Condiment Product Occlusion Image Dataset
#object detection #image classification #product recognition #image segmentation #computer vision
- 15000 records
- 3.4G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-09-20
AI Analysis & Value Prop
The condiment market is facing challenges such as product misidentification and occlusion in images, which can hinder effective inventory management and customer experience. Current solutions often fail to account for occlusions that obscure product labels, leading to inaccuracies in automated processes. This dataset aims to address these issues by providing a comprehensive collection of occluded images of popular Asian condiments like Kikkoman, Maggi, and Lee Kum Kee, thus fulfilling a critical need for training robust computer vision systems. The dataset will be collected using high-resolution cameras in various retail environments, ensuring diverse lighting and occlusion scenarios. Quality control will involve multiple rounds of annotation, consistency checks, and expert reviews to maintain high accuracy. Images will be stored in JPG format, organized systematically for easy access and processing.
Dataset Insights
Sample Examples
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Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| object_count | int | The total number of condiment products in the image. |
| occlusion_level | string | The degree to which products are obscured, such as partially or completely blocked. |
| label | string | The labels or names of condiment products detected in the image. |
| bounding_box | json | Coordinate information of the bounding box for each product. |
| visibility | float | The proportion of the product actually visible in the image. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What is the condiment product occlusion recognition image dataset?
- The condiment product occlusion recognition image dataset is a specialized object detection dataset used to identify condiment products in the retail industry, assisting in recognizing these products when they are occluded in images.
- What are the applications of this dataset in the e-commerce field?
- In the e-commerce field, this dataset can be used to optimize image recognition and processing tasks, improving the display and retrieval accuracy of condiment products on e-commerce platforms.
- How does the condiment product occlusion recognition image dataset help improve product recognition rate?
- This dataset improves product recognition rates by providing a wealth of occlusion scenario images, which help train models to better identify partially occluded condiment products.
- How is the image information in this dataset annotated?
- The image information in this dataset is annotated using object detection techniques, with each condiment product labeled for its location, size, and occlusion status.
- Which industries or fields can benefit from this dataset?
- In addition to the retail and e-commerce industries, this dataset can also be used in image processing, computer vision, and AI research fields to improve the accuracy of related technologies and applications.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Condiment Product Occlusion Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/54cbbe86f83ed8c5b189707a151f7be0?dataset_scene_id=9},
urldate={2025-08-28},
keywords={condiment dataset,image occlusion dataset,retail e-commerce images,computer vision training dataset},
version={1.0}
}Using this in research? Please cite us.
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