基于Pytorch的Yolov4算法实现车辆检测以及跟踪(深度学习)

上传者: xixixixixixixi21 | 上传时间: 2022-04-29 16:08:29 | 文件大小: 5.24MB | 文件类型: ZIP
将VOC格式文件放至data的文件夹 JPEGImages文件夹中存放数据图片 Annotations文件夹中存放与图片一一对应的标签文件 调整voc2yolo4.py文件中的trainval_percent 、train_percent的值,控制训练集、测试集、验证集的比例;调整完成后运行该文件,在data/ImageSets/Main文件夹中生成对应数据集的图片文件名 运行voc_annotation.py文件,运行前将文件中的classes列表替换为自己数据集的class的名字 运行后自动生成yolo_train.txt文件,文件中每一行的格式为图片路径和图片中标注框的位置以及分类,如下所示 data/JPEGImages/MVI_20011__img00001.jpg 592,378,752,540,3 557,120,604,163,2 545,88,580,118,2 508,67,536,92,3 553,70,582,89,7 731,114,783,153,2 902,250,960,357,3 修改train.py中的路径参数与自己电脑上的路径相匹配 classes

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