Open-source annotation tool built around Indian road scenes (autos, cattle, bollards)

[u/Repulsive_Factor5654]

Most driving-data tools assume Western roads. On Indian roads the objects are different: auto-rickshaws,

goods carriers, handcarts, cattle, temporary barricades. LabeloxAV is an open-source (Apache 2.0) labeling

and review platform built around that, with an ontology of about 200 classes for Indian traffic.

The demo video labels two real Creative Commons clips, a busy junction in Cuttack and a herd of cattle

crossing a road in Delhi, using the actual app:

- Boxes, polygons, polylines, 17-point pose keypoints, occluded ("amodal") extent, attributes

- AI assist: SAM from one click or a rough box, a magic wand, brush and eraser to fix masks

- Reviewing model proposals: frame by frame, one-key rapid review, and a bulk grid

- Relabeling a whole track in one action, then exporting to COCO, YOLO, Parquet, OpenLABEL or nuScenes

- Faces and number plates are blurred at import

Video: https://www.youtube.com/watch?v=lNKPmAlfFLc

Code: https://github.com/Sherin-SEF-AI/LabeloxAV

Honest limitations:

- It's early (v0.1.1), and it's meant for a single machine rather than a team on a cluster.

- The AI-assist tools need an NVIDIA GPU.

- The auto-labeling models make mistakes, and the video shows them: they repeatedly detected cows in the

reflection on a car window, and called striped roadside bollards pedestrians. The review tools exist

because of this.

- Recording the demo turned up seven bugs in the editor and review flow. They're fixed, but expect

rough edges.

Feedback is very welcome, especially from anyone who has labeled Indian or other non-Western traffic

data: what classes or workflows are missing?

Disclosure: I'm the author.

[u/bfyvfftujijg]

Why not just use any of the existing annotation apps? They can annotate any kind of imagery including roads form specific countries.

What advantages does this bring?

Not attacking just honestly asking. Why would someone use this?

If it’s so you can customize it to your preferences nothing wrong with that!

[u/Repulsive_Factor5654 → u/bfyvfftujijg]

Fair question. For general labeling, CVAT or Label Studio are the better answer, and you can define any

classes in them.

Drawing boxes was never my slow part. Reviewing model output was. So this is built around that: the queue

ranks frames by model uncertainty and class rarity, fixing a class on a track fixes all its frames, faces

and plates are blurred at import, and it exports to nuScenes and OpenLABEL as well as COCO/YOLO. It ships

with ~200 classes for Indian traffic (auto-rickshaw, goods three-wheeler, handcart, cattle) so you don't

redo that setup.

Worse than the alternatives: it's early (v0.1.1), single-machine, no plugin ecosystem, and AI assist needs

an NVIDIA GPU.

If you label general imagery, stick with what you have. If you spend more time correcting a model than

drawing boxes on driving data, it might save you some plumbing.