Printed comics are rendered using halftone screening — a process where continuous tones are broken into grids of tiny dots or lines so that they can be reproduced with a fixed-colour ink. When you scan a printed page, those dot patterns are captured by the scanner and appear as a visible repeating texture in the digital image. Descreening removes this printing artefact while reconstructing the smooth tonal gradients and clean linework that existed in the original artwork. Unlike a simple blur, the descreen models are trained to distinguish halftone structure from real image detail and to leave edges, hatching, and fine lines untouched.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/ollm/opencomic-ai-training/llms.txt
Use this file to discover all available pages before exploring further.
Dataset
Each descreen model was trained on 120,000 image pairs with 10 degraded variants per clean image. The training data combines four dataset splits to expose the model to the full variety of halftone patterns it will encounter in real scans:opencomic-ai-descreen-hard— hard dots at a fixed 45° angleopencomic-ai-descreen-hard-moire— hard dots plus moiré interference patternsopencomic-ai-descreen-hard-any-angle— hard dots at random anglesopencomic-ai-descreen-hard-moire-any-angle— hard dots at random angles with moiré
- Hard dot halftones at standard print angles (45°)
- Hard dot halftones at arbitrary angles (full rotation range)
- CMYK multi-channel halftones (added in v2.0)
Model Variants
All three variants operate at 1× scale and produce NCNN weight files as a.bin + .param pair.
| Model | Architecture | NCNN Path | Iterations |
|---|---|---|---|
opencomic-ai-descreen-hard | ESRGAN | models/descreen/ncnn/ | 1,000,000 |
opencomic-ai-descreen-hard-lite | ESRGAN Lite | models/descreen/ncnn/ | 1,000,000 |
opencomic-ai-descreen-hard-compact | Compact | models/descreen/ncnn/ | 450,000 |
Pre-Trained From Artifact Removal
Each descreen model is fine-tuned from its corresponding artifact removal checkpoint rather than trained from scratch:| Descreen Model | Pre-trained From |
|---|---|
opencomic-ai-descreen-hard | opencomic-ai-artifact-removal |
opencomic-ai-descreen-hard-lite | opencomic-ai-artifact-removal-lite |
opencomic-ai-descreen-hard-compact | opencomic-ai-artifact-removal-compact |
Preserving Detail — v2.0 Improvements
OpenComic AI v2.0 made targeted improvements to prevent the descreen model from over-processing non-halftone content. The training dataset was extended to include circles and circles with a dot inside (such as eyes and irises) so the model learns to leave them untouched. Parallel lines and grids (such as ruled panels, crosshatching, and screen tones that are not halftones) were also added as negative examples. Additionally, a fix was applied to prevent the model from brightening very dark images or hard edges that happen to be adjacent to a halftone area.