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.
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
Built Distribution
File details
Details for the file large-image-converter-1.15.2.dev49.tar.gz.
File metadata
- Download URL: large-image-converter-1.15.2.dev49.tar.gz
- Upload date:
- Size: 21.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.7.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 70984ec7383798a7c2b22ce920aed9d62a1f9851909d484a907463ed298d65b7 |
|
| MD5 | 90541c804476db65b1920167fe1d5441 |
|
| BLAKE2b-256 | 3e21e779b06174685ce70f90e1df24997f8676510adf945beda4291bd67276b3 |
Provenance
File details
Details for the file large_image_converter-1.15.2.dev49-py3-none-any.whl.
File metadata
- Download URL: large_image_converter-1.15.2.dev49-py3-none-any.whl
- Upload date:
- Size: 21.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.7.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | b373563eaada059b297aec583ff5a367843cf2a890b68da6ae0249e9307275fd |
|
| MD5 | 0ca6450f5e12d51f0224b9e828d22cec |
|
| BLAKE2b-256 | 05365d45019635ad3679f0fbf3f1c17732d177128b20f6aaa29ea9bf842e5054 |
