Datasets:
file_name stringclasses 5
values | quality stringclasses 3
values | product_category stringclasses 2
values | occlusion_level stringclasses 3
values | background_complexity stringclasses 2
values |
|---|---|---|---|---|
4a648908bfefb3d165a274fd28b213b4.jpg | 1280*960 | Cleaner | Not Occluded | Normal |
7e41a1bdd336aeea2a63bf2d9d9943f1.jpg | 1280*2272 | Cleaner | Partially Occluded | Complex |
92570b90e6858acb57523e6ec5c81944.jpg | 1280*1706 | Cleaner | Partially Occluded | Normal |
984118071c01f132b44f20a1ab788ab0.jpg | 1280*1706 | Cleaning Agent | Partially Obstructed | Normal |
c404b07b5d417c1e122fd48e68916b33.jpg | 1280*960 | Cleaner | Partially Occluded | Normal |
Household Cleaning Products Occlusion Image Dataset
The retail e-commerce industry faces significant challenges in accurately recognizing products that are partially obstructed in images. Current models often struggle with occlusion, leading to decreased performance in product detection and search functionalities. Existing datasets lack sufficient diversity in occluded images, making it difficult for machine learning models to generalize. This dataset aims to address these challenges by providing a rich collection of images featuring common household cleaning products like Lysol, Clorox, Mr. Clean, and Vanish, captured in various occlusion scenarios. The data was collected using high-resolution cameras in controlled environments to ensure clarity and consistency. Quality control measures included multiple rounds of annotation, consistency checks among annotators, and expert reviews to ensure high accuracy. The dataset is organized in JPG format, with images structured in folders by product type, facilitating easy access and integration into machine learning workflows. The dataset contains 15,000 images, and the file size is estimated at 1.8 GB.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| product_category | string | The category of household cleaning products in the image, such as cleaning agents, brooms, mops, etc. |
| occlusion_level | string | The level of occlusion of household cleaning products in the image, such as partially occluded, fully occluded, or not occluded. |
| background_complexity | string | The complexity of the image background, such as simple, complex, ordinary. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| 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 |
Source & Contact
If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com
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