copick / generate-torch-basic-features / 0.0.7

Generate Multiscale Basic Features with Torch using Copick API (Chunked, Corrected)

Compute multiscale basic features of a tomogram from a Copick run in chunks and save them using Copick's API.
Tags
imagingcryoetPython
Solution written by
Kyle Harrington
License of solution
MIT
Source Code

Arguments

--copick_config_path
Path to the Copick configuration JSON file. (default value: PARAMETER_VALUE)
--run_name
Name of the Copick run to process. (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)
--feature_type
Name for the feature type to be saved. (default value: PARAMETER_VALUE)
--intensity
Include intensity features (default value: 1)
--edges
Include edge features (default value: 1)
--texture
Include texture features (default value: 1)
--sigma_min
Minimum sigma for Gaussian blurring (default value: 0.5)
--sigma_max
Maximum sigma for Gaussian blurring (default value: 16.0)
--num_sigma
Number of sigma values between sigma_min and sigma_max for texture features. (default value: 5)

Usage instructions

Please follow this link for details on how to install and run this solution.