datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
code_x_glue_cc_defect_detection
Dataset Card for "code_x_glue_cc_defect_detection"
Dataset Summary
CodeXGLUE Defect-detection dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/Defect-detection
Given a source code, the task is to identify whether it is an insecure code that may attack software systems, such as resource leaks, use-after-free vulnerabilities and DoS attack. We treat the task as binary classification (0/1), where 1 stands for insecure code and 0 for secure… See the full description on the dataset page: https://huggingface.co/datasets/google/code_x_glue_cc_defect_detection.welding-defect-object-detection
Welding Defect Object Detection
2,028 annotated images of welds for defect detection, in both YOLO and COCO
formats. Three classes:
id (YOLO / COCO)
name
0 / 1
Bad Weld
1 / 2
Good Weld
2 / 3
Defect
Splits
split
images
annotations
train
1,619
4,583
valid
283
802
test
126
301
Layout
├── data.yaml # YOLO class names + split paths
├── train|valid|test/
│ ├── images/ # .jpg
│ └── labels/… See the full description on the dataset page: https://huggingface.co/datasets/rikkarth/welding-defect-object-detection.nut_defect_detection
Nut Defect Classification
Synthetic Industrial Quality Inspection Dataset
Nut Defect Classification (Synthetic Dataset)
This dataset is a synthetic collection of industrial nut images designed for image classification tasks, specifically focusing on defect detection in manufacturing pipelines. It serves as a benchmark and training resource for computer vision algorithms used in quality assurance.… See the full description on the dataset page: https://huggingface.co/datasets/Kinzaaa/nut_defect_detection.blade-defect-detection
Blade Defect Detection Dataset (notch / crack / ablation)
A YOLO-format object detection dataset for blade surface defect detection, covering
three defect types: notch, crack, and ablation.
Dataset Structure
├── anomaly.yaml # Ultralytics YOLO dataset config (relative paths)
├── train/ # images + labels
├── val/ # images + labels
└── test/ # images + labels
anomaly.yaml uses relative paths — training can be launched directly from… See the full description on the dataset page: https://huggingface.co/datasets/hahahang2/blade-defect-detection.synthetic-mvtec-ad-defect-detection
Synthetic MVTec AD – Defect Detection Dataset by AnywayLabs.ai
Need a custom synthetic dataset for your own defect detection use case?
This dataset is an open-source sample of our synthetic data generation work at AnywayLabs.
If you're working on:
industrial defect detection
visual inspection
supervised anomaly detection
hard-to-collect defect classes
synthetic data for computer vision training
You can request a custom synthetic dataset here, or email:… See the full description on the dataset page: https://huggingface.co/datasets/anywaylabs/synthetic-mvtec-ad-defect-detection.welding-defect-object-detection
Welding Defect Object Detection
2,028 annotated images of welds for defect detection, in both YOLO and COCO
formats. Three classes:
id (YOLO / COCO)
name
0 / 1
Bad Weld
1 / 2
Good Weld
2 / 3
Defect
Splits
split
images
annotations
train
1,619
4,583
valid
283
802
test
126
301
Layout
├── data.yaml # YOLO class names + split paths
├── train|valid|test/
│ ├── images/ # .jpg
│ └── labels/… See the full description on the dataset page: https://huggingface.co/datasets/l985215117/welding-defect-object-detection.wafer-defect-detectionDataset used by the paper:
Wu, Ming-Ju, Jyh-Shing R. Jang, and Jui-Long Chen. “Wafer Map Failure Pattern Recognition and Similarity Ranking for Large-Scale Data Sets.” IEEE Transactions on Semiconductor Manufacturing 28, no. 1 (February 2015): 1–12.
defect-detectionA dataset containing safe and vulnerable code to fine-tune a llm for defect detection.
The data is extracted from the wonderful work in the CVEFixes repository.
Citation:
@inproceedings{bhandari2021:cvefixes,
title = {{CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software}},
booktitle = {{Proceedings of the 17th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE '21)}},
author = {Bhandari, Guru… See the full description on the dataset page: https://huggingface.co/datasets/mcanoglu/defect-detection.dagm_defect_detection_textured_surfacesPCB-Solder-Joint-Defect-Detection-Dataset
PCB Solder Joint Defect Detection Dataset
The PCB manufacturing industry is facing challenges in maintaining high-quality standards, particularly in the detection of solder joint defects post-wave and reflow soldering. Existing solutions often rely on manual inspection or less efficient automated systems that are prone to errors. This dataset aims to address the specific technical challenge of accurately identifying and classifying defects in solder joints, fulfilling the business… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/PCB-Solder-Joint-Defect-Detection-Dataset.code-code-DefectDetection
Dataset is imported from CodeXGLUE and pre-processed using their script.
Where to find in Semeru:
The dataset can be found at /nfs/semeru/semeru_datasets/code_xglue/code-to-code/Defect-detection in Semeru
CodeXGLUE -- Defect Detection
Task Definition
Given a source code, the task is to identify whether it is an insecure code that may attack software systems, such as resource leaks, use-after-free vulnerabilities and DoS attack. We treat the task as… See the full description on the dataset page: https://huggingface.co/datasets/semeru/code-code-DefectDetection.Car-Gear-Surface-Defect-DetectionOak-Defect-Detection
Dataset Card for Oak Defect Detection
Dataset Description
Dataset Summary
The Oak Defect Detection dataset contains high-resolution line-scan imagery of green rough oak planks with pixel-level annotations for defect detection. The dataset is designed for semantic segmentation tasks to identify and classify defects in wood planks, including BlackRot, Knots, and Stains.
