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README.md

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+---
+tags:
+- classification tasks
+- image recognition
+- machine learning
+- product identification
+- online shopping
+- image search
+license: cc-by-nc-sa-4.0
+task_categories:
+- image-classification
+language:
+- en
+pretty_name: Parent-Child Outfit Image Classification Dataset
+size_categories:
+- 1B<n<10B
+---
+
+# Parent-Child Outfit Image Classification Dataset
+
+With the rapid development of retail e-commerce, the parent-child outfit market is also gradually expanding, and consumer demand for parent-child outfit products is increasing. However, existing product classification systems often fail to accurately identify and classify parent-child outfits, leading to poor user experience and affecting sales performance. Current solutions lack in labeling accuracy and data integrity, making it difficult to meet the growing market demand. Therefore, the construction of a parent-child outfit image classification dataset is aimed at improving the accuracy of product identification and meeting the classification needs of e-commerce platforms for parent-child outfit products. This dataset contains 15,000 images of parent-child outfit products, and through high-quality labeling and classification, it helps e-commerce platforms provide more accurate search and recommendation services.
+
+Data collection was carried out using high-resolution cameras in well-lit environments to ensure image quality. We have undertaken multiple rounds of labeling and consistency checks to ensure the accuracy of annotations, and invited domain experts for review. Data is stored in JPG format, and images are organized into folders according to category to facilitate subsequent retrieval and processing.
+
+## Technical Specifications
+
+| Field | Type | Description |
+| :---  | :---  | :--- |
+| file_name | string | File name |
+| quality | string | Resolution |
+| clothing_type | string | The type of clothing in the image, such as 'T-Shirt', 'Dress' or 'Set'. |
+| number_of_people | int | The number of people appearing in the image. |
+| background_scene | string | The background scene where the image was taken, such as 'indoor', 'outdoor', 'studio', etc. |
+| age_group_detected | string | The age group of the people detected, such as 'adult', 'child', or 'infant'. |
+| color_palette | string | The main color palette described in the image, such as 'warm colors', 'cool colors', or 'neutral colors'. |
+| pose_type | string | The type of poses of the people in the image, such as 'standing', 'sitting', or 'walking'. |
+
+## Compliance Statement
+
+<table>
+  <tr>
+    <td>Authorization Type</td>
+    <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
+  </tr>
+  <tr>
+    <td>Commercial Use</td>
+    <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
+  </tr>
+  <tr>
+    <td>Privacy and Anonymization</td>
+    <td>No PII, no real company names, simulated scenarios follow industry standards</td>
+  </tr>
+  <tr>
+    <td>Compliance System</td>
+    <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
+  </tr>
+</table>
+
+## Source & Contact
+
+If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/0108f48bff42a227d1971cac55c9ec61?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com