PitchTrack: the coach report, and the video behind it

Plateau United (NPFL) get a coach report after their home games, from a fixed three-lens rig on the stand with no camera operator. This page is the step after the report: OpenCV 5 on AWS EC2 turns a moment the report points at into a watchable follow shot. Plateau United 4-0 Kano Pillars, New Jos Stadium, 11 Oct 2026.

OpenCV …AWS EC2 · eu-north-13 × 3840×2160 lensesno motors, no camera operator

What the coach report said about this match

The full report as the club received it: kamhq.com/plateau/2026-10-11-kano-pillars. It measures the team from player positions, with no player identity.

Watch it: three minutes, rendered on this server

Session clock 2640–2820 s: the build-up, the corner (watch the cut to the taker at the near flag at about 2780 s), Plateau's second goal (Ekundayo Ojo, 45+3') at about 2790 s, and the celebration at the bench. The camera chooses its own lens, aim and zoom. No one steered it.

Render a window yourself

This runs the same OpenCV 5 pipeline on the EC2 instance, live: three 4K decoders, the pitch homography, roll levelling, crop and warp, and an H.264 encode. One render runs at a time. A 20-second window takes about a minute on 2 vCPUs.

Idle.

How it works

Rig on the stand3 × 4K USB lenses, Pi 5~17 fps each, .mkv + manifest Detection + trackingYOLO + ByteTrack, laptop GPU→ tracking_log.csv (metres) AWS EC2 m7i-flex.large · eu-north-1 OpenCV 5 virtual cameraVideoCapture × 3 (FFmpeg)homography → action pointdensity peak, gatedroll from vanishing ptresize(INTER_AREA)warpAffine → 1920×1080ffmpeg libx264 server.py job queue/api/render · /api/jobs nginx :80page + /media (mp4)

What it does not do

Kam Labs, Jos, Nigeria · OpenCV AI Competition 2026 entry · Technical report · /api/health