file_name stringclasses 1 value | quality stringclasses 1 value | sweet_potato_count stringclasses 1 value | sweet_potato_size stringclasses 1 value | sweet_potato_color stringclasses 1 value | background_type stringclasses 1 value | light_conditions stringclasses 1 value | field_location stringclasses 1 value |
|---|---|---|---|---|---|---|---|
edc98049b5134932cf2a3184eefb252f.jpg | 5184*3456 | About 20 | Average about 15 cm | Orange | No obvious background | Indoor lighting | Not applicable |
Sweet Potato Automatic Counting Dataset
In the agricultural sector, sweet potatoes, as one of the important crops, face challenges such as low efficiency in yield monitoring and management. Traditional manual counting methods are not only time-consuming and labor-intensive but also prone to errors. Existing automatic counting technologies largely rely on simple image processing algorithms, which fail to meet the demands for high precision and efficiency. This dataset aims to provide a rich sweet potato image dataset to promote the application of object detection algorithms in sweet potato counting, addressing the issues of low automation and insufficient counting accuracy. The dataset contains 5000 annotated sweet potato images collected using high-resolution cameras under various lighting and environmental conditions, ensuring data diversity and completeness. For quality control, a multi-round annotation and expert review mechanism is adopted to ensure the consistency and accuracy of data annotations. The data is stored in JPEG format and organized by image ID for convenient retrieval and use.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| sweet_potato_count | int | The number of sweet potatoes in the image. |
| sweet_potato_size | float | The average size of the sweet potatoes in centimeters. |
| sweet_potato_color | string | The dominant color of the sweet potatoes. |
| background_type | string | The type of background in the image, such as soil or grass. |
| light_conditions | string | The lighting conditions when the image was taken, such as sunny or cloudy. |
| field_location | string | Description of the field location at the time of shooting. |
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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