首页 xyxy=yolov8_results.boxes.xyxy.cpu().numpy(), confidence=yolov8_results.boxes.conf.cpu().numpy(), class_id=yolov8_results.boxes.cls.cpu().numpy().astype(int), mask=extract_yolov8_masks(yolov8_results), 怎么用 boxes = detections.xyxy conf = detections.confidence class_ids = detections.class_id results = [] if polygon.shape[0] > 0: for label, score, seg in zip(class_ids, conf, polygon): # 将多边形的点坐标转换为列表形式 points = [[float(coord[0]), float(coord[1])] for coord in seg] results.append({ "confidence": str(score), "label": labels.get(label, "unknown"), "points": points, "type": "polygon",})

xyxy=yolov8_results.boxes.xyxy.cpu().numpy(), confidence=yolov8_results.boxes.conf.cpu().numpy(), class_id=yolov8_results.boxes.cls.cpu().numpy().astype(int), mask=extract_yolov8_masks(yolov8_results), 怎么用 boxes = detections.xyxy conf = detections.confidence class_ids = detections.class_id results = [] if polygon.shape[0] > 0: for label, score, seg in zip(class_ids, conf, polygon): # 将多边形的点坐标转换为列表形式 points = [[float(coord[0]), float(coord[1])] for coord in seg] results.append({ "confidence": str(score), "label": labels.get(label, "unknown"), "points": points, "type": "polygon",})

时间: 2024-02-14 14:30:19 浏览: 398

根据您提供的代码，您可以将以下代码作为替代： ```python xyxy = detections.xyxy confidence = detections.confidence class_id = detections.class_id results = [] if polygon.shape[0] > 0: for label, score, seg in zip(class_id, confidence, polygon): # 将多边形的点坐标转换为列表形式 points = [[float(coord[0]), float(coord[1])] for coord in seg] results.append({ "confidence": str(score), "label": labels.get(label, "unknown"), "points": points, "type": "polygon", }) ``` 在这个修改后的代码中，我们使用 `detections` 对象的属性来获取边界框的坐标、置信度和类别ID，并将它们分别赋值给 `xyxy`、`confidence` 和 `class_id` 变量。然后，我们使用 `zip` 函数来将 `class_id`、`confidence` 和 `polygon` 配对，然后在循环中处理每个配对。我们将多边形的点坐标转换为列表形式，并将结果添加到 `results` 列表中。请确保根据您的实际情况修改代码，并根据需要调整变量名和逻辑。

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