Datasets:
file_name stringclasses 5 values | quality stringclasses 5 values | obstruction_level stringclasses 4 values | folded_state stringclasses 2 values | background_complexity stringclasses 4 values |
|---|---|---|---|---|
017ce8399932e7684d52f39ff6573fcd.jpg | 1280*1219 | partially obstructed | worn | simple |
2f232a2c17f386f57d00e02c44aaad99.jpg | 1280*960 | partially obstructed | worn | complex |
5a16cb22f2394ea210f84f27e4537b46.jpg | 1280*2276 | unobstructed | worn | simple |
95968802d912679f1d9afb48f778afed.jpg | 1280*1008 | partial obstruction | worn | medium |
9d49576a1b173cf7795fb82e51e0363e.jpg | 1280*2200 | Unobstructed | Worn | Simple |
POLO Shirt Occlusion Image Dataset
The retail e-commerce industry faces significant challenges with product visibility due to various occlusions, such as clothing folds and body postures that obscure branding. Existing solutions often fail to accurately identify and classify products under these conditions, leading to reduced sales and customer dissatisfaction. This dataset aims to address the specific need for robust algorithms that can effectively handle occlusions in product images, enhancing visibility and recognition for better customer engagement. The dataset comprises images collected from diverse retail environments, utilizing high-resolution cameras in controlled lighting to ensure clarity. Quality control measures include multi-round annotations, consistency checks among annotators, and expert reviews to maintain high accuracy. The data is organized in a JPG format, with structured folders for easy access to images and associated metadata.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| obstruction_level | string | The degree to which the polo shirt is occluded in the image, for example, partially occluded or fully occluded. |
| folded_state | string | The state of the polo shirt in the image, whether it is hanging, folded, or worn. |
| background_complexity | string | The complexity of the background in the image, such as simple or complex. |
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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