Yoga Pants Occlusion Image Dataset

#object detection #image segmentation #classification #fashion detection #image classification #model training
  • 5000 records
  • 1.2G
  • JPG/PNG/JSON
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-03-18

AI Analysis & Value Prop

The current retail e-commerce industry faces challenges in accurately detecting product visibility due to occlusions caused by apparel styles, particularly yoga pants. Existing solutions often struggle with the variability of occlusion types and angles, leading to reduced accuracy in automated systems. This dataset aims to tackle the issue of identifying and classifying images where the waist or knee areas of yoga pants are obscured by motion blur or camera angles. The data is collected using high-resolution cameras in controlled environments with varying lighting to simulate real-world conditions. Quality control is performed through multiple annotation rounds, consistency checks, and expert reviews. The dataset is organized in JPG format, with each image accompanied by detailed annotations for effective training and evaluation.

Dataset Insights

Sample Examples

d0703528**.png|1280*1661|1.32 MB

21c595a7**.png|1280*3399|899.23 KB

809c422e**.png|1280*1208|1.68 MB

3efa0771**.png|1280*1305|1.90 MB

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
occlusion_levelintThe proportion or degree to which the target object is occluded, with higher values indicating more severe occlusion.
blur_levelintThe degree of blur in the image, derived from image clarity analysis, used to assess the blur condition of different images.
color_dominancestringThe dominant color in the image, with the primary tone of the image extracted through color analysis.
texture_complexityintThe complexity of textures in the image, obtained by analyzing changes in local features.
background_clutterintThe level of complexity or clutter in the background, with higher values indicating a more complex background.
reflection_presencebooleanWhether there is a reflection in the image, true if present, otherwise false.

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What is the Yoga Pants Occlusion Recognition Image Dataset?
The Yoga Pants Occlusion Recognition Image Dataset focuses on improving the accuracy of clothing recognition, particularly addressing issues of occlusion and blur.
What application areas is this dataset suitable for?
This dataset is mainly suitable for the retail sector, used for developing and optimizing clothing recognition systems to improve performance in cases of occlusion and blur.
How can this dataset be used to improve the accuracy of clothing recognition?
By using this dataset to train and fine-tune models, one can better recognize and handle situations where occlusion and blur are present in the images, thus improving clothing recognition accuracy.
Why choose image modality to construct this dataset?
Image modality is the most direct and rich source of information in visual recognition, suitable for conducting object detection tasks, especially for analysis of specific scenarios like clothing and occlusion.
What types of occlusion and blur situations are included in the dataset?
The dataset includes occlusion and blur situations mainly related to everyday wearing scenarios of yoga pants, such as overlaps, folds, and complex backgrounds.

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Cite this Work

@dataset{Mobiusi2025,
  title={Yoga Pants Occlusion Image Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/0b80d9c6e1a56fc1e9b4ac846560a360?dataset_scene_id=9},
  urldate={2025-08-28},
  keywords={Yoga Pants Dataset,Occlusion Detection,Image Classification,Retail E-commerce},
  version={1.0}
}

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