Comments (6)
However, tha main issue is actually that the model does not seem to work on the current official Caffe version (see #29).
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Hi @michaelschwier , I think we used a cropping layer which is different from what original Caffe currently has, and it has a slightly different behavior.
The error you get when using the Docker image is most probably some Nvidia Driver and CUDA compatibility issue. The docker image uses an older CUDA, like 6.5 or 7.
Have you tried to install an older Nvidia driver ? for example Nvidia driver 367.57, it is compatible with Titan X, Titan X Pascal and Titan Xp and various other Nvidia GPU models but you have to check if your GPU is supported.
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@michaelschwier this comment highlights the difference between Jonlong's caffe version (the one we used) and the original caffe version : #3 (comment)
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Hi @mohamed-ezz, thank you for your answer. I gave up on the Nvidia Docker, but managed to get a CPU-only version running buy building Jonlong's caffe version. Thank you for the hint to #3.
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@michaelschwier So is the problem solved yet ?
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@mohamed-ezz I'd consider it solved for me, the CPU version is enough for my purposes. Thanks!
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Related Issues (20)
- The dropbox link of weights.caffemodel were expired HOT 6
- Model Address invalidation? HOT 2
- Why is my prediction so bad?
- Batch normalization not used? Step2 dataset? HOT 3
- question HOT 3
- Input image sizing HOT 2
- #question. Do we need to train for step 2 in cascaded FCN? HOT 1
- #Question:The results in the Docker are inconsistent with the illustrations in the paper
- Class Weight Selection HOT 1
- Pretrained TensorFlow Models HOT 5
- Result is very worse followed by the ipynb file HOT 3
- A question about training sets and metrics
- Question:The results for the code are error HOT 11
- Need help in preprocessing HOT 1
- Issue with prediction method
- Weights for MRI model
- TypeError: slice indices must be integers or None or have an __index__ method`
- How testing and training is done
- training data format HOT 2
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