Code is now in the repo — ‘’’pip install numpy Pillow’’’ where you can duplicate the values.
Kodim might seem outdated, but it’s still the primary benchmark cited in learned image compression research (CLIC, neural codec papers) and is referenced across hundreds of published works.
The question isn’t whether newer capture pipelines produce different data — they do — but whether the research community understands the statistical structure of the benchmark it’s been using for thirty years.
Think of data dependent things like - compression?