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Error code: ConfigNamesError Exception: ImportError Message: To be able to use AnonAstroData/SBI-16-3D, you need to install the following dependency: astropy. Please install it using 'pip install astropy' for instance. Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response config_names = get_dataset_config_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names dataset_module = dataset_module_factory( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1914, in dataset_module_factory raise e1 from None File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1880, in dataset_module_factory return HubDatasetModuleFactoryWithScript( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1504, in get_module local_imports = _download_additional_modules( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 354, in _download_additional_modules raise ImportError( ImportError: To be able to use AnonAstroData/SBI-16-3D, you need to install the following dependency: astropy. Please install it using 'pip install astropy' for instance.
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
SBI-