Comments (5)
cache_dict内部保存的就是从GT中读出来的坐标点,可以查看这个代码
https://github.com/cfzd/Ultra-Fast-Lane-Detection-v2/blob/master/scripts/cache_culane_ponits.py
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纵坐标必须要和the_anno_row_anchor保持一致吗
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@zhenghao222
那不需要,你完全可以自己定义,甚至纵坐标是非均匀的都可以,后面会使用my_interp把他们全部插值到所输入的anchor上
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这个代码中组织成这样主要是考虑希望所有的车道线上的点数都是一样的,这样后面好处理,DALI在读取数据时一个batch内的大小要一致
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非常感谢您的回复
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Related Issues (20)
- 关于模型大小的问题,删除optimizer之后为何模型还有上百兆的空间,转化为onnx后仍然很大,请问这是正常的吗? HOT 6
- 模型转换为onnx后slice层错误 HOT 1
- test.py: error: unrecognized arguments: --local-rank=3 HOT 2
- Problem when do inference on CurveLanes HOT 1
- how to convert ufldv2_tusimple_res34_320x800.onnx to tensorrt
- Dockerfile for same one wants to use this repo on docker😉
- how to label for data
- 关于数据集转换
- 如何测试 论文中的 time 和fps
- 弯道的优化思路 HOT 1
- 根据CULane做测试的时候,训练莫名被killed HOT 6
- 无法生成culane_anno_cache.json文件 HOT 7
- 自己的dataset的__getitem__使用my_interp,出现re-initialize CUDA in forked subproces的问题
- 训练过程中会找不到一个文件
- 能否像V1那样使用辅助分支的方法训练
- 当我启用了SegHead结构后,就发生了报错。 HOT 2
- 更改输入网络的图片大小之后还有哪些需要修改 HOT 1
- curvelanes HOT 1
- Tusimple数据集问题
- 请问是否能够读取摄像头画面并实时进行预测呢?该如何设置? HOT 2
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