Datasets:
file_name stringclasses 5 values | quality stringclasses 5 values | curtain_track_type stringclasses 1 value | material_composition stringclasses 3 values | defect_presence stringclasses 1 value | color stringclasses 3 values | surface_finish stringclasses 1 value | dimensions stringclasses 3 values | installation_type stringclasses 2 values | track_shape stringclasses 1 value |
|---|---|---|---|---|---|---|---|---|---|
0f4a41190c3dc48e23cc70790b97b02e.png | 1701*1450 | Single track | Aluminum | No | White | Matte | Unknown | Ceiling-mounted | C-shape |
2cbb558322334bb07a86800023a4e906.png | 1045*1450 | Single track | Aluminum | No | Silver | Matte | Unknown | Ceiling-mounted | C-shape |
8bbd71a02fe4612e89f1bd1a5f936b5c.png | 2176*1450 | Single track | Aluminum | No | White | Matte | Approximately 2 meters long, width and height unclear | Wall-mounted | C-shape |
cfdae9c4b054407439612dc1b50e1c0a.png | 1845*1450 | Single track | Metal | No | Black | Matte | Moderate length, width and height undetermined | Ceiling-mounted | C-shape |
fb613e62f5c5f1b40cd75cdc9a01971a.png | 1334*1450 | Single track | Plastic | No | White | Matte | Unknown | Ceiling-mounted | C-shape |
Curtain Track Guide Slot Detection Dataset
The current retail e-commerce industry faces challenges such as uneven product quality and low detection efficiency, especially in the detection of curtain track guide slots. Manual inspection is not only time-consuming but also prone to human errors, making quality control difficult. Existing automated detection solutions largely rely on traditional visual recognition technologies, which struggle to adapt to complex environments and still lack accuracy. This dataset aims to improve the detection accuracy and efficiency of curtain track guide slots through high-quality target detection data, meeting the growing quality demands of the smart home product market. Data is collected using high-resolution cameras under standard lighting conditions to ensure clear and usable images. To enhance data quality, we implemented multiple rounds of annotation and consistency checks and invited domain experts for review to ensure data accuracy and reliability. Data is stored in JPEG format and categorized and organized according to product type and detection needs.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| curtain_track_type | string | Indicates the specific type of curtain track, such as single track or double track. |
| material_composition | string | The main material composition of the curtain track, such as aluminum or plastic. |
| defect_presence | boolean | Detects whether there are noticeable defects in the curtain track, with values being yes or no. |
| color | string | The color of the curtain track, such as white or black. |
| surface_finish | string | The surface finishing process of the curtain track, such as matte or glossy. |
| dimensions | string | The length, width, and height of the curtain track. |
| installation_type | string | The installation type of the curtain track, such as ceiling-mounted or wall-mounted. |
| track_shape | string | The cross-sectional shape of the curtain track, such as C-shaped or I-shaped. |
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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