Clothing Attributes Dataset

Datasets Overview

The dataset comprises 1,856 high-quality images, meticulously labeled with 26 distinct clothing attributes. Each label represents specific characteristics of garments, enabling granular analysis and model training. The labels were curated using Amazon Mechanical Turk, ensuring accuracy and diversity.

Key Features

• Comprehensive Annotations:
  • Includes attributes like “long sleeves,” “has collar,” “striped pattern,” “solid color,” and more.
  • Each image is labeled with multiple attributes, supporting multi-label classification tasks.
• Diverse Dataset:
  • Covers a variety of clothing styles, patterns, and designs, making it suitable for both generic and specialized research.
• Image Quality:
  • High-resolution images ensure clarity, allowing detailed feature extraction.

Applications of the Clothing Attributes Dataset

1. Fashion Recommendation Systems:
   Build models that suggest clothing items based on visual attributes.
2. E-commerce Automation:
   Automate tagging and categorization of products for online platforms.
3. Image Recognition Training:
   Train AI systems to detect and classify clothing features with high accuracy.
4. Fashion Trend Analysis:
   Analyze patterns and trends in clothing styles using attribute-based insights.

Advantages of Using This Dataset

• Multi-Label Capabilities: Enables the study of complex relationships between attributes.
• Enhances Research Efficiency: Pre-annotated data saves time, allowing researchers to focus on model development.
• Real-World Applications: Supports practical implementations in e-commerce, retail, and AI fashion solutions.
• High Accuracy Labels: Crowdsourced labeling ensures reliable data for robust training.

Download the Dataset Today!

Empower your research and AI projects with the Clothing Attributes Dataset. Whether you’re developing advanced image recognition models or studying fashion trends, this dataset provides the tools you need to succeed.