--- license: cc-by-4.0 pretty_name: Ground-based Imaging data tags: - astronomy - compression - images --- # GBI-16-2D Dataset SGBI-16-2D is a dataset which is part of the AstroCompress project. It contains data assembled from the Keck Telescope. Describe data format # Usage You first need to install the `datasets` and `astropy` packages: ```bash pip install datasets astropy ``` There are two datasets: `tiny` and `full`, each with `train` and `test` splits. The `tiny` dataset has 2 2D images in the `train` and 1 in the `test`. The `full` dataset contains all the images in the `data/` directory. ## Local Use (RECOMMENDED) Alternatively, you can clone this repo and use directly without connecting to hf: ```bash git clone https://huggingface.co/datasets/AstroCompress/GBI-16-2D ``` ```bash git lfs pull ``` Then `cd SBI-16-3D` and start python like: ```python from datasets import load_dataset dataset = load_dataset("./GBI-16-2D.py", "tiny", data_dir="./data/", writer_batch_size=1, trust_remote_code=True) ds = dataset.with_format("np") ``` Now you should be able to use the `ds` variable like: ```python ds["test"][0]["image"].shape # -> (TBD) ``` Note of course that it will take a long time to download and convert the images in the local cache for the `full` dataset. Afterward, the usage should be quick as the files are memory-mapped from disk. ## Use from Huggingface Directly To directly use from this data from Huggingface, you'll want to log in on the command line before starting python: ```bash huggingface-cli login ``` or ``` import huggingface_hub huggingface_hub.login(token=token) ``` Then in your python script: ```python from datasets import load_dataset dataset = load_dataset("AstroCompress/GBI-16-2D", "tiny", writer_batch_size=1, trust_remote_code=True) ds = dataset.with_format("np") ```