Example Usage - Predefined Tasks | Anchor Image Analysis

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Introduction

Some tasks are included in the Anchor distribution, to be easily run from the command-line with -t taskname, and are termed predefined tasks.

Tip: See Example Usage for step-by-step guides on using these tasks. A good starting point!

To list the names of all available predefined tasks, type in a shell either:

A user can extend the available predefined tasks, by adding BeanXML to the /config/tasks subdirectory in an Anchor distribution.

To run a task, open a shell (e.g. Command Prompt or Powershell in Windows), change to a directory with images, and then:

Next, consider enabling additional outputs with the -o options or refining your inputs with the -i options.

Tip: In Windows, hold the shift key when right-clicking on a folder in Windows Explorer to open a Command Prompt or Powershell in that folder.

See some Quick Start - Example Commands and the following tables for guidance.

Task Name	Input Type	Description
histogram	images	extracts histograms of the intensity values an image.
resize	images	scales each image to fit inside fixed dimensions, preserving aspect ratio. Optionally accepts -ps.
center	images	like `resize` but uses a common output size for all images, and centers within it. Optionally accepts -ps.

Task Name	Input Type	Description
segment/coco	images	instance segmentation based on 80 MSCOCO object categories.
segment/text	images	finds text-regions in images.

Task Name	Input Type	Description
feature/hog	images	extracts a HOG feature descriptor for all images.
feature/intensity	images	extracts statistics of pixel values.
feature/metadata	images	extracts basic metadata as features, including dimensions.

Task Name	Input Type	Description
cluster/timestamp	any files	clusters files by timestamp (from (from EXIF, file attributes or naming).

Task Name	Input Type	Description
anonymize	any files	copies files, randomizing order and hiding the original naming.
convert	images	converts the file format** of input images.
copy	any files	copies files, preserving naming and subdirectory structure.

Task Name	Input Type	Description
montage	images	creates a montage that balances available space.
montage/balance	images	identical to above.
montage/table	images	creates a montage that imposes a table structure.
montage/slices	images	creates a montage of all z-slices in a 3D image.

Task Name	Input Type	Description
count	any files	counts the number of input-files.
list	any files	shows a line `inputName -> inputPath` for each input.
list/names	any files	shows each input’s name on a separate line.
list/paths	any files	shows each input’s path on a separate line.
summarize	images	combines the summaries in `summarizeImages` and `summarizePaths`
summarize/images	images	summarizes image attributes (dimensions, bit depth etc.)
summarize/paths	any files	summarizes file attributes (size, patterns among the file-paths etc.)

Task Name	Input Type	Description
project/mean	images	creates a mean-intensity projection of all inputs.
project/meanResize	images	scales inputs to a constant size, then the `mean` projection.
project/max	images	creates a maximum-intensity projection of all inputs.
project/maxResize	images	scales inputs to constant size, then the `max` projection.
project/min	images	creates a minimum-intensity projection of all inputs.
project/minResize	images	scales inputs to constant size, then the `mean` projection.
project/standardDeviation	images	creates a standard-deviation projection of all inputs.
project/standardDeviationResize	images	scales inputs to constant size, then the above projection.