This dataset was collected using line-scan imaging systems and includes both color images and… See the full description on the dataset page: https://huggingface.co/datasets/nrodgers98/Oak-Defect-Detection.welding-defect-detectiondataset_defect_detection_200_OK
Real‑Life Industrial Dataset of Casting Product
Disesuaikan kembali oleh tim 200 OK untuk keperluan membuat model prediksi menggunakan Xception untuk mendeteksi cacat pada impeller submersible pump.
Tentang Dataset
Dimensi: 512 x 512 px grayscale
Dataset ini tanpa augmentasi lebih lanjut
Total gambar: 1300 gambar
519 gambar berlabel ok_front
781 gambar berlabel def_front
Penggunaan Dataset
Untuk training: 1040 gambar
Untuk validation: 260 gambar… See the full description on the dataset page: https://huggingface.co/datasets/Kelompok200OK/dataset_defect_detection_200_OK.insulator-defect-detectionPCB-Solder-Joint-Defect-Detection-Dataset
PCB Solder Joint Defect Detection Dataset
The PCB manufacturing industry is facing challenges in maintaining high-quality standards, particularly in the detection of solder joint defects post-wave and reflow soldering. Existing solutions often rely on manual inspection or less efficient automated systems that are prone to errors. This dataset aims to address the specific technical challenge of accurately identifying and classifying defects in solder joints, fulfilling the business… See the full description on the dataset page: https://huggingface.co/datasets/TerLiphi/PCB-Solder-Joint-Defect-Detection-Dataset.industrial-pcb-defect-detection-dataset
EdgePCB Defect Detection Dataset
Overview
The EdgePCB Defect Detection Dataset is a large-scale annotated dataset designed for training and evaluating deep learning models for automated PCB (Printed Circuit Board) inspection. The dataset supports real-time object detection tasks and is specifically curated for industrial applications using edge AI systems.
It is developed as part of the EdgePCB-AI project, which focuses on deploying YOLOv8-based defect detection models on… See the full description on the dataset page: https://huggingface.co/datasets/Tanishjain9/industrial-pcb-defect-detection-dataset.yolo-neu-det-surface-defect-object-detection
NEU-DET钢材表面缺陷目标检测数据集
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fabric-defect-detectionbig-dataset-test-defect-detectiondefect-detectionyolo-wood-surface-defect-detection
木材表面缺陷检测数据集
本数据集为木材表面缺陷检测数据集,适用于计算机视觉领域的目标检测任务。
数据集标签信息
检测类别数(nc):4
类别名称:Crack(裂纹), Dead Knot, Live Knot, Marrow
适用场景
Crack, Dead Knot, Live Knot等多类目标的智能检测
目标检测模型训练与部署
计算机视觉算法研究
网盘地址
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code_ujb_defectdetectiondefect-detection-testyolo-railway-track-defect-object-detection
铁路轨道缺陷目标检测数据集
本数据集为铁路轨道缺陷目标检测数据集,适用于智慧交通领域的目标检测任务。
数据集标签信息
检测类别数(nc):7
类别名称:Cracks(裂纹), Flakings(表层剥落), Grooves(沟槽磨耗), Joint(钢轨接缝), Shellings(壳状剥离), Spallings(碎屑剥落), Squats(踏面暗伤)
适用场景
Cracks, Flakings, Grooves等多类目标的智能检测
基础设施智能巡检与病害检测
目标检测模型训练与部署
计算机视觉算法研究
网盘地址
在线下载链接:https://www.data2.cn
在线获取数据集:铁路轨道缺陷目标检测数据集
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yolo-train-wheel-surface-defect-detection
火车车轮表面缺陷检测数据集
本数据集为火车车轮表面缺陷检测数据集,适用于计算机视觉领域的目标检测任务。
数据集标签信息
类别名称:flat, hole(孔洞), stain(污渍)
适用场景
flat的智能识别与检测
hole的智能识别与检测
stain的智能识别与检测
网盘地址
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euv-stochastic-defect-drift-detection-v0.1
What this dataset tests
Early stochastic failure is a drift event.
Not a single spike.
The signal is coherence decay across:
source noisepulse stabilityresist responseLER spreaddefect rate rise
Task
Predict JSON:
drift_score 0..1precursor_flag 0 or 1dominant_axis one of
nonesourceresistcoupled
Example
{"drift_score":0.52,"precursor_flag":1,"dominant_axis":"coupled"}
Inputs
All fields are deltas vs a known baseline window.… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/euv-stochastic-defect-drift-detection-v0.1.yolo-industrial-packaging-defect-detection
工业包装缺陷检测数据集
本数据集为工业包装缺陷检测数据集,适用于工业AI领域的实例分割任务。
适用场景
工业产线智能质检与缺陷自动筛查
实例分割模型训练与部署
计算机视觉算法研究
网盘地址
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在线获取数据集:工业包装缺陷检测数据集
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code-ujb-defectdetection_all_input
