Polished and well engineered. Punching above its star count.

[ECCV 2026] Official code of “MindDrive: A Vision-Language-Action Model for Autonomous Driving via Online Reinforcement Learning”

Documentation

94

Contributing guide5pt77

CONTRIBUTING guide found.

Install and run instructions9pt90

README documents how to install the project.

README12pt100

README is present.

License6pt100

Licensed under Apache-2.0.

Engineering

78

Issue and PR templates6pt0

No issue or PR templates found (−100 pts).

Add .github/ISSUE_TEMPLATE/ with bug_report.md and feature_request.md to guide contributors. It dramatically improves issue quality.

Tests18pt80

Test files detected (mmcv/datasets/pipelines/test_time_aug.py).

Reproducibility6pt80

Lockfile present (requirements.txt). Installs are reproducible.

CI/CD14pt100

CI is configured (rl_projects/scenario_runner/Jenkinsfile).

Linting and formatting5pt100

Linter or formatter configured (rl_projects/scenario_runner/.pylintrc).

Project health

91

Housekeeping3pt40

No .gitignore found (−60 pts).

Add a .gitignore to keep build output, node_modules, and secrets out of version control.

Dependency manifest6pt100

Dependency manifest found (requirements.txt).

Repository metadata5pt100

Repository has a description.

Activity5pt100

Actively maintained (pushed within the last month).

Repository health signals

Activity, community, and responsiveness at scan time

Activity

  • Commits (30d / 90d)
  • 22
    Forks
  • 0
    Releases

Community

  • Community health
  • authors own >50% of commits
  • 232
    Watchers

Responsiveness

  • 22d 8h
    Median issue response
  • Median PR merge time
  • 0
    Open issues
Repository files13 root entries
  • adzoo
  • assets
  • data
  • docs
  • mmcv
    Good: Test files detected (mmcv/datasets/pipelines/test_time_aug.py).
  • rl_projects
    Good: CONTRIBUTING guide found.
    Issue: CONTRIBUTING guide contents could not be read (−28 pts vs a readable file).Fix: Move the file to the repo root or docs/CONTRIBUTING.md so its setup, style, test, and PR sections can be graded.
    Good: Code of conduct present.
    Good: CI is configured (rl_projects/scenario_runner/Jenkinsfile).
    Good: Linter or formatter configured (rl_projects/scenario_runner/.pylintrc).
    Good: Environment pinned via rl_projects/scenario_runner/Dockerfile.
  • team_code
  • vis_tools
  • clear.py
  • LICENSE
    Good: Licensed under Apache-2.0.
  • README.md
    Good: README is present.
    Good: README is well structured with multiple sections.
    Good: README includes screenshots or visuals. Great for first impressions.
    Good: README has code examples.
    Good: README links to a live demo or deployed app.
    Good: README includes status badges.
    Good: README documents how to install the project.
    Good: README documents how to run the project.
  • requirements.txt
    Good: Lockfile present (requirements.txt). Installs are reproducible.
    Good: Dependency manifest found (requirements.txt).
  • setup.py