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BoofCV QR Images V2
A mirror of Peter Abeles' QR Code Performance Benchmark image set from BoofCV, repackaged as a HuggingFace dataset with the corner annotations parsed into structured fields.
487 images: 461 detection images across 14 difficulty categories with 1,153 hand-annotated QR corner quads, plus 26 decoding images with expected payload strings.
Categories
| category | images | category | images | |
|---|---|---|---|---|
| nominal | 65 | rotations | 44 | |
| glare | 50 | blurred | 42 | |
| curved | 49 | damaged | 34 | |
| close | 40 | bright_spots | 32 | |
| brightness | 28 | pathological | 23 | |
| monitor | 17 | noncompliant | 16 | |
| shadows | 14 | lots | 7 |
Fields
| field | notes |
|---|---|
image |
the picture |
subset |
detection (461) or decoding (26) |
category |
one of the 14 above, or decoding |
corners |
list of 4-point polygons, one per QR — every detection image has these |
n_qr_codes |
QR instances in the image (1,153 total across the detection set) |
expected_message |
the decoded string, for all 26 decoding images |
source_path |
original path inside the BoofCV archive |
One parsing note that matters
The upstream .txt files use two different formats: some have a SETS
header with one line per QR (8 floats = 4 corners), and some have no header and
one line per point, four consecutive lines to a QR. Reading only the first
format yields corners for 175 of 461 images and silently looks like "the rest
are unannotated". Both formats are parsed here, and the point-style files were
checked to contain a whole number of quads.
Usage
from datasets import load_dataset
ds = load_dataset("devmandan/boofcv-qr-images-v2", split="test")
hard = ds.filter(lambda r: r["category"] in {"damaged", "curved", "glare"})
multi = ds.filter(lambda r: r["n_qr_codes"] > 1)
Provenance and licensing — read before redistributing
Original source: https://boofcv.org/notwiki/regression/fiducial/qrcodes_v2.zip Author: Peter Abeles (BoofCV).
BoofCV does not state an explicit licence for this image set. The project publishes it openly as a benchmark and describes its images and evaluation code as freely available, which is why it is mirrored here — but "freely available" is not a licence grant, and no licence is or can be granted by this mirror. If you need defined redistribution terms, get them from the BoofCV project.
The parsed annotations and repackaging in this repository are offered under CC BY 4.0. The images are Peter Abeles' work, not the mirror publisher's.
If you are the rights holder and want this mirror removed, open a discussion here and it will be taken down.
Citation
@misc{boofcv_qr_v2,
title = {BoofCV QR Code Performance Benchmark, Images V2},
author = {Abeles, Peter},
howpublished = {\url{https://boofcv.org/}},
note = {QR detection and decoding benchmark image set}
}
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