Datasets:

shanexf
/

2026-24679-fastener-matching

label int64	label_name string	source_id string	parent_id string	augmentation string	is_augmented bool
0	mismatch	fastener_mismatch_000	fastener_mismatch_000	none	false
0	mismatch	fastener_mismatch_001	fastener_mismatch_001	none	false
0	mismatch	fastener_mismatch_002	fastener_mismatch_002	none	false
0	mismatch	fastener_mismatch_003	fastener_mismatch_003	none	false
0	mismatch	fastener_mismatch_004	fastener_mismatch_004	none	false
0	mismatch	fastener_mismatch_005	fastener_mismatch_005	none	false
0	mismatch	fastener_mismatch_006	fastener_mismatch_006	none	false
0	mismatch	fastener_mismatch_007	fastener_mismatch_007	none	false
0	mismatch	fastener_mismatch_008	fastener_mismatch_008	none	false
0	mismatch	fastener_mismatch_009	fastener_mismatch_009	none	false
0	mismatch	fastener_mismatch_010	fastener_mismatch_010	none	false
0	mismatch	fastener_mismatch_011	fastener_mismatch_011	none	false
0	mismatch	fastener_mismatch_012	fastener_mismatch_012	none	false
0	mismatch	fastener_mismatch_013	fastener_mismatch_013	none	false
0	mismatch	fastener_mismatch_014	fastener_mismatch_014	none	false
0	mismatch	fastener_mismatch_015	fastener_mismatch_015	none	false
0	mismatch	fastener_mismatch_016	fastener_mismatch_016	none	false
0	mismatch	fastener_mismatch_017	fastener_mismatch_017	none	false
0	mismatch	fastener_mismatch_018	fastener_mismatch_018	none	false
0	mismatch	fastener_mismatch_019	fastener_mismatch_019	none	false
0	mismatch	fastener_mismatch_020	fastener_mismatch_020	none	false
0	mismatch	fastener_mismatch_021	fastener_mismatch_021	none	false
0	mismatch	fastener_mismatch_022	fastener_mismatch_022	none	false
0	mismatch	fastener_mismatch_023	fastener_mismatch_023	none	false
0	mismatch	fastener_mismatch_024	fastener_mismatch_024	none	false
0	mismatch	fastener_mismatch_025	fastener_mismatch_025	none	false
1	match	fastener_match_000	fastener_match_000	none	false
1	match	fastener_match_001	fastener_match_001	none	false
1	match	fastener_match_002	fastener_match_002	none	false
1	match	fastener_match_003	fastener_match_003	none	false
1	match	fastener_match_004	fastener_match_004	none	false
1	match	fastener_match_005	fastener_match_005	none	false
1	match	fastener_match_006	fastener_match_006	none	false
1	match	fastener_match_007	fastener_match_007	none	false
1	match	fastener_match_008	fastener_match_008	none	false
1	match	fastener_match_009	fastener_match_009	none	false
1	match	fastener_match_010	fastener_match_010	none	false
1	match	fastener_match_011	fastener_match_011	none	false
1	match	fastener_match_012	fastener_match_012	none	false
1	match	fastener_match_013	fastener_match_013	none	false
1	match	fastener_match_014	fastener_match_014	none	false
1	match	fastener_match_015	fastener_match_015	none	false
1	match	fastener_match_016	fastener_match_016	none	false
1	match	fastener_match_017	fastener_match_017	none	false
1	match	fastener_match_018	fastener_match_018	none	false
1	match	fastener_match_019	fastener_match_019	none	false
1	match	fastener_match_020	fastener_match_020	none	false
1	match	fastener_match_021	fastener_match_021	none	false
1	match	fastener_match_022	fastener_match_022	none	false
1	match	fastener_match_023	fastener_match_023	none	false
1	match	fastener_match_024	fastener_match_024	none	false
1	match	fastener_match_025	fastener_match_025	none	false
1	match	fastener_match_026	fastener_match_026	none	false
1	match	fastener_match_027	fastener_match_027	none	false
1	match	fastener_match_028	fastener_match_028	none	false

24-679 (Fall 2026): Fastener Matching — Bolt-and-Nut Compatibility

shanexf/2026-24679-fastener-matching

Photographs of bolt-and-nut pairs for a binary image classifier that predicts whether the two fasteners are compatible. Every photo shows exactly one bolt and one nut side by side. Matching and mismatching pairs were photographed under different orientations, positions, lighting conditions, and viewing angles.

