Datasets:

arudaev
/

smart-bin-detect

license: other
task_categories:
  - object-detection
  - image-classification
tags:
  - waste
  - recycling
  - smart-bin-recognition
configs:
  - config_name: legacy
    drop_labels: true
    data_files:
      - split: train
        path: legacy/images/*.jpg
  - config_name: open_images
    drop_labels: true
    data_files:
      - split: train
        path: open_images/images/*/*.jpg
  - config_name: negatives
    drop_labels: true
    data_files:
      - split: train
        path: negatives/images/*/*.jpg

arudaev/smart-bin-detect

Training data for Smart Bin Recognition – a validator ("is there a bin?") and an identifier ("which bin?"). The design lives in docs/04-ml-pipeline.md in the project repo, which is private; the manifests here carry per-image provenance and are the authoritative record of what this dataset contains.

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

`open_images`


frames	1110
boxes	1936
crops	0
crops pending adjudication	0
bins per frame	{1: 708, 2: 206, 3: 98, 4: 40, 5: 28, 6: 13, 7: 8, 8: 5, 9: 2, 12: 1, 18: 1}
licence	https://creativecommons.org/licenses/by/2.0/
region	unknown
label origin	open-images

`negatives`


frames	17474
boxes	0
crops	0
crops pending adjudication	0
bins per frame	{0: 17474}
licence	https://creativecommons.org/licenses/by/2.0/
region	unknown
label origin	open-images

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)

Large subsets interpose a shard level – images/ab/<id>.jpg, the two hex characters being sha256(stem) – because the Hub rejects a push where any directory holds more than 10 000 files, and the negative corpus alone is ~17 500. manifest.json says which: "layout": "sharded", and a manifest without the key is flat. legacy/ is flat and stays that way.

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 — every multi-bin frame here comes from Open Images. Numbers measured on legacy alone are in-distribution numbers.

There is no geographic holdout. Every Open Images frame carries region_id: "unknown", because the source does not record where a photograph was taken, so no split in this dataset answers "does it work in another city". See docs/11-phase2-results.md in the project repo for what was measured, on which split, and on what hardware.