FFCV Imagenet Image Quality vs. Native Imagenet Image Quality
See original GitHub issueHello! I see that FFCV offers alot of options for the quality of the dataset - e.g. in the imagenet example:
# - 50% JPEG encoded, 90% raw pixel values
# - quality=90 JPEGs
./write_dataset.sh 500 0.50 90
One thing I’m curious is the effects of these quality options on the training results of the dataset, as I’m interested in reproducing Imagenet results but faster using FFCV. What would also be recommended settings to use if you would like to produce Native Imagenet Quality precisely (barring the crop size).
Issue Analytics
- State:
- Created 2 years ago
- Comments:11 (3 by maintainers)
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Just to add: for our ImageNet results (the speed/accuracy tradeoff scatterplot and table), we use:
I think this thread has been dealt with. @YassineYousfi Feel free to start a new conversation about these specific topics.