Comments (4)
taigw
commented on August 22, 2024
This is because the number of LGG images is much smaller than that of HGG images.
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siddharthamantrala
commented on August 22, 2024
Is it possible to train without a GPU?
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siddharthamantrala
commented on August 22, 2024
Do I need to change the directory paths in the Job_test file to test the code with the dataset, even if i dont have a GPU?
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taigw
commented on August 22, 2024
A GPU is required for training. Otherwise the training process would be very slow.
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Related Issues (20)
- Regarding subimage patch and label size HOT 7
- ERROR (nifti_image_write_hdr_img2): cannot open output file HOT 11
- the validation data segmentation result HOT 3
- How to use multi-gpu? HOT 1
- Do I have to rewrite test.py when I define the network without NiftyNet? HOT 1
- About the size of data_shape HOT 9
- UnboundedLocalError: local variable referenced before assignment.
- Activation Layer Before Convolution layer in ResBlock HOT 1
- net1 output is null HOT 2
- Can I stop training early?
- Some questions about data_root
- test_one_image_three_nets_adaptive_shape function
- Config File Generation for brats 2018 Data
- Overlap in Train/Test Data
- How to enable NiftyNet's balanced window sampler?
- loss is not declined HOT 1
- OOM about training with brats17 data HOT 1
- Error: Provided indices are out-of-bounds
- No module named 'util'
- Where can we find the labels for Brats 2015 dataset?
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