Computer vision datasets for manufacturing inspection
From defect detection to assembly verification, images.cv helps manufacturing teams build structured datasets for quality assurance and production monitoring — with annotation, packaging, and ML-ready delivery.
Manufacturing CV use cases
Structured datasets tailored to real industrial inspection workflows.
Defect detection on production lines
Identify scratches, dents, cracks, and anomalies in real-time visual inspection.
PCB and electronics inspection
Detect solder defects, missing components, and misalignments on circuit boards.
Weld quality assessment
Classify weld seam quality, porosity, undercut, and incomplete fusion defects.
Assembly verification and part counting
Verify correct assembly sequences and count parts per station or container.
Surface defect classification
Classify surface finish issues like rust, pitting, discoloration, and coating failures.
Tool and equipment monitoring
Track tool wear, detect misplacement, and monitor equipment condition over time.
What you get
A structured, annotated dataset ready for your training pipeline.
bboxes/
Bounding box JSON files
coco/
COCO-format annotations
data/
Final image files
masks/
Segmentation masks
yolo/
YOLO TXT annotations
index.csv
File-level dataset index
meta.json
Dataset metadata summary
Standard annotation formats
YOLO, COCO, bounding boxes, and segmentation masks in every delivery.
Defect-level labeling
Each defect type is labeled and classified according to your taxonomy.
Annotation alignment
All annotations are validated against image files to ensure consistency.
Train / validation / test split
Optional dataset splitting with consistent file naming across partitions.
Tell us about your dataset needs
Fields marked with * are required.
Annotation formats needed
Ready to build your manufacturing CV dataset?
Tell us about your inspection use case and we'll scope it together.