legacy: 370 usable frames from Painfully-Trivial v1.0.0

README.md

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+---
+license: other
+task_categories:
+  - object-detection
+  - image-classification
+tags:
+  - waste
+  - recycling
+  - smart-bin-recognition
+---
+
+# arudaev/smart-bin-detect
+
+Training data for **Smart Bin Recognition** – a validator ("is there a bin?")
+and an identifier ("which bin?"). See
+[`docs/04-ml-pipeline.md`](https://github.com/arudaev/Painfully-Trivial) for the
+design, and the manifests in this repo for per-image provenance.
+
+**Every image carries provenance**: source, source URL, licence, region,
+capture date, annotator where known, label origin (`human` / `machine` /
+`legacy` / `open-images`) and adjudication status. Licences differ per subset and
+are recorded per image; there is no single licence for the whole repo, which is
+why the header says `other`.
+
+## Subsets
+
+### `legacy`
+
+| | |
+|---|---|
+| frames | 370 |
+| boxes | 403 |
+| crops | 403 |
+| crops pending adjudication | 403 |
+| bins per frame | {1: 341, 2: 25, 3: 4} |
+| licence | MIT |
+| region | de-by-deggendorf |
+| label origin | legacy |
+
+
+## How to read this
+
+Each subset directory is a self-contained pool:
+
+```
+<subset>/
+├── manifest.json   provenance for every frame, and every crop
+├── images/         full frames
+├── labels/         YOLO labels; an EMPTY file means a deliberate background image
+└── crops/          identifier candidates (present only where relevant)
+```
+
+`sbr.dataset.prepare.build_yolo_tree` assembles them into a training tree,
+grouping frames by capture cluster so that two photographs of the same bin can
+never straddle a split.
+
+## What this data is not
+
+The legacy subset is **one city in one week**, 370 usable frames, and not one
+frame of it holds four or more bins. Numbers measured on it are
+in-distribution numbers. See `docs/09-phase2-results.md` for what was measured,
+on which split, and on what hardware.