Datasets:

hzafar
/

TEXMET

pretty_name: TEXMET
license: cc0-1.0
annotations_creators:
  - expert-generated
language:
  - en
task_categories:
  - image-classification
  - other
tags:
  - computer-vision
  - textiles
  - cultural-heritage
  - art-history
  - metropolitan-museum
  - tapestry
  - fabric
  - pattern-recognition
  - image
size_categories:
  - 10K<n<100K
source_datasets:
  - original
configs:
  - config_name: default
    data_files: clean_dataset/clean_textiles_dataset.json

TeXMET: Curated Textile Dataset from the Metropolitan Museum of Art

Overview

TeXMET is a high-quality, manually curated dataset of textile and tapestry objects from the Metropolitan Museum of Art's Open Access collection. This dataset has been carefully cleaned, validated, and optimized for computer vision and deep learning applications.

🎯 TEXMET FINAL - CURATED DATASET

Total Images: 18,644 high-resolution images
Unique Objects: 1,697 textile/tapestry objects
Average Resolution: 3.3 MP (1557 x 1631 pixels)
Average File Size: 1.35 MB per image
Format: 100% JPEG, 92% RGB mode
Quality: Hand-selected, duplicates removed, visually validated

Dataset Statistics

Curation Method: Manual validation using FiftyOne + CLIP embeddings
Original Collection: 27,373 objects → Curated to 18,644 premium samples
Quality Control: Similarity analysis, duplicate removal, visual inspection
Coverage: Global textile traditions spanning 4000+ years
Image Quality: High-resolution, suitable for ML/CV applications

Directory Structure

TEXMET/
├── clean_dataset/                   # 🎯 TEXMET FINAL CURATED DATASET
│   ├── clean_textiles_dataset.json  # Main dataset (1,697 objects)
│   ├── texmet_metadata.json         # Comprehensive metadata
│   ├── images/                      # Primary images (~1,697 images)
│   └── additional_images/           # Additional views (~17K images)
├── FINAL_CORRECTED_MET_TEXTILES_DATASET/  # Original raw data (27,373 objects)
│   └── objects_with_images_only/    # Complete raw collection
└── README.md                        # This file

Data Quality & Curation Process

Initial Collection: 27,373 objects from MET API (99.274% success rate)
Filtering: Focus on high-quality textile/tapestry objects
Manual Curation: Visual inspection and validation using FiftyOne
Duplicate Removal: CLIP embedding analysis + manual verification
Quality Control: Removed low-quality, irrelevant, or damaged images
Final Validation: 1,697 premium objects with 18,644 images

Image Specifications

Total Images: 18,644 images
Average Dimensions: 1557 x 1631 pixels
Average Aspect Ratio: 1.14 (slightly portrait)
Average File Size: 1.35 MB
Average Resolution: 3.3 megapixels
Format: 100% JPEG
Color Mode: 92% RGB, 8% other modes
Quality: High-resolution, ML/CV ready

Research Applications

✅ Textile pattern recognition and classification
✅ Cultural heritage digitization and analysis
✅ Style transfer and generative AI
✅ Historical textile dating and attribution
✅ Cross-cultural design studies
✅ Computer vision algorithm development
✅ Digital art and design inspiration
✅ Large-scale image analysis and clustering

Usage Examples

import json
import pandas as pd

# Load the curated dataset
with open('clean_dataset/clean_textiles_dataset.json', 'r') as f:
    data = json.load(f)

df = pd.DataFrame(data)
print(f"TeXMET Final: {len(df)} curated objects")

# Load metadata
with open('clean_dataset/texmet_metadata.json', 'r') as f:
    metadata = json.load(f)
print(f"Total images: {metadata['image_statistics']['total_images']}")

Version History

TeXMET Final v1.0 (July 2025): 1,697 curated objects, 18,644 images
Raw Collection (July 2025): 27,373 objects collected from MET API

Technical Specifications

Format: JSON with UTF-8 encoding
Image Format: 100% JPEG
Resolution: High-resolution (average 3.3 MP)
File Organization: Git LFS for large files
Compatibility: Ready for PyTorch, TensorFlow, OpenCV

Citation and Credits

TeXMET Dataset Citation

@dataset{texmet2025,
  title={TeXMET: Curated Textile Images from the Metropolitan Museum of Art},
  author={HAMZA},
  year={2025},
  publisher={Thesis Project},
  version={1.0},
  note={Manually curated dataset: 1,697 objects, 18,644 images}
}

Original Data Source

This dataset (TeXMET) is a curated subset of textiles and tapestries from The Metropolitan Museum of Art's Open Access collection, compiled for research purposes. To the best of our knowledge, this is the first comprehensive compilation of MET's textile and tapestry collections in this format, manually curated and optimized for computer vision applications.

@misc{MET_OpenAccess_2024,
  author       = {{The Metropolitan Museum of Art}},
  title        = {Open Access Artworks Dataset},
  year         = {2024},
  howpublished = {\url{https://github.com/metmuseum/openaccess}},
  note         = {CC0 public-domain images and metadata; accessed July 2025},
}

Legal & Licensing

License: CC0 (Public Domain) - same as original MET data
Usage Rights: Free for any purpose without restriction
Attribution: Metropolitan Museum of Art (recommended)
Copyright: All images are in the public domain

Acknowledgments

Data Source: The Metropolitan Museum of Art Open Access Initiative
Curation Tools: FiftyOne, CLIP embeddings, manual validation
API Access: MET Museum Collection API
Project: TeXMET - Textile Analysis Thesis Project
Created: July 2025

Performance & Quality Metrics

Image Quality: 100% JPEG, high resolution
Duplicate Removal: CLIP similarity + manual verification
Manual Validation: Visual inspection of all selected objects
Research Ready: Optimized for ML/CV applications

Note: This is a research compilation and curation of existing open access data. All rights and credits belong to The Metropolitan Museum of Art. We thank the MET for making their collection freely available for research and education.

🎯 TeXMET Final: 1,697 Premium Objects, 18,644 High-Quality Images Total Dataset Size: 26.5 GB. Ready for Computer Vision and Machine Learning Applications!

Last Updated: July 8, 2025