Htj2k
A project to evaluate htj2k for IIIF
Install / Use
/learn @IIIF/Htj2kREADME
htj2k
This is a IIIF community project to evaluate the new htj2k standard and its applicability to IIIF. We intend to test a number of different jp2 libraries and Pyramid tiffs to compare htj2k to this existing formats.
This repository will be a place to publish our data and scripts so others can scrutinise our results.
Presentations & reports
Creating jp2s, htj2k images and ptiffs
We have created various scripts in the convert directory to convert a source TIFF file to the various formats we are using for the testing. You can run each of the scripts to convert a single file or use the convert.sh command to convert a directory of images. See the convert readme
For our testing we have been using source tiff files from the Getty but the scripts should work with tiffs from other organisations.
You will need to install the following programs to generate some of the derivatives:
- LibVIPS for Pyramid Tiffs.
- Kakadu for generating htj2k files and jp2s
- OpenJPEG a jp2 library
- Grok a jp2 library
Running the image server
We have a docker setup to test OpenJpeg and Kakadu and details can be found in the image_server README.md.
Test scripts
We are using locust for our testing and you can find the testing scripts in the load_test directory.
The fromList locustfile will test a set of IIIF urls against lossy and lossless versions of jp2, htj2k and ptiff files. It can be run as follows:
cd load_test/fromlist
locust -u 1 --autostart --url-list ../../data/50_images/mirador_urls.txt --host http://0.0.0.0:8000
Note you must have the image server running on port 8000 as configured in the supplied Docker.
Related Skills
node-connect
347.9kDiagnose OpenClaw node connection and pairing failures for Android, iOS, and macOS companion apps
frontend-design
108.7kCreate distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
openai-whisper-api
347.9kTranscribe audio via OpenAI Audio Transcriptions API (Whisper).
qqbot-media
347.9kQQBot 富媒体收发能力。使用 <qqmedia> 标签,系统根据文件扩展名自动识别类型(图片/语音/视频/文件)。
