Learnings from training a font recognition model from scratch

Learnings from training a font recognition model from scratch(mixfont.com)

35 points by justswim 64 days ago | 7 comments

Surely the next step is to tweak the open source font with AI to slightly better target the desired font?

Sometimes you're trying to replicate a logo and they've hand tweaked a letter or two, or stretched it.

edit: (Google Fonts actually have fonts you can natively stretch and some with replacement character variants) I wonder if the tool uses that to better match?)

Sometimes you just don't want to pay for a fancy font and I believe font shapes are not copyrightable?

hank_z 59 days ago |

I’m curious to know how this model tackles newly released fonts. How difficult would it be if this model needs to recognise font in a different language?

Tommix11 59 days ago |

Graphic designer here. A font recognition ai is sorley needed. Gemini and its competitors flat out lie when asked and Adobe Illustrators Retype is laughably bad. The problem I face almost every day is not to find a close match but to find the actual font in use, commercial or not.

WillAdams 59 days ago | |

whatthefont and identifont used to work well, but they've been overwhelmed by new designs which are not used often enough to warrant inclusion.

I just use Rookledge's Type Finder and a battered copy of Precision Type 5.0

codemog 59 days ago |

Curious why the model architecture wasn’t talked about at all? Did I miss that part?

g58892881 59 days ago | |

pretty basic

``` from torchvision import models

# Avoid downloading pretrained weights; we load trained checkpoint weights. model = models.resnet18(weights=None) model.fc = nn.Linear(model.fc.in_features, num_classes) ```

https://github.com/mixfont/lens/blob/main/lens_inference.py#...

Terretta 63 days ago |

Instructive, with a rewarding repo for your time.