LibreLingBotVision Semantic Segmentation
Collection
LingBot-Vision self-supervised ViT backbones (Apache-2.0) with LibreYOLO-trained dense heads for ADE20K semantic segmentation. • 3 items • Updated
LibreLingBotVisionb-sem
LingBot-Vision ViT-B/16 (86M backbone) self-supervised backbone with a LibreYOLO-trained 1x1 dense head for ADE20K 150-class semantic segmentation at 512x512.
Source
The backbone derives from robbyant/lingbot-vision ("Vision Pretraining for Dense Spatial Perception", Fu et al., 2026, arXiv:2607.05247), weights from robbyant/lingbot-vision-vit-base. Copyright (c) 2026 Robbyant. Licensed under the Apache License 2.0.
Modifications
The backbone tensors are unchanged (the LibreYOLO port is parity-verified at
max_abs_diff == 0 against the reference implementation). The dense head is a
1x1 convolution over the frozen patch-token grid, trained by LibreYOLO on
ADE20K following the linear-probing protocol of the upstream technical
report (ADE20K val mIoU 50.1 at 512x512, single scale; upstream linear-probe reference 51.4). Conversion and metadata wrapping:
weights/convert_lingbotvision_weights.py in the
LibreYOLO source repository.
Usage
from libreyolo import LibreYOLO
model = LibreYOLO("LibreLingBotVisionb-sem.pt")
results = model.predict("image.jpg")
results.save("out.jpg")
Fine-tune on your own semantic dataset (head-only by default, matching the
linear-probe recipe; pass freeze_backbone=False for a full fine-tune):
model.train(data="your_semantic.yaml", epochs=20)
License
Apache License 2.0. See the LICENSE and NOTICE
files in this repository.
Dataset Note
ADE20K has separate dataset terms and is not redistributed in this repository.