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README.md

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+---
+tags:
+- Object Detection
+- Image Classification
+- Assembly Line Automation
+- Accident Vehicle Quick Inspection
+license: cc-by-nc-sa-4.0
+task_categories:
+- object-detection
+language:
+- en
+pretty_name: Front Lamp Detection Dataset
+size_categories:
+- 1B<n<10B
+---
+
+# Front Lamp Detection Dataset
+
+In the industrial sector, the need for automated quality control and rapid inspection of accident vehicles is increasing due to the growing complexity of production lines and safety regulations. Current solutions often struggle with accuracy and speed, leading to inefficiencies and potential safety hazards. This dataset aims to address these challenges by providing high-quality annotated images of front lamps to enhance detection algorithms. Data is collected using high-resolution cameras in controlled environments, ensuring a consistent quality. Multiple rounds of annotation and expert reviews are implemented to maintain high standards of labeling accuracy. The dataset is stored in JPG format, organized by image categories, and supported by a comprehensive metadata structure.
+
+## Technical Specifications
+
+| Field | Type | Description |
+| :---  | :---  | :--- |
+| file_name | string | File name |
+| quality | string | Resolution |
+| headlight_position | string | The position or area information of the headlights in the image. |
+| headlight_count | int | The number of headlights detected in the image. |
+| glare_presence | boolean | Whether there is glare from the headlights present in the image. |
+| headlight_type | string | The type of headlights, such as halogen lamps, LED lights, etc. |
+
+## Compliance Statement
+
+<table>
+  <tr>
+    <td>Authorization Type</td>
+    <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
+  </tr>
+  <tr>
+    <td>Commercial Use</td>
+    <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
+  </tr>
+  <tr>
+    <td>Privacy and Anonymization</td>
+    <td>No PII, no real company names, simulated scenarios follow industry standards</td>
+  </tr>
+  <tr>
+    <td>Compliance System</td>
+    <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
+  </tr>
+</table>
+
+## Source & Contact
+
+If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/e9fbc474764c36e6bbd7a29898611fbd?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com