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---
language:
- en
license:
- mit
---
# ADT Dataset
## Dataset Description
This dataset contains Aria Digital Twin (ADT) sequences with various sensor data and annotations, including 2D/3D bounding boxes, trajectories, eye gaze data, and VRS recordings.
## Quick Start
```python
from adt_dataset_loader import ADTDatasetLoader
# Load entire dataset
loader = ADTDatasetLoader("ariakang/ADT-test")
# Load specific sequence
loader = ADTDatasetLoader("ariakang/ADT-test", sequence_name="Apartment_release_clean_seq131_M1292")
```
## Installation
```bash
# Install required packages
pip install datasets pandas
```
## Dataset Structure
Each sequence contains:
- VRS Files:
- video.vrs
- synthetic_video.vrs
- segmentations.vrs
- depth_images.vrs
- CSV Data:
- 2D/3D bounding boxes
- Aria device trajectories
- Eye gaze data
- Scene objects
- JSON Data:
- Instance annotations
- Metadata
- MPS Data:
- Eye gaze processing
- SLAM results
## Flexible Loading Options
### 1. Load Entire Dataset
```python
# Initialize loader with all sequences
loader = ADTDatasetLoader("ariakang/ADT-test")
# See available sequences and data types
available_files = loader.get_available_files()
print("Available files:", available_files)
# Load all data types
bbox_2d = loader.load_2d_bounding_boxes()
bbox_3d = loader.load_3d_bounding_boxes()
trajectory = loader.load_aria_trajectory()
eyegaze = loader.load_eyegaze()
metadata = loader.load_metadata()
slam_data = loader.load_mps_slam()
```
### 2. Load Specific Sequences
```python
# Load a specific sequence
loader = ADTDatasetLoader(
"ariakang/ADT-test",
sequence_name="Apartment_release_clean_seq131_M1292"
)
# Load data from this sequence
bbox_2d = loader.load_2d_bounding_boxes()
trajectory = loader.load_aria_trajectory()
```
### 3. Load Selected Data Types
```python
# Initialize loader for specific sequence
loader = ADTDatasetLoader("ariakang/ADT-test", "Apartment_release_clean_seq131_M1292")
# Load only 2D bounding boxes and VRS info
bbox_2d = loader.load_2d_bounding_boxes()
vrs_info = loader.get_vrs_files_info()
# Get paths to specific VRS files
video_vrs = [f for f in vrs_info if f['filename'] == 'video.vrs'][0]
print(f"Video VRS path: {video_vrs['path']}")
# Load only SLAM data
slam_data = loader.load_mps_slam()
closed_loop = slam_data['closed_loop'] # Get specific SLAM component
```
## Available Data Types and Methods
### Main Data Types
```python
# Bounding Boxes and Trajectories
bbox_2d = loader.load_2d_bounding_boxes()
bbox_3d = loader.load_3d_bounding_boxes()
trajectory = loader.load_aria_trajectory()
# Eye Gaze and Scene Data
eyegaze = loader.load_eyegaze()
scene_objects = loader.load_scene_objects()
# Metadata and Instances
metadata = loader.load_metadata()
instances = loader.load_instances()
# MPS Data
eye_gaze_data = loader.load_mps_eye_gaze() # Returns dict with 'general' and 'summary'
slam_data = loader.load_mps_slam() # Returns dict with various SLAM components
```
### VRS Files
```python
# Get VRS file information
vrs_info = loader.get_vrs_files_info()
# Example: Access specific VRS file info
for vrs_file in vrs_info:
print(f"File: {vrs_file['filename']}")
print(f"Path: {vrs_file['path']}")
print(f"Size: {vrs_file['size_bytes'] / 1024 / 1024:.2f} MB")
```
### Custom Loading
```python
# Load any file by name
data = loader.load_file_by_name("your_file_name.csv")
```
## Data Format Examples
### 2D Bounding Boxes
```python
bbox_2d = loader.load_2d_bounding_boxes()
print(bbox_2d.columns)
# Columns: ['object_uid', 'timestamp[ns]', 'x_min[pixel]', 'x_max[pixel]', 'y_min[pixel]', 'y_max[pixel]']
```
### Aria Trajectory
```python
trajectory = loader.load_aria_trajectory()
print(trajectory.columns)
# Columns: ['timestamp[ns]', 'x', 'y', 'z', 'qx', 'qy', 'qz', 'qw']
```
### MPS SLAM Data
```python
slam_data = loader.load_mps_slam()
# Components:
# - closed_loop: DataFrame with closed-loop trajectory
# - open_loop: DataFrame with open-loop trajectory
# - calibration: Calibration parameters
```
## Error Handling
```python
try:
data = loader.load_file_by_name("non_existent_file.csv")
except ValueError as e:
print(f"Error: {e}")
```
## Notes
- All CSV files are loaded as pandas DataFrames
- JSON/JSONL files are loaded as Python dictionaries/lists
- VRS files are not loaded into memory, only their metadata and paths are provided
- Use `get_available_files()` to see all available data in your sequence
## Repository Structure
VRS files are stored in sequence-specific folders:
`sequences/{sequence_name}/vrs_files/`
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