Datasets:

OliseNS
/

person-face-package-home-security-detection

license: other
license_name: multi-source-aggregated-terms
license_link: LICENSE
pretty_name: Person, Face & Package — Home Security Detection (YOLO)
task_categories:
  - object-detection
tags:
  - image
  - object-detection
  - computer-vision
  - yolo
  - ultralytics
  - bbox
  - home-security
  - surveillance
  - face-detection
  - parcel-detection
  - delivery
  - vehicle-detection
  - pet-detection
  - bird-detection
annotations_creators:
  - crowdsourced
  - found
language:
  - en

Person, face & package — home-security detection dataset

YOLO-format dataset for person, face, vehicles, small vehicles, parcels, pets, and birds in home / delivery / street scenes. Full data lives under bigsplit/; sample/ is a 100-image preview subset (same layout: flat images/ and labels/).

Training configs point at a data.yaml beside those folders. Both splits use the same class list (nc and names); only the root path and which image set is packaged differ. Labels are YOLO .txt files with one line per box: class_id x_center y_center width height (normalized 0–1).

`data.yaml` — tags and layout

Class tags are the names list; order is the YOLO class index (0 … nc - 1). Below is the canonical schema used by sample/data.yaml (checked in). The full split uses the same nc and names in bigsplit/data.yaml; path, train, and val resolve to that folder’s images/ when you train from the dataset root.

sample/data.yaml

# Preview sample (100 images); same layout as bigsplit — no split subfolders.
path: .
train: images
val: images
nc: 9
names:
  - person
  - face
  - vehicle
  - bike
  - bicycle
  - parcel
  - dog
  - cat
  - bird

When the full dataset is present, bigsplit/data.yaml uses the same path / train / val / nc / names (often with a file header comment describing the full split instead of the sample).

Preview (bounding boxes)

Five PNGs are generated from the checked-in sample/ images and YOLO labels. Each file stitches three frames edge-to-edge at equal height (no padding between panels). Boxes and class names are drawn from the corresponding sample/labels/*.txt files.

Sample preview 1 — three stitched frames Sample preview 2 — three stitched frames Sample preview 3 — three stitched frames

Sample preview 4 — three stitched frames Sample preview 5 — three stitched frames

preview_01.png · preview_02.png · preview_03.png · preview_04.png · preview_05.png · preview_manifest.txt (source filenames per composite)

Regenerate after changing sample/:

python3 -m venv .venv   # once
.venv/bin/pip install pillow pyyaml
.venv/bin/python scripts/make_readme_preview.py

Layout

bigsplit/data.yaml — class list and paths (train / val both point at images/).
sample/data.yaml — same schema for the preview subset.

Classes (`nc: 9`)

id	name
0	person
1	face
2	vehicle
3	bike
4	bicycle
5	parcel
6	dog
7	cat
8	bird

License

See LICENSE.