Every number here came from one real run.
This page uses a single 40-frame capture of Map_Airbase_Demo, taken on Unreal Engine 5.8 and processed by the same pipeline a customer would use. The distributions are recomputed from its buffers and manifests; the checks are quoted from its report. Nothing was selected to look good.
- Frames
- 40
- Instances
- 4,378
- Dataset grade
- A · 92.4/100
- Raw health
- B · 82/100
- Seed
- 67
More data is not the same as better data.
Ten thousand frames of the same view from the same distance is one frame, repeated. These are the real distributions of the 40-frame airbase capture this page has been showing, computed from its own buffers and manifests.
- Measured
- 4,402
- Min
- 33.19m
- Median
- 78.87m
- 90th
- 108.06m
- Max
- 187.81m
Every annotated instance, measured from the camera position to the actor's own recorded position. The run's cameras sit in four authored zones, which is why the mass falls between 40 and 120 metres rather than spreading evenly.
Target, actual, gap
Only constraints this run actually declared appear here. A target nobody configured would be a number invented for a table.
| Constraint | Target | Actual | Gap |
|---|---|---|---|
| Minimum spacing between placements | ≥ 1.00 m | 1.00 m | met |
| Viewpoint retries per frame | ≤ 32 | 9 | met |
| Targets visible per accepted frame | ≥ 18 | 73 | met |
| Frames with no annotation | 0 | 0 | met |
Every check, pass or fail.
Quality gates decide whether a capture is allowed to become a dataset. Verification checks go further and ask whether the labels agree with the geometry that produced them. Both run on every capture, and both are recorded whether or not the answer is flattering.
| Check | Kind | Result | Recorded message |
|---|---|---|---|
| empty-frame-rate | Quality gate | PASS | |
| empty-seg-rate | Quality gate | PASS | |
| total-instances | Quality gate | PASS | |
| mean-instances-per-frame | Quality gate | PASS | |
| black-rgb | Quality gate | PASS | |
| missing-files | Quality gate | PASS | |
| small-object-rate | Quality gate | PASS | |
| determinism | Verification | PASS | |
| configuration-snapshot-integrity | Verification | PASS | |
| spawn-manifest-integrity | Verification | PASS | |
| color-collisions | Verification | PASS | |
| pixels-vs-transforms | Verification | PASS | |
| missing-visible-people | Verification | FAIL |
The failing check found three visible people with no bounding box, out of ninety in the sample it inspected. They lost their pixels to a neighbouring instance in the ID buffer. A dataset that hid this would still contain the error; the only difference would be that you found it later.
Unreal goes in. A dataset comes out.
The engine writes a raw dump and nothing else. Everything a trainer consumes is derived from that dump afterwards, which is why the same run can be re-exported into a different format without going back to the editor.
Map_Airbase_Demo · 40 frames · 1920×1080
- raw/rgb.png, seg.png, depth.npy per frame
- labels/boxes and masks derived from the ID buffer
- metadata/frame.json, spawn_manifest.json, capture.json
- reports/report.json, validation.json, previews
- dataset.yamlclass names and split paths
| Split | Images | Labels | Masks |
|---|---|---|---|
| train | 31 | 31 | 31 |
| val | 9 | 9 | 9 |
| test | 0 | 0 | 0 |
Only the formats this build genuinely writes are listed. The test split is empty on this run because it was exported with a train and validation split only, and an empty split is shown as empty rather than quietly dropped.
Or skip the argument and read the files.
The frames, masks, labels, metadata and the reports quoted on this page are downloadable. Open them, run your own checks, and decide for yourself.
Download the sample datasets →