Model card
The full card lives in docs/model-card.md. Everything below is read from the report produced by the last run of ml/eval.py, so this page cannot show a number that was never measured.
Synthetic demo checkpoint. Trained on procedurally generated imagery of eight invented countries. Every metric below describes that synthetic world; none of it transfers to real-world geolocation.
Identity
- Checkpoint
- demo-convnext_atto-rig-h10
- Model version
- 0.1.0
- Dataset
- synthetic-v1
- Rig
- rig-h10 (10 views)
- Encoder
- convnext_atto
- Aggregator
- attention
Held-out test metrics
56 sequences, geographically separated from training.
- Top-1 accuracy
- 1.0000
- Top-3 accuracy
- 1.0000
- Macro F1
- 1.0000
- Expected calibration error
- 0.5570
- Brier score
- 0.3770
- Temperature
- 1.0000
Calibration: not fitted: validation accuracy is 1.000, which leaves temperature scaling no errors to calibrate against. Temperature held at 1.0.
View-count ablation
The same checkpoint, evaluated with fewer views masked in.
- 1 view(s)
- top-1 0.8393 · 79 ms
- 3 view(s)
- top-1 0.9821 · 73 ms
- 5 view(s)
- top-1 1.0000 · 69 ms
- 10 view(s)
- top-1 1.0000 · 77 ms
Per country
| Country | Precision | Recall | F1 | Support |
|---|---|---|---|---|
| XA | 1.000 | 1.000 | 1.000 | 7 |
| XB | 1.000 | 1.000 | 1.000 | 7 |
| XC | 1.000 | 1.000 | 1.000 | 7 |
| XD | 1.000 | 1.000 | 1.000 | 7 |
| XE | 1.000 | 1.000 | 1.000 | 7 |
| XF | 1.000 | 1.000 | 1.000 | 7 |
| XG | 1.000 | 1.000 | 1.000 | 7 |
| XH | 1.000 | 1.000 | 1.000 | 7 |
Latency
- Median per sequence (CPU)
- 68.2 ms
CPU only. This machine has a CPU-only torch build (2.14.0+cpu), so no GPU figure is reported rather than estimated.
Intended use
Demonstrating and evaluating multi-view visual geolocation. A prediction is probabilistic and describes the appearance of a place.
Out of scope
- Identifying, tracking or inferring anything about a person.
- Establishing someone’s nationality, residence or movements.
- Any decision affecting a person’s rights, safety or access to services.
- Operational or forensic geolocation of real imagery.