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.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.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.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.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.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.PCB-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.insulator-defect-detectiondefect-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.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… See the full description on the dataset page: https://huggingface.co/datasets/pavan777/code_x_glue_cc_defect_detection.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.defect-detection-testcode_ujb_defectdetectionbig-dataset-test-defect-detectioncode-ujb-defectdetection_all_inputdefect_detection
Defect Detection for Industrial Quality Control
This repository contains the datasets and model checkpoints for an automated quality control system designed to detect defects in plastic injection-molded components.
🔍 Project Overview
This project applies deep learning to industrial manufacturing. By utilizing YOLOv8 architectures, the system identifies surface defects in real-time, specifically optimized for deployment on edge devices like the Raspberry Pi 5.
📂… See the full description on the dataset page: https://huggingface.co/datasets/KrP77-HF/defect_detection.