Live capabilities

See what
ThirdEye sees.

Three models. Built for unstructured driving environments. Running in real time.

Model 01 / Semantic Segmentation

Every pixel, classified.

Our SEGFormer model -- fine-tuned on the IDD dataset -- labels every pixel across 28 road-specific classes: roads, autorickshaws, cattle, cyclists, tunnels, and more.

Drag the divider to reveal the segmentation layer.

28 classes -- IDD-trained -- 30fps -- Explore dataset on HuggingFace

Model 02 / Object Detection

What's on the road.

Our YOLO model -- trained on real-world unstructured road data -- detects and classifies every road user in a frame. Filter by object class to isolate what matters.

15 classes -- YOLOv11m architecture -- Explore dataset on HuggingFace

Model 03 / Scene Classification

Context at a glance.

Using CLIP zero-shot classification, ThirdEye identifies driving conditions from a single frame. Weather, road type, and time of day, all inferred automatically.

01 -- Weather

02 -- Scene

Select a weather condition first

03 -- Time of Day

Select a scene type first

56 unique conditions captured -- 4 weather states -- 6 scene types -- 4 times of day

Behind the demos

Real-world data.
Open on HuggingFace.

Every frame above was captured, processed, and labeled entirely by ThirdEye's pipeline -- no external datasets, no synthetic data.

Explore dataset Get in touch