All pre-generated data released by the Princeton Vision and Learning lab is hosted here: https://infinigen-data.cs.princeton.edu/
You can download these yourself, or use our rudimentary download/untar script as shown in the examples below. To minimize traffic, please use the --cameras, --seeds and --data_types arguments to download only the data you are interested in.
# See all available options (recommended):
python -m tools.download_pregenerated_data --help
# Download a few images with geometry ground truth visualization pngs to inspect locally:
python -m tools.download_pregenerated_data --output_folder outputs/my_download --repo_url https://infinigen-data.cs.princeton.edu/ --release_name 2023_10_13_preview --seeds 4bbdd3e0 2d2c1104 --cameras camera_0 --data_types Image_png Depth_png Flow3D_png SurfaceNormal_png OcclusionBoundaries_png
# Download only the data needed monocular depth (modify as needed for Flow3D, ObjectSegmentation etc):
python -m tools.download_pregenerated_data --output_folder outputs/my_download --repo_url https://infinigen-data.cs.princeton.edu/ --release_name 2023_10_13_preview --cameras camera_0 --data_types Image_png Depth_npy
# Download everything available in a particular datarelease
python -m tools.download_pregenerated_data --output_folder outputs/my_download --repo_url https://infinigen-data.cs.princeton.edu/ --release_name 2023_10_13_preview
We provide an example pytorch-style dataset class (dataset_loader.py) to help load data in our format.
Assuming you ran the "Download only the data needed monocular depth" example command above, you should be able to use the following example by a python interpreter (python
) in the root of the repository:
from infinigen.tools.dataset_loader import get_infinigen_dataset
dataset = get_infinigen_dataset("outputs/my_download", data_types=["Image_png", "Depth_npy"])
print(len(dataset))
print(dataset[0].keys())
Note: dataset_loader.py is designed to be separable from the main infinigen codebase; you can copy/move this file into your own codebase, but you must also copy it's dependency suffixes.py
, or copy suffixes.py
's contents into dataset_loader.py
.
Please see GroundTruthAnnotations.md for documentation on the various available ground truth, and examples of how they can be used once loaded.