可口可乐网站建设的目的,苏州保洁公司收费价格表,cdr做网站分辨率,企业seo排名外包一 需求
FaceBookReserch中SlowFast源码中检测框是用Detectron2进行目标检测#xff0c;本文想实现用yolov8替换detectron2二 实施方案
首先#xff0c;yolov8 支持有自定义库ultralytics#xff08;仅支持yolov8#xff09;#xff0c;安装对应库
pip install ultraly…一 需求
FaceBookReserch中SlowFast源码中检测框是用Detectron2进行目标检测本文想实现用yolov8替换detectron2二 实施方案
首先yolov8 支持有自定义库ultralytics仅支持yolov8安装对应库
pip install ultralytics源码中slowfast/visualization.py 43行中
if cfg.DETECTION.ENABLE:self.object_detector Detectron2Predictor(cfg, gpu_idself.gpu_id)根据ultralytics文档进行定义 创建对应YOLOPredictor类(加入了检测框及其标签具体见前一篇文章)
class YOLOPredictor:def __init__(self, cfg, gpu_idNone):# 加载预训练的 YOLOv8n 模型self.model YOLO(/root/autodl-tmp/data/runs/detect/train/weights/best.pt)self.detect_names, _, _ get_class_names(cfg.DEMO.Detect_File_Path, None, None)def __call__(self, task):Return bounding boxes predictions as a tensor.Args:task (TaskInfo object): task object that containthe necessary information for action prediction. (e.g. frames)Returns:task (TaskInfo object): the same task info object but filled withprediction values (a tensor) and the corresponding boxes foraction detection task.# 得到预测置信度# scores outputs[instances].scores[mask].tolist()# 获取类别标签# pred_labels outputs[instances].pred_classes[mask]# pred_labels pred_labels.tolist()# 进行标签匹配# for i in range(len(pred_labels)):# pred_labels[i] self.detect_names[pred_labels[i]]# preds [# [{:.4f}] {}.format(s, labels) for s, labels in zip(scores, pred_labels)# ]# 加入预测标签# task.add_detect_preds(preds)# task.add_bboxes(pred_boxes)middle_frame task.frames[len(task.frames) // 2]outputs self.model(middle_frame)boxes outputs[0].boxesmask boxes.conf 0.5pred_boxes boxes.xyxy[mask]scores boxes.conf[mask].tolist()pred_labels boxes.cls[mask].to(torch.int)pred_labels pred_labels.tolist()for i in range(len(pred_labels)):pred_labels[i] self.detect_names[pred_labels[i]]preds [[{:.4f}] {}.format(s, labels) for s, labels in zip(scores, pred_labels)]加入预测标签task.add_detect_preds(preds)task.add_bboxes(pred_boxes)return task
