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image
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95
4.03k
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stringclasses
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detection
blurred
detection/blurred/image001.jpg
1
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null
detection
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detection
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null
detection
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detection
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null
detection
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detection/blurred/image006.jpg
1
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detection
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detection
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detection
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detection
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detection
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detection
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detection
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detection
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null
detection
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detection
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detection
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detection
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detection
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detection
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detection
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detection
blurred
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detection
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detection
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detection
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2
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detection
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detection
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detection
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detection
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detection
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detection
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detection
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detection
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detection
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detection
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detection
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null
detection
blurred
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null
detection
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detection
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null
detection
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detection
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null
detection
bright_spots
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3
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null
detection
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detection
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null
detection
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detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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null
detection
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detection
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detection
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null
detection
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null
End of preview. Expand in Data Studio

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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