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HaohaoNJU avatar HaohaoNJU commented on July 20, 2024

如果你的模型是用自己的数据集训练的,请在这里 更改下图片大小的配置,因为这些配置是按照nuscenes数据写的。

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ryontang avatar ryontang commented on July 20, 2024

如果你的模型是用自己的数据集训练的,请在这里 更改下图片大小的配置,因为这些配置是按照nuscenes数据写的。

好的,谢谢,排查到是create_data.py的类别设置与模型训练的类别不统一,导致的输出结果错误

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stanny880913 avatar stanny880913 commented on July 20, 2024

如果你的模型是用自己的数据集训练的,请在这里 更改下图片大小的配置,因为这些配置是按照nuscenes数据写的。

好的,谢谢,排查到是create_data.py的类别设置与模型训练的类别不统一,导致的输出结果错误

您好,想請問能否詢問您如何用自己的dataset訓練centerfusion呢?謝謝

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UmangBDhanani avatar UmangBDhanani commented on July 20, 2024

Yes I woud also like to know the same, to train centerfusion on own datasets. Thank you in advance.

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ryontang avatar ryontang commented on July 20, 2024

如果你的模型是用自己的数据集训练的,请在这里 更改下图片大小的配置,因为这些配置是按照nuscenes数据写的。

好的,谢谢,排查到是create_data.py的类别设置与模型训练的类别不统一,导致的输出结果错误

您好,想請問能否詢問您如何用自己的dataset訓練centerfusion呢?謝謝

您好,参考centerNet和centerFusion的训练过程

  1. 首先你需要将本地数据集的格式按照coco数据集整理,具体可以参考convert_nuScenes.py
    训练得到一个centerNet pth权重文件,可以把这个baseline作为centerfusion训练的baseline;

(具体可参考centerFusion的 train.sh文件,)
2. 然后冻结baseline的backbone使用centerfusion代码训练目标速度(此时还没有加载radar point);

3.加载radar point训目标速度/depth/nuscenes_att等属性

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