Comments (11)
--multiprocessing你跑的时候有加吗?另外你可以试下单卡 --debug 的时候是否能够顺利跑起来?
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--multiprocessing加了也会报错,另外跑单卡也会出现同样的问题,加了--debug 也不行
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还有想请问下PSMNet应该也是用了3D卷积,为什么那个代码在12G显存上可以跑起来呢,有没有什么有效的方法可以改进呢?
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是的,之前因为3D volume占用显存较大,所以我把很多3D conv缩减后能够大量地降低显存使用。比较奇怪你那边显存还是超了。我建议你可以试着把volume 的 range减小一下,主要是BEV (X/Y)的面积减小进一步减小显存看下。如果有问题可以用--debug调试下
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好的,谢谢
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你好,想请教一个问题,在深度网络训练部分,根据lidar生成深度图的过程中,将lidar投影到图像上,是不是无法保证每个像素都有对应的深度ground truth呢,想请问下这部分是怎么处理的,投影得到的深度值结果可以直接用于模型的训练么?
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是的,投影后直接用cost volume去估计深度就行。只有有深度的pixel做loss,否则就ignore。
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好的,谢谢解答
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你好,我和你遇到了一样的问题,我想请教一下关于12g多gpu依旧报outofmemory这个问题你解决了吗
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你好,我能问一下./configs/default/config_car.py是多少G显存的模型,我12G的GPU适合跑哪个模型
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你好问一下,最后oom的问题解决了吗
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Related Issues (20)
- Train, Val, Test split HOT 4
- Inference Speed HOT 2
- 同一个目标多个预测框 HOT 9
- the error of the depth estimation HOT 2
- What is the supervision of point cloud? HOT 6
- may i train this model without the depth estimation? HOT 1
- monocular experiment HOT 12
- Model that has been trained
- tensorflow / tensorflow lite HOT 2
- About the construction of Plane Sweep Volume HOT 4
- where's the split files?
- 作者你好,你的build_cost_volume_forward部分是c++实现的吗? HOT 1
- TypeError: expected dtype object, got 'numpy.dtype[float64]' in eval.py HOT 1
- ./configs/default/config_disp.py这个文件是用来做什么的,是只包含深度估计网络的config吗 HOT 1
- Question about setup(performance issue) HOT 2
- Using 3D Geometry Volume to predict depth. HOT 4
- Results don't match with paper on KITTI Leaderboard HOT 7
- CUDA out of memory HOT 7
- The wrong outputs of the pre-trained model HOT 7
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