Comments (10)
It because the return format of zip() is different between python2 and 3.
change the line grads_and_vars = zip(clipped_grads, tvars)
in optimizer/generic_optimizer.py to grads_and_vars = list(zip(clipped_grads, tvars))
, it works for me.
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It seems to be python-related, I changed from python 3.5 to python 2.7 and the KITTI training works out of the box now.
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Hi WPSanberg,
It seems to me that we are meeting the similar problem, i posted my question in the previous thread.
Wenouyang
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Hello , I don't know where the problem is in what you did ,
but I've trained the model on my own dataset and it did work , I'll tell what I did , maybe it will help ,
I mainly changed the input file , and set it up so that it loads the images directly from train and validation folders , after loading it resizes them to the same resolution as Kitti images , and then it gets the ground truth mask from the hypes , and use it to read the 'gt_images' and separate it into the different classes, the rest I didn't touch ... hope it helps
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To me this looks like the tensor loss
/total_loss
is not well defined. Can you check, whether the loss function actually gets computed correctly?
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Hi Marvin,
It indeed seems to be about the loss, the error rises in tensorvisions def build_training_graph(hypes, queue, modules):
at this segment:
with tf.name_scope("Loss"): losses = objective.loss(hypes, decoded_logits, labels)
but I am not sure how to trace it beyond that.
By the way, I get the same error message if I try to run the training process with the original configuration on the KITTI data.
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Yeah, if I find some spare time, I will look into python 3.5. In theory it should work out of the box.
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@WPSanberg how to comment out line 123,train.maybe_download_and_extract(hypes),it should be what
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@WPSanberg how to comment out line 123,train.maybe_download_and_extract(hypes),it should be what
Nothing. Just go to Format and Comment out that region.
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Related Issues (20)
- Can not download pretrained model ftp://mi.eng.cam.ac.uk/pub/mttt2/models/KittiSeg_pretrained.zip HOT 3
- redundant patches in my training data
- Question for Precision Calculation HOT 3
- error in running demo.py , TimeoutError and URLError HOT 1
- Training image size is not the same,Does It can training? HOT 1
- What about the inference speed ?
- I got an error when running 'train.py' HOT 3
- how to output the pool layers as features?
- How to evaluate BEV result just like KITTI server? HOT 1
- PR-curve
- Issues report
- How to run this on video HOT 1
- Attribute error module scipy.misc has no attribute imread HOT 2
- 哈哈谢谢大兄弟咯,我训练出来了,待会在kitti测试集上测评一下
- Trained model
- Testing with grayscale images
- Unable to train my own dataset HOT 2
- I got this error while running python train.py
- IOError: [Errno ftp error] proxy support for ftp protocol currently not implemented
- Cannot download KittiSeg_pretrained.zip HOT 3
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