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The get_data function provides access to test data and model files, handling Git LFS downloads automatically.

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Basic Usage

from dimos.utils.data import get_data

# Get path to a data file/directory
data_path = get_data("cafe.jpg")
print(f"Path: {data_path}")
print(f"Exists: {data_path.exists()}")

Path: /home/lesh/coding/dimos/data/cafe.jpg
Exists: True

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How It Works

output
  1. Checks if data/{name} already exists locally
  2. If missing, pulls the .tar.gz archive from Git LFS
  3. Decompresses the archive to data/
  4. Returns the Path to the extracted file/directory

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Common Patterns

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Loading Images

from dimos.utils.data import get_data
from dimos.msgs.sensor_msgs.Image import Image

image = Image.from_file(get_data("cafe.jpg"))
print(f"Image shape: {image.data.shape}")

Image shape: (771, 1024, 3)

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Loading Model Checkpoints

skip
from dimos.utils.data import get_data

model_dir = get_data("models_yolo")
checkpoint = model_dir / "yolo11n.pt"
print(f"Checkpoint: {checkpoint.name} ({checkpoint.stat().st_size // 1024}KB)")

Checkpoint: yolo11n.pt (5482KB)

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Loading Recorded Data for Replay

skip
from dimos.utils.data import get_data
from dimos.utils.testing.replay import TimedSensorReplay

data_dir = get_data("unitree_office_walk")
replay = TimedSensorReplay(data_dir / "lidar")
print(f"Replay {replay} loaded from: {data_dir.name}")
print(replay.find_closest_seek(1))

Replay <dimos.utils.testing.replay.TimedSensorReplay object at 0x7fdc24c708f0> loaded from: unitree_office_walk
{'type': 'msg', 'topic': 'rt/utlidar/voxel_map_compressed', 'data': {'stamp': 1751591000.0, 'frame_id': 'odom', 'resolution': 0.05, 'src_size': 77824, 'origin': [-3.625, -3.275, -0.575], 'width': [128, 128, 38], 'data': {'points': array([[ 2.725, -1.025, -0.575],
       [ 2.525, -0.275, -0.575],
       [ 2.575, -0.275, -0.575],
       ...,
       [ 2.675, -0.525,  0.775],
       [ 2.375,  1.175,  0.775],
       [ 2.325,  1.225,  0.775]], shape=(22730, 3))}}}

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Loading Point Clouds

skip
from dimos.utils.data import get_data
from dimos.mapping.pointclouds.util import read_pointcloud

pointcloud = read_pointcloud(get_data("apartment") / "sum.ply")
print(f"Loaded pointcloud with {len(pointcloud.points)} points")

Loaded pointcloud with 63672 points

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Data Directory Structure

Data files live in data/ at the repo root. Large files are stored in data/.lfs/ as .tar.gz archives tracked by Git LFS. 
data/
 ├──cafe.jpg
 ├──apartment/
 │   └──sum.ply
 └──.lfs/
     ├──cafe.jpg.tar.gz
     └──apartment.tar.gz

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Adding New Data

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Small Files (< 1MB)

Commit directly to data/:
skip
cp my_image.jpg data/

# 2. Compress and upload to LFS
./bin/lfs_push

git add data/.lfs/my_image.jpg.tar.gz

git commit -m "Add test image"

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Large Files or Directories

Use the LFS workflow:
skip
# 1. Copy data to data/
cp -r my_dataset/ data/

# 2. Compress and upload to LFS
./bin/lfs_push

git add data/.lfs/my_dataset.tar.gz

# 3. Commit the .tar.gz reference
git commit -m "Add my_dataset test data"
The lfs_push script:
  1. Compresses data/my_dataset/ → data/.lfs/my_dataset.tar.gz
  2. Uploads to Git LFS
  3. Stages the compressed file
A pre-commit hook (bin/hooks/lfs_check) blocks commits if you have uncompressed directories in data/ without a corresponding .tar.gz in data/.lfs/.

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Location Resolution

When running from:
  • Git repo: Uses {repo}/data/
  • Installed package: Clones repo to user data dir:
    • Linux: ~/.local/share/dimos/repo/data/
    • macOS: ~/Library/Application Support/dimos/repo/data/
    • Fallback: /tmp/dimos/repo/data/