Day 83: Collecting validation data (session 1)
Running the protocol — the real world pushes back
Execute session 1: photograph people, run the pipeline, take tape measurements, log everything. Reality will surprise you — a pose the model handles worse than expected, a garment that confuses parsing, a height input that throws off calibration. This is the point. The gap between how you *assumed* the pipeline behaves and how it *actually* behaves on real bodies is the entire value of this exercise.
Collect the first validation batch
Run at least two or three people through the full protocol. For each: capture photos under the planned conditions, record the engine's per-dimension cm and confidence, and take careful tape measurements as ground truth. Don't fix anything yet — just collect honestly, including the embarrassing results. The failures are data, not something to hide.
Resist the urge to tune to the test
When a measurement is off, the temptation is to tweak the pipeline until *this* person measures well. Don't — that's Day 45's validation-overfitting trap in a new form. Collect all sessions first, analyze the patterns (Day 85), then improve based on systematic error, not one person's result. Verification over plausibility means the test stays honest.
Key terms
- Field validation
- Testing a system on real subjects under realistic conditions, surfacing gaps between assumed and actual behavior.
- Paired measurement
- A recorded (predicted, ground-truth) pair enabling per-dimension error analysis.
During validation, a measurement is clearly off for one person. Why not immediately tweak the pipeline to fix that case?
