# streamlit/demo-self-driving

Streamlit app demonstrating an image browser for the Udacity self-driving-car dataset with realtime object detection using YOLO.

Repository: https://github.com/streamlit/demo-self-driving
Canonical: https://ross.abutalabs.com/products/demo-self-driving
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2026-01-09T15:37:07+00:00

## Health v2 (maintenance only)
Score: 60/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 61, release rhythm 35, longevity 100
- inputs: {"age_days": 2553, "days_push": 236, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1290, forks 472 (observed 2026-08-28T04:04:15.495828+00:00)

## What it is
A Streamlit demo app that provides an interactive image browser for the Udacity self-driving-car dataset with realtime YOLO object detection, implemented in under 300 lines of Python. It serves as an official example illustrating Streamlit's major building blocks.

## Use cases
- browse and explore the udacity self-driving car dataset images
- run realtime yolo object detection on images
- learn how to build a streamlit app
- demo computer vision models in an interactive web app
- example of image annotation visualization

## When to choose
- you want a ready-made example of object detection in a Streamlit app
- you are learning Streamlit and want to see its building blocks in action
- you need a quick interactive browser for the Udacity self-driving dataset

## When to avoid
- you need production-grade object detection pipelines
- you want a general-purpose image annotation or labeling tool
- you don't use Python or Streamlit

## Facets
- artifact type: application
- maturity: stable
- function: image-processing, computer-vision, data-visualization
- domain: computer-vision, autonomous-vehicles, data-visualization, machine-learning
- platform: python, cross-platform
- tags: streamlit, yolo, object-detection, udacity-dataset, demo-app, image-browser, web-server

## Member repositories
- streamlit/demo-self-driving (main) score 60

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:15.495828+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:55:40.710676+00:00, confidence not recorded.
  - readme: https://github.com/streamlit/demo-self-driving (fetched 2026-08-28T04:04:15.495828+00:00, sha 6336fdd8d86e)
- Data as of 2026-08-30T08:39:29.467469+00:00.