融合Pointpillar与ResNeXt模型---实战记录(持续更新)

1. 数据集下载

# download left color images:

wget https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_image_2.zip

# download calibration results:

wget https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_calib.zip

# download labels:

wget https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_label_2.zip

# download Velodyne point clouds:

wget https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_velodyne.zip

# download development kit:

wget https://s3.eu-central-1.amazonaws.com/avg-kitti/devkit_object.zip

睿智的目标检测26——Pytorch搭建yolo3目标检测平台_Bubbliiiing的博客-CSDN博客_睿智的目标检测26睿智的目标检测26——Pytorch搭建yolo3目标检测平台学习前言源码下载yolo3实现思路一、预测部分1、主题网络darknet53介绍2、从特征获取预测结果3、预测结果的解码4、在原图上进行绘制二、训练部分1、计算loss所需参数2、pred是什么3、target是什么。4、loss的计算过程训练自己的yolo3模型学习前言一起来看看yolo3的Pytorch实现吧,顺便训练一下自己的...https://blog.csdn.net/weixin_44791964/article/details/105310627https://blog.csdn.net/qq_42173959/article/details/105727368https://blog.csdn.net/qq_42173959/article/details/105727368pointpillars代码阅读----prep_pointcloud篇_Little_sky_jty的博客-CSDN博客Brief这一篇内容主要是对函数prep_pointcloud进行debug和记录,这里也是dataloader的大部分内容,同时也涉及到gt的loss函数部分。作者的function breif如下:convert point cloud to voxels, create targets if ground truths exists. input_dict format: da...https://blog.csdn.net/weixin_40805392/article/details/102135201

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