This article currently summarizes 28 common open source industrial defect data sets, which are being continuously updated
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Northeastern University Hot Rolled Strip Surface Defect Dataset
Official link: Vision-based SIS for steel
This data set was collected by several teachers including Song Kechen from Northeastern University. It contains three types of data. Sometimes the official website cannot be opened. I saved all three defect data sets in Baidu Netdisk.
Baidu network disk link:
Link: https://pan.baidu.com/s/1bAKoSG7VHE98JdHJPGJvcw
Extraction code: ibje
(1)NEU surface defect database
The data set collects 6 kinds of defects including inclusions, scratches, pressed scale, cracks, pits and plaques, with 300 images for each defect, and the image size is 200×200. The data set includes classification and target detection. However, there are a small number of errors in the labeling of target detection, which need attention. Some examples are as follows:

(2)Micro surface defect database
Miniature steel strip defect data, the defect is only about 6×6 pixels in size

(3)Oil pollution defect database
Dataset of Silicon Steel Surface Defects Interferenced by Oil Contamination

Strip defect data set provided by Severstal Steel Company in Kaggle
Four types of strip surface defects are provided in this dataset. There are 12568 training sets and 5506 testing sets. The image size is 1600×256.

Severstal Strip Defect Dataset
If there is a need for academic research, it can be used without restrictions, please designate PAO Severstal ( https://www.severstal.com/) as the dataset owner.
Official link: https://www.kaggle.com/c/severstal-steel-defect-detection/data
I originally wanted to upload it to Baidu Netdisk for everyone to download, but more than 500 files require super membership. . . Tens of thousands of pictures are too many to upload manually.
UCI Steel Plates Faults Data Set
The dataset contains 7 strip defect types. This data set is not image data, but 28 kinds of characteristic data of steel strip defects, which can be used in machine learning projects.

Official link: https://archive.ics.uci.edu/ml/datasets/Steel+Plates+Faults
Baidu network disk link:
Link: https://pan.baidu.com/s/1VhEW8xodv5XhTnBKoz5Z_w
Extraction code: 9uv2
DAGM 2007 dataset
The dataset is artificially generated and contains a total of 10 classes with an image size of 512×512. The data set is a partial example as follows:

Official link: https://hci.iwr.uni-heidelberg.de/content/weakly-supervised-learning-industrial-optical-inspection
Baidu network disk link:
Link: https://pan.baidu.com/s/1EyK3flXj2S9Uyooi10HsCA
Extraction code: j9qz
Magnetic Tile Defect Dataset
The data set collected by a research group of the Institute of Automation, Chinese Academy of Sciences is the data set of the paper "Saliency of magnetic tile surface defects". The images of 6 common magnetic tile defects were collected and marked with semantic segmentation.

Official link: https://github.com/abin24/Magnetic-tile-defect-datasets
Baidu network disk link:
Link: https://pan.baidu.com/s/1iuSHXoVJT-eInFh9xNzEyw
Extraction code: ky8i
Kolektor Surface Defects Dataset
This dataset is an electronic commutator defect dataset collected and labeled by Kolektor Group. The data set contains 50 written electronic commutators, each with 8 pictures and its semantically segmented label. The size of the image is 500×1240 pixels. For more convenient training, the image needs to be adjusted to 512×1408 in advance.

Official link: https://www.vicos.si/Downloads/KolektorSDD
Baidu network disk link:
Link: https://pan.baidu.com/s/1HSzHC1ltHvt1hSJh_IY4Jg
Extract code: 1zlb
Rail Surface Defects Dataset
The RSDDs dataset contains two types of datasets: the first is the Type I RSDDs dataset captured from the fast lane, which contains 67 challenging images. The second is a dataset of Type II RSDDs captured from ordinary/heavy transport tracks, which contains 128 challenging images.
Each image of the two datasets contains at least one defect, and the background is complex and noisy.
These defects in the RSDDs dataset have been flagged by some professional human observers in the field of orbital surface inspection.

Official link: http://icn.bjtu.edu.cn/Visint/resources/RSDDs.aspx
Baidu network disk link:
Link: https://pan.baidu.com/s/1svsnqL0r1kasVDNjppkEwg
Extraction code: nanr
Cement Road Cracks Dataset
It is mainly aimed at the crack detection of cement pavement, which can be used for classification, segmentation and detection

Official link: cuilimeng/CrackForest
Baidu network disk link:
Link: https://pan.baidu.com/s/19qEBt0JDLs1v6jS5y8HJhQ
Extraction code: 7nzx
Bridge Crack Image Data
Detection data of bridge cracks:

Baidu network disk link:
Link: https://pan.baidu.com/s/1z-y3GhsWmbqzezD-eZSL-A
Extraction code: z493
Concrete Surface Crack Defect Dataset
The dataset contains images of various concrete surfaces with and without cracks. The image data is divided into negative (no cracks) and positive (no cracks) parts in separate folders for image classification. There are 20,000 images per category, for a total of 40,000 images with RGB channels of 227 x 227 pixels.