Source and task

All photographs were taken by the dataset author for the 24-679 image-data assignment. The label is encoded by the Google Drive folder each photo was sorted into. The two classes are not equally represented; see the split table for the actual counts. 1 = match (the nut threads onto the bolt); 0 = mismatch (it does not). Compatibility was determined physically by trying the nut on the bolt before photographing the pair.

Course: 24-679, Fall 2026, Carnegie Mellon University.

Fields

Field	Meaning and modeling role
`image`	224 × 224 RGB pixels; the model's image input.
`label`	Classification target: 1 = match; 0 = mismatch.
`label_name`	Readable target description; exclude from model inputs.
`source_id`, `parent_id`	Unique row key and its original source key; provenance only.
`augmentation`, `is_augmented`	Method identifier and synthetic flag; provenance only.

Splits

Split	Rows	Mismatch (0)	Match (1)
original	55	26	29
augmented	550	260	290

The original split holds the prepared photographs. The augmented split holds only synthetic rows, each generated from one original by exactly one transformation. Because every synthetic row shares an image with an original, evaluation should split by parent_id so that no parent appears on both sides of a train/test boundary.

Preprocessing and augmentation

Every original was oriented using EXIF metadata, converted to RGB, resized while preserving aspect ratio, and padded with gray (128, 128, 128) to 224 × 224. Camera metadata and original filenames are not stored.

Each original contributed exactly 10 synthetic variants, so the augmented split is 10x the original split and keeps its class proportion. Variants cycle through eight label-preserving methods: horizontal/vertical flip; rotation of 10–45° in either direction; translation of up to 12% of the frame; brightness factors 0.5–0.8 or 1.25–1.7; contrast factors 0.5–0.75 or 1.3–1.9; color saturation factors 0.3–0.7 or 1.3–1.8; Gaussian blur with radius 0.8–2.0 px; and additive Gaussian noise with σ = 6–18 on the 0–255 scale. Transforms are not stacked. Random choices use seed 24679.

Augmentation method	Stored rows
`brightness`	55
`color_saturation`	55
`contrast`	55
`flip`	110
`gaussian_blur`	55
`gaussian_noise`	55
`rotation`	110
`translation`	55

Intended use and limitations

Use for teaching image preparation, augmentation, and small-data classification. The collection is small, comes from a single photographer and a limited set of fasteners, and can contain shortcuts such as background, lighting, or the specific bolts and nuts that recur across photos. Thread pitch is a fine detail that may not be resolvable at 224 × 224, so a classifier may rely on diameter and overall appearance instead. Synthetic variants do not add independent photographs. The classes are imbalanced, so report per-class accuracy or balanced accuracy rather than plain accuracy, and use a held-out set of fasteners that never appear in training before claiming generalization.

AI use acknowledgment

The preparation notebook's code, markdown, and this card were drafted with Claude (Anthropic) as a coding assistant and then reviewed, edited, and run by the dataset author. The photographs, the physical compatibility test behind each label, and the folder sorting were done by the author.

Privacy and licensing

The photographs contain only fasteners and a background surface; no people, faces, or identifying text. Original filenames and camera metadata were removed. No license is assigned by this card.

Load

from datasets import load_dataset
ds = load_dataset("shanexf/2026-24679-fastener-matching")
originals, synthetic = ds["original"], ds["augmented"]

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