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Visual crack detection

Dataset acquired from https://digitalcommons.usu.edu/all_datasets/48/

Images

About this project

Visual Anomaly Detection (FOMO-AD)

Dataset: https://digitalcommons.usu.edu/all_datasets/48/

Maguire, M., Dorafshan, S., & Thomas, R. J. (2018). SDNET2018: A concrete crack image dataset for machine learning applications. Utah State University. https://doi.org/10.15142/T3TD19

Data (1,308 items)

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nominal.7113-25.jpg.3cpc89uh.ingestion-6c4b8994d8-dx5m8.jpg.42kn9hm5.d80bf3d42cc2

ID: 506297777

Label: nominal

nominal.7103-178.jpg.3cpc86qr.ingestion-6c4b8994d8-d9rzn.jpg.42kn9fif.d80bf3d42cc2

ID: 506296859

Label: nominal

nominal.7076-210.jpg.3cpc7tf1.ingestion-6c4b8994d8-d9rzn.jpg.42kn99q7.d80bf3d42cc2

ID: 506293958

Label: nominal

nominal.7127-127.jpg.3cpc8e40.ingestion-6c4b8994d8-dx5m8.jpg.42kn9kj8.d80bf3d42cc2

ID: 506299906

Label: nominal

nominal.7091-158.jpg.3cpc8334.ingestion-6c4b8994d8-d9rzn.jpg.42kn9cni.d80bf3d42cc2

ID: 506295399

Label: nominal

no anomaly.uncracked.7115-77.jpg.3cpca9gc.ingestion-6c4b8994d8-dx5m8.jpg.47594tld.e1401aeba576

ID: 506308730

Label: nominal

nominal.7112-83.jpg.3cpc89mo.ingestion-6c4b8994d8-pvc99.jpg.42kn9hfi.d80bf3d42cc2

ID: 506297696

Label: nominal

nominal.7117-143.jpg.3cpc8b0v.ingestion-6c4b8994d8-dx5m8.jpg.42kn9idt.d80bf3d42cc2

ID: 506298353

Label: nominal

Model accuracy (Unoptimized (float32))

Validation set

Test set

95.9%

On-device performance (Cortex-M7 216MHz, Quantized (int8))

Latency

105 ms.

Peak RAM usage

625.6K

Flash usage

69.5K

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Dataset summary

Data collected

1,308 items

Labels

nominal

Project info

Project ID	288658
License	BSD 3-Clause Clear
No. of views	201,791
No. of clones	64