v1.4 — natural-image models of the paper, earlier-submission and channel-ablation checkpoints

The natural-image models of the paper, the scribble model of the earlier submission and the channel-ablation models.

File	Size	What it is	Notes
detfill_scribble_imagenet_64ch_200ep.pth	485 MB	Natural-image (ImageNet subset) scribble model, 64 base channels	The model behind the supplementary ImageNet tables (configs/scribble_real.yaml). Re-evaluated on 24 test images: PSNR Hint-AUC 18.4 (printed 18.0).
detfill_dot_imagenet_64ch_200ep.pth	485 MB	Natural-image dot model, 64 base channels	The model behind the supplementary ImageNet tables (configs/dot_real.yaml; its conditioning stage has 3 channels, as released). Re-evaluated on 24 test images: PSNR Hint-AUC 15.0 (printed 15.7).
detfill_scribble_illust_earlier_64ch_200ep.pth	485 MB	Scribble model of the earlier submission (64 base channels)	Its archived config samples with 1,000 steps (sample_step: 1000); superseded by the 96-channel v1.0 model retrained for the revision.
detfill_scribble_illust_32ch_200ep.pth	129 MB	Scribble model, 32 base channels, 200 epochs	Supplementary channel-ablation figure ("C = 32"). Use configs/scribble_illust.yaml with model_channels: 32.
detfill_scribble_illust_64ch_200ep.pth	485 MB	Scribble model, 64 base channels, 200 epochs	Channel ablation. model_channels: 64.
earlier_run_configs.tar.gz	2 KB	The archived training configs of these models	argparse-namespace YAML files.

The main tables of the paper use the v1.0 checkpoints. Reproduction example: EXAMPLES_MODE=full bash reproduce/examples/run_examples.sh runs the 32/64/96-channel comparison (E8) and the earlier scribble model (E11) on the example images. SHA-256 sums: SHA256SUMS.txt and checkpoints/README.md.