历所有的结果，如果发现目标不在多边形内部，则将其对应的索引添加到一个列表中，遍历完所有结果后，再将这些索引对应的结果从results中删除。