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  ### Notes:
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- - **File naming convention**: `{collection_robot_MAC_address}_{collection_time}_{point_name}`.
 
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  - **Annotations**:
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- - `.json`: Contains pixel-level polygonal segmentation masks for industrial objects.
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- - `.txt`: Contains human-readable semantic descriptions of the scene.
 
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  - **Other modalities**:
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- - Videos: `.mp4` (RGB / IR)
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- - Sensor logs: `.txt` (gas, temp, humidity)
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- - Point clouds: `.bag` (ROS bag format)
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- - Audio: `.wav`
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- - **Parameters**: Includes extrinsic calibration, hardware specs, and software settings for accurate multimodal fusion.
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  > This structure ensures synchronized access across all modalities and supports both supervised learning and world modeling tasks. Each sample metadata (e.g., robot ID, location, timestamp, safety label) is stored in JSON format. Segmentation masks are provided as PNG images with instance IDs matching the annotation JSON.
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  ## Data Splits
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  | Split | Number of Samples |
 
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  ### Notes:
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+ - **Inspection point identifier**: Each folder name represents an inspection point, such as `coal_conveyor-Level04-SuspendedRail-000560`. The same identifier is used in both the `Annotations` and `Other_modalities` folders to enable cross-modal correspondence.
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+ - **Inspection instances**: A single inspection point may contain multiple inspection instances. In the `Annotations` folder, these instances are distinguished by numerical suffixes appended to the filenames, such as `-001`, `-002`, and `-003`.
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  - **Annotations**:
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+ - `.jpg`: Visible-light image frame for the corresponding inspection instance.
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+ - `.json`: Pixel-level polygonal segmentation annotations and related metadata.
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+ - `.txt`: Human-readable semantic description of the scene.
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  - **Other modalities**:
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+ - `.mp4`: Visible-light and infrared videos.
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+ - `.txt`: Sensor logs, including gas concentration, temperature, and humidity.
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+ - `.bag`: Point-cloud data in ROS bag format.
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+ - `.wav`: Audio recordings.
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+ - **Parameters**: The `Parameters` folder contains hardware specifications, software settings, and calibration-related files used to support multimodal interpretation and fusion.
 
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  > This structure ensures synchronized access across all modalities and supports both supervised learning and world modeling tasks. Each sample metadata (e.g., robot ID, location, timestamp, safety label) is stored in JSON format. Segmentation masks are provided as PNG images with instance IDs matching the annotation JSON.
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+ The shared inspection point identifier allows the multimodal and sensory records in `Other_modalities` to be linked to one or more annotated inspection instances in `Annotations`.
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  ## Data Splits
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  | Split | Number of Samples |