Official link: https://www.kaggle.com/arunrk7/surface-crack-detection
Tianchi Aluminum Profile Surface Defect Dataset
The data set provided in the 2018 Ali Tianchi Competition, Guangdong Industrial Intelligent Manufacturing Big Data Innovation Competition-Intelligent Algorithm Competition.

Baidu network disk link:
Link: https://pan.baidu.com/s/1jnSwJ2xRzdSplUtvTbuIuw
Extraction code: i10s
Tianchi Textile Surface Anomaly Dataset
In the actual production process of cloth, due to the influence of various factors, there will be stains, holes, hair particles and other defects. In order to ensure product quality, it is necessary to carry out defect detection on cloth. Cloth defect inspection is an important link in the production and quality management of the textile industry. At present, manual inspection is easily affected by subjective factors and lacks consistency; and the long-term work of inspectors under strong light has a great impact on vision. Due to the wide variety of cloth defects, various morphological changes, and the difficulty of observation and identification, intelligent detection of cloth defects has been a technical bottleneck that has plagued the industry for many years. This data covers various important defects of cloth in the textile industry, and each picture contains one or more defects. The data includes two types of plain cloth and patterned cloth. Among them, about 8,000 pieces of plain color cloth are used for the preliminary round; about 12,000 pieces of patterned cloth are used for the semi-finals.
Baidu network disk link:
Link: https://pan.baidu.com/s/1eRCCpQhkH05gBTaDkdSAAw
Extraction code: 2j46
AITEX Fabric Defect Dataset
This dataset contains 245 images of 4096x256 pixels with 7 different fabric structures. There are 140 defect-free images in the dataset, 20 of each type of fabric. In addition, there are 105 pictures of 12 different types of fabric defects commonly seen in the textile industry.
AITEX FABRIC IMAGE DATABASE - Aitexwww.aitex.es/afid/

Workpiece wear dataset: BSData
The dataset contains 1104 3-channel images and 394 image annotations, and the surface damage type is "pitting".

KTH-TIPS database
The background texture dataset provided by the Royal Institute of Technology in Sweden includes 10 categories including sandpaper, aluminum foil, styrofoam, sponge, corduroy, linen, cotton, black bread, orange peel and biscuits.

Baidu network disk link:
Link: https://pan.baidu.com/s/10essXdRrZtlx4CcSirq6Kw
Extraction code: am65
Printed Circuit Board (PCB) Defect Dataset
This is a public synthetic PCB dataset released by Peking University, which contains 1386 images with 6 types of defects (missing holes, mouse bites, opens, shorts, strays, pseudo-copper) for detection, classification and configuration. quasi-task.

Official link: Peking University Intelligent Robot Open Laboratory
Baidu network disk link: https://pan.baidu.com/s/1hoPNd7_SAxOWa2XbBZZuTg
Printed Circuit Board (PCB) Defect Dataset
DeepPCB: A data set contains 1500 pairs of images, each pair of images consists of a defect-free template image and an aligned test image, which annotated the 6 most common PCB defects: open, short, mousebite, spur, pin hole and spurious copper.

AITEX dataset
The database consists of 245 4096 x 256 pixel images of seven different fabric structures. There are 140 non-defect images in the database, 20 for each type of fabric, besides this, there are 105 images of different types of fabric defects (12 types of defects) that are common in the textile industry. The large size of the image allows the user to use different window sizes, thus increasing the number of samples. Databases on the Internet also contain segmentation masks of all images with defects such that white pixels represent defect regions and the remaining pixels are black.

Official link: https://www.aitex.es/afid/
Baidu network disk link:
Link: https://pan.baidu.com/s/1u-trbeeN_-5GceDVQekyhA
Extraction code: z9yc
Kylberg Texture Dataset v. 1.0
28 texture images, each with 160 unique textures. The image size is 576x576 pixels.

Official link: http://www.cb.uu.se/~gustaf/texture/
Transmission Line Insulator Dataset
In the dataset, Normal_Insulators contains 600 images of insulators captured by drones.
Defective_Insulators contains defective insulators, and the number of insulator defect images is 248.
Datasets include datasets and labels.

Official link: InsulatorData/InsulatorDataS dataset in Baidu AI Studio
There are many data sets in Baidu AI Studio, you can search directly
Baidu AI Studio - AI learning and training community aistudio.baidu.com/aistudio/index

For example:
Cloth Defect Dataset: Cloth Defect Dataset:
Tile Defects Dataset: Tile Defects Dataset
Insulator self-explosion defect image: Insulator self-explosion defect image
Industrial Defect Inspection: Industrial Defect Inspection
PCB Defect Inspection: PCB Defect Inspection
Escalator Step Defects: Escalator Step Defects
CV Datasets on the web
Aggregates common datasets in the CV domain, less related to industrial defects.
Official link: http://www.cvpapers.com/datasets.html
Solar Panel Defects Dataset
Solar panel dataset, which contains 2624 300x300 solar panel defect images.

Welcome everyone to leave a message to add, and jointly build an article that provides convenience for everyone.
For the data set of image classification and detection field scenes, please refer to my other article: