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morphospaces
/
train_swin_unetr_pixel_embedding
/ 0.0.2
Train SwinUnetr Pixel Embedding Network
Train the SwinUnetr pixel embedding network using the provided script and dataset.
Tags
imaging
cryoet
Python
napari
Citation
Morphospaces team.
https://github.com/morphometrics/morphospaces
Solution written by
Kyle Harrington
License of solution
MIT
Source Code
View on GitHub
Arguments
--lr
Learning rate. (default value: PARAMETER_VALUE)
--logdir_path
Path to save logs and checkpoints. (default value: PARAMETER_VALUE)
--batch_size
Batch size for training. (default value: PARAMETER_VALUE)
--patch_threshold
Patch threshold. (default value: PARAMETER_VALUE)
--loss_temperature
Loss temperature. (default value: PARAMETER_VALUE)
--pretrained_weights_path
Path to pretrained weights. (default value: PARAMETER_VALUE)
--max_epochs
Maximum number of epochs for training. (default value: PARAMETER_VALUE)
--copick_config_path
Path to the Copick configuration JSON file. (default value: PARAMETER_VALUE)
--train_run_names
Comma-separated list of Copick run names for training data. (default value: PARAMETER_VALUE)
--val_run_names
Comma-separated list of Copick run names for validation data. (default value: PARAMETER_VALUE)
--voxel_spacing
Voxel spacing to be used. (default value: PARAMETER_VALUE)
--tomo_type
Type of tomogram to process. (default value: PARAMETER_VALUE)
Usage instructions
Please follow
this link
for details on how to install and run this solution.