MonoDETR
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ZrrSkywalker
On the accuracy issue of MonoDETR on the KITTI test set
I only achieved 11.59% accuracy on the official using your public weights. I would like to ask what causes this? I want to replicate the 16.47% accuracy of the paper on the test set.
This is my replicate results, the problem is same with u. We also look forward a reasonable explain.
This is my replicate results, the problem is same with u. We also look forward a reasonable explain.
Excuse me, is this the model of the original paper, or there are some changes. I applied for the upload model on the official website but failed, may I ask, how did you apply
@Vipermdl @BeyondVE I used the pre-trained weights he published. According to my understanding, the results in KITTI test set are obtained by model training in the whole trainval set.
@Vipermdl @BeyondVE I used the pre-trained weights he published. According to my understanding, the results in KITTI test set are obtained by model training in the whole trainval set.
It seems to me that what the author released is a pre-trained weight that is only trained on the training set. The performance of their published weights on the validation set is consistent with the performance of our own reproduction. But the problem is that we cannot reproduce the test set performance, even if we use train+val data and make multiple attempts.
It seems to me that what the author released is a pre-trained weight that is only trained on the training set. The performance of their published weights on the validation set is consistent with the performance of our own reproduction. But the problem is that we cannot reproduce the test set performance, even if we use train+val data and make multiple attempts.
I have the same problem. What I want to know is how to choose the model with the best results when using the full training and validation set for training?
@Vipermdl @BeyondVE I used the pre-trained weights he published. According to my understanding, the results in KITTI test set are obtained by model training in the whole trainval set.
It seems to me that what the author released is a pre-trained weight that is only trained on the training set. The performance of their published weights on the validation set is consistent with the performance of our own reproduction. But the problem is that we cannot reproduce the test set performance, even if we use train+val data and make multiple attempts.
After training, how good is your validation set？
It seems to me that what the author released is a pre-trained weight that is only trained on the training set. The performance of their published weights on the validation set is consistent with the performance of our own reproduction. But the problem is that we cannot reproduce the test set performance, even if we use train+val data and make multiple attempts.
I have the same problem. What I want to know is how to choose the model with the best results when using the full training and validation set for training?
After training, how good is your validation set？
It seems to me that what the author released is a pre-trained weight that is only trained on the training set. The performance of their published weights on the validation set is consistent with the performance of our own reproduction. But the problem is that we cannot reproduce the test set performance, even if we use train+val data and make multiple attempts.
I have the same problem. What I want to know is how to choose the model with the best results when using the full training and validation set for training?
After training, how good is your validation set？
If train+val is used for training, the result of val cannot be used as a reference indicator. I used the last parameters for testing. According to the code of author, TTA may be used, but this requires the author to open source their complete code.
It seems to me that what the author released is a pre-trained weight that is only trained on the training set. The performance of their published weights on the validation set is consistent with the performance of our own reproduction. But the problem is that we cannot reproduce the test set performance, even if we use train+val data and make multiple attempts.
I have the same problem. What I want to know is how to choose the model with the best results when using the full training and validation set for training?
After training, how good is your validation set？
If train+val is used for training, the result of val cannot be used as a reference indicator. I used the last parameters for testing. According to the code of author, TTA may be used, but this requires the author to open source their complete code.
After training, what are the results of the verification set？can you reach the level of the paper,and why“If train+val is used for training, the result of val cannot be used as a reference indicator.” 。Thank you very much
It seems to me that what the author released is a pre-trained weight that is only trained on the training set. The performance of their published weights on the validation set is consistent with the performance of our own reproduction. But the problem is that we cannot reproduce the test set performance, even if we use train+val data and make multiple attempts.
I have the same problem. What I want to know is how to choose the model with the best results when using the full training and validation set for training?
After training, how good is your validation set？
If train+val is used for training, the result of val cannot be used as a reference indicator. I used the last parameters for testing. According to the code of author, TTA may be used, but this requires the author to open source their complete code.
After training, what are the results of the verification set？can you reach the level of the paper,and why“If train+val is used for training, the result of val cannot be used as a reference indicator.” 。Thank you very much
In my opinion MonoDETR is very unstable and needs to be repeated many times to get good results.
It seems to me that what the author released is a pre-trained weight that is only trained on the training set. The performance of their published weights on the validation set is consistent with the performance of our own reproduction. But the problem is that we cannot reproduce the test set performance, even if we use train+val data and make multiple attempts.
I have the same problem. What I want to know is how to choose the model with the best results when using the full training and validation set for training?
After training, how good is your validation set？
If train+val is used for training, the result of val cannot be used as a reference indicator. I used the last parameters for testing. According to the code of author, TTA may be used, but this requires the author to open source their complete code.
After training, what are the results of the verification set？can you reach the level of the paper,and why“If train+val is used for training, the result of val cannot be used as a reference indicator.” 。Thank you very much
In my opinion MonoDETR is very unstable and needs to be repeated many times to get good results.
The verification set effect of my model is two points lower than that of the paper. May I ask what your best verification set effect is
- The training process is relatively unstable, so please use the same config and try some times.2.Please Refer to this link: https://github.com/ZrrSkywalker/MonoDETR/issues/51. The code is upgraded for the better and stable performance. U could refer to the link and revise the code, then try the original ckpt. Or use the A100/ other GPU to train this version code.
在我看来，作者发布的是一个只在训练集上训练的预训练权重。他们公布的权重在验证集上的表现和我们自己复现的表现是一致的。但问题是，即使我们使用train+val数据，多次尝试，我们也无法复现测试集上的表现。
我也遇到同样的问题，我想知道在使用全量训练集和验证集进行训练时，如何选取效果最好的模型？
训练之后，你的验证集效果如何？
如果使用train+val进行训练，val的结果不能作为参考指标，我用了最后一个参数进行测试，根据作者的代码，可以使用TTA，但这需要作者开源他们的完整代码。
训练完验证集结果怎么样？能达到论文水平吗？为什么“如果用train+val进行训练，val的结果不能作为参考指标”。非常感谢
在我看来，MonoDETR 非常不稳定，需要重复多次才能获得良好的结果。
你好，你最终得到与论文中相近的测试集结果了吗？
我是用这个repo进行训练的结果，包含三个类别。
对于汽车类别的结果与你提交得到的结果相近。
- 训练过程相对不稳定，请使用相同配置多试几次。2.请参考此链接：将模型转为原始版本（在 3090 中运行） #51。代码已升级，性能更好更稳定。您可以参考链接修改代码，然后尝试原始 ckpt。或者使用 A100/其他 GPU 训练此版本代码。
您好，现版本的repo是最稳定的吗？我在一张RTX 4090上训练，是否需要修改如您之前提到的group_num以及注释https://github.com/ZrrSkywalker/MonoDETR/blob/main/lib/models/monodetr/depthaware_transformer.py中467-473行？
我尝试修改并在您公开的权重以及我训练的权重上测试，性能有进一步的下降。
是修改后，再次训练？