Course

Computer Vision Safety & Diagnostics

Build OpenCV object detection pipelines for industrial danger recognition and medical diagnostics.

Level

Advanced

Duration

48 hrs

License

CC-BY

Provider

PowerProgress Vision Clinic

AI tutor ready

Connect plan → quiz → feedback

Launch the learner mission control to pair this syllabus with lesson-aware copilots and checkpoint quizzes.

Manifest compliance

Mirror-ready resources

Modules inherit license notes from our legal archive. Tag your builds with #vision-clinic so takedowns + payouts trace back instantly.

Need removal or attribution edits? See docs/legal-archive-workflow.

Kardashev track

Compute contributions unlocked

Complete this course to accelerate the community compute stewardship pillar.

Readiness status

92%

46,000 hrs/mo pledged

Report civic GPU hours or pledge racks via /projects

View playbook →

Kardashev intelligence

Civic missions bottleneck

3 weekly posts - 50 live missions. Close the 48pt gap by running the recommended playbook.

critical

Readiness

52%

Gap to 100%

-48 pts

  • Target

    120 weekly updates / 30 missions

Synced 10:15:03 PMExecute playbook

Live impact

0

Units pledged · 0 commitments

Add your build thread in /community with #vision-clinic to unlock mentor + affiliate boosts.

Mapped missions

mission-vision-safety

Tag your build logs with these mission IDs for auto credit.

Telemetry tags

visionsafety

Use these hashtags in /community so mentors trace your runbooks.

Module

OpenCV Foundations

Stand up reproducible detection pipelines across CPU/GPU/edge targets.

1 lessons · 2 takeaways

Mission outcomes

  • Package OpenCV builds per target platform.
  • Benchmark detectors with telemetry + compliance logging.

Module

Danger Recognition

Detect hazards, PPE violations, and restricted-area breaches with explainable alerts.

1 lessons · 2 takeaways

Mission outcomes

  • Fuse thermal/depth + RGB cues for safety.
  • Route detections to escalation flows and hardware interlocks.

Module

Medical Diagnostics

Apply computer vision to imaging modalities with clinician-in-loop governance.

1 lessons · 2 takeaways

Mission outcomes

  • Normalize DICOM/PHI and audit model outputs.
  • Design uncertainty overlays + review workflows for doctors.