Comments (5)
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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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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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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Yes I woud also like to know the same, to train centerfusion on own datasets. Thank you in advance.
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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
- 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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Related Issues (7)
- 您好,刚接触深度学习和多传感器融合方向,有些问题想向您请教 HOT 1
- which type of GPU to get the Computation speed in the README? HOT 1
- why split model to img_model and fusion_model? HOT 2
- why pip install -r requirements.txt, many dependency related with ros pip package could not installed HOT 2
- 询问代码耗时过大原因 HOT 2
- Problem installing packages from requirements.txt HOT 1
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