Introduction - cvpl_tools documentation

This tool provides useful visualization and processing APIs for image files. Built on top of:

• Napari

• ome-zarr-py

• Numpy, Scipy and scikit-image

These pip dependencies and their versions are same as SPIMquant. If dependency conflicts in other places, let me know.

Installation of cvpl_tools using pip (Note Napari viewer requires one of pyqt or pyside2 installed.)

pip install cvpl_tools[nnunet]

Now you can go to GettingStarted/ome_zarr to learn how to view an OME_ZARR image locally or on cloud.

Contents:

• Introduction
• Quickstart
  • Installation
  • OME ZARR
  • nn-UNet
• Viewing and IO of OME Zarr
  • Viewing of ome zarr file
  • Reading and Writing ome zarr files
  • Specifying slices in path
• Setting Up the Script
  • Dask Cluster and temporary directory
  • Dask Logging Setup
  • cache directory
  • A Quicker Setup
• Defining Segmentation Pipeline
  • Motivation
  • SegProcess
  • Extending the Pipeline
  • Running the Pipeline
• Result Caching
  • Overview
  • cache directory
  • Tips
• nn-UNet
  • Overview
  • Negative Masking for Mouse-brain Lightsheet
  • Annotation
  • Training
  • Prediction
  • Annotation Using Syglass
• Beta-Amyloid Plaque Detection
  • Workflow Overview
  • Python Implementation
• Dev Setup
  • Poetry
  • Documentations
  • Unit Testing
  • Misc

API Reference

• cvpl_tools.ome_zarr.napari.add.py
  • group()
  • subarray()
  • group_from_path()
  • subarray_from_path()
• cvpl_tools.ome_zarr.io.py
  • load_zarr_group_from_path()
  • load_dask_array_from_path()
  • write_ome_zarr_image()
• cvpl_tools.tools.fs.py
  • cdir_init()
  • cdir_commit()
  • cdir_query()
  • save()
  • load()
  • display()
• cvpl_tools.im.ndblock.py
  • NDBlock
  • ReprFormat
• cvpl_tools.im.process
  • block_to_block_forward()
  • lc_interpretable_napari()
  • in_to_bs_custom()
  • in_to_bs_simple_threshold()
  • in_to_lc_blobdog_forward()
  • in_to_cc_sum_scaled_intensity()
  • bs_lc_to_os_forward()
  • bs_to_os
  • lc_to_cc
  • os_to_cc
  • os_to_lc
  • any_to_any
• cvpl_tools.im.algs
  • label()
  • scale_nearest()
  • affine_transform_nearest()