Novel engineering contribution implementing several papers to improve the quality of raster-to-vector conversion.
From our internal testing, it's the open-source SoTA, surpassed only by vectorizer.ai.
It is built in Rust, has a wasm based version you can play with, and 2 models (one for SR, one for denoising) to help it work better with in-the-wild images.
On PNGs, the benefit is smaller and mainly perceptual. dE00 actually decreases with the SR model but perceptual quality increases especially if the original raster was very low resolution.
On JPEGs or other lossy compression inputs, both models help significantly. They've been trained with slightly different objectives. The SR one uses standard SR loss (with extra weighting near borders), the denoiser is trained to enforce the axioms that the vectorizer uses so it's the one that's recommended for production.
I haven't tried running both at the same time, but it might be worth experimenting. Both are open weight so you can check yourself if curious.
Novel engineering contribution implementing several papers to improve the quality of raster-to-vector conversion.
From our internal testing, it's the open-source SoTA, surpassed only by vectorizer.ai.
It is built in Rust, has a wasm based version you can play with, and 2 models (one for SR, one for denoising) to help it work better with in-the-wild images.
https://huggingface.co/spaces/Logolabs/inkvec
Really nice work. Curious how much of the quality gain comes from the SR/denoising models vs the vectorization algorithm itself?
On PNGs, the benefit is smaller and mainly perceptual. dE00 actually decreases with the SR model but perceptual quality increases especially if the original raster was very low resolution.
On JPEGs or other lossy compression inputs, both models help significantly. They've been trained with slightly different objectives. The SR one uses standard SR loss (with extra weighting near borders), the denoiser is trained to enforce the axioms that the vectorizer uses so it's the one that's recommended for production.
I haven't tried running both at the same time, but it might be worth experimenting. Both are open weight so you can check yourself if curious.
https://huggingface.co/Logolabs/inkvec-denoiser-001 https://huggingface.co/Logolabs/inkvec-sr-001