Automated detection of expressway pavement cracks is critically important for infrastructure inspection and maintenance.
Rows683
Configurations1
Size149.4 MB
License—
AccessPublicly accessible
Monthly Downloads—
Dataset Card
Automated detection of expressway pavement cracks is critically important for infrastructure inspection and maintenance. In this task, range information provides a key geometric cue for distinguishing genuine cracks from pavement textures, shadows, stains, and other visual interference. However, industrial-grade pavement data acquisition equipment is expensive, and pixel-wise annotation is labor intensive. Consequently, most existing pavement crack datasets contain only visual imagery and cannot precisely represent the geometric morphology of the pavement surface. GTCrack was developed to alleviate this data bottleneck. A survey vehicle equipped with two laser line profilers was used to…
Excerpt from the card by Guoxi Liu.
Structure
default 683 rows
| Split | Rows | Size |
|---|---|---|
| train | 478 | 173.2 KB |
| validation | 102 | 38.5 KB |
| test | 103 | 37.0 KB |
imageImagerange_imageImagelabelImageidstringwidthint64heightint64
Details
- Repository
- hf-gx/GTCrack
- Publisher
- Guoxi Liu
- Task category
- Image segmentation
- Tags
- pavement-crack-detection, semantic-segmentation, multimodal
- Size category
- Not stated by the source
- Languages
- en
- Revision
- c28e72ccbee6e4b21e34f8c2ddce3fb5b95b5eb2
- Last updated
- 2026-09-18
Files
2,055 files, 149.4 MB in total.
Data4 files · 139.0 KB
Documentation1 file · 3.7 KB
Other2049 files · 149.2 MB
Repository1 file · 2.5 KB
Every file
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|---|---|---|---|
| dataset_summary.json | Data | 370 B | — |
| test/metadata.jsonl | Data | 20.9 KB | — |
| train/metadata.jsonl | Data | 97.0 KB | — |
| validation/metadata.jsonl | Data | 20.7 KB | — |
| README.md | Documentation | 3.7 KB | — |
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| .gitattributes | Repository | 2.5 KB | — |
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Download from Guoxi Liu
Released by Guoxi Liu through its official repository on Hugging Face.