Skip to main content

Converter for Large Image.

Project description

Convert a variety of images into the most efficient format for Large Image.

Geospatial files are converted into cloud-optimized geotiff via gdal_translate. Single-image non-geospatial files are converted into pyramidal tiff files via pyvips. Multi-image tiff files are converted into tiff files with multiple pyramidal tiff images and have a custom image description to store frame details.

Some files can be read via the various tile sources in large_image without conversion but are inefficient (for example, uncompressed data in nd2 files). Converting these files will result in more efficient data access.

Installation

To install via pip with custom-built wheels:

pip install large-image-converter[sources] --find-links https://girder.github.io/large_image_wheels

The [sources] extra requirement is optional. When specified, all of the default large-image tile sources are installed for additional metadata extraction and format support.

Requirements

If the custom-built wheels do not cover your platform, or you want to use different versions of tools, you can install the prerequisites manually. For full functionality, the following packages and libraries are needed:

  • GDAL 3.1.0 or greater, including the command-line tools and the python library

  • libtiff, including the command-line tools

  • libvips

Additionally, the various tile sources for large_image can be used to read input files to extract and preserve metadata and to read files that can’t be read via libvips or GDAL. The requirements of those sources need to be installed.

Usage

Command Line

In the simplest use, an image can be converted via:

large_image_converter <source path>

An output image will be generated in the same directory as the source image.

The full list of options can be obtained via:

large_image_converter --help

From Python

The convert function contains all of the main functionality:

from large_image_converter import convert

convert(<source path>)

# See the options
print(convert.__doc__)

From Girder

The converter is installed by default when girder-large-image is installed. It relies on Girder Worker to actually run the conversion.

The conversion task can be reached via the user interface on the item details pages, via the createImageItem method on the ImageItem model, or via the POST item/{itemId}/tiles endpoint.

Limitations and Future Development

There are some limitations that may be improved with additional development.

  • For some multi-image files, such as OME Tiff files that cannot be read by an existing large_image tile source, the specific channel, z-value, or time step is not converted to readily usable metadata.

  • Whether the original file is stored in a lossy or lossless format is not always determined. If unknown, the output defaults to lossless, which may be needlessly large.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

large-image-converter-1.17.0.tar.gz (21.1 kB view details)

Uploaded Source

Built Distribution

large_image_converter-1.17.0-py3-none-any.whl (21.7 kB view details)

Uploaded Python 3

File details

Details for the file large-image-converter-1.17.0.tar.gz.

File metadata

File hashes

Hashes for large-image-converter-1.17.0.tar.gz
Algorithm Hash digest
SHA256 05bdb847832aec695195c9efb97758bd9d617c56727f7288004559f4caa4c457
MD5 8746fda22cf89567b9815c8aed660e9a
BLAKE2b-256 95402f6d2f36b89fb47921b41e9406e190b53f551d27a4c46b223fcced255e7d

See more details on using hashes here.

Provenance

File details

Details for the file large_image_converter-1.17.0-py3-none-any.whl.

File metadata

File hashes

Hashes for large_image_converter-1.17.0-py3-none-any.whl
Algorithm Hash digest
SHA256 29239da224c1a453120a78eea03a2378b6c711bcbf828943d4fb6ea57e4500af
MD5 3a2a9692936149e279044c91042f54b6
BLAKE2b-256 021a2d0c52312ff459e9452015278b1bea948d1f4a505c12f2e08f8b31753978

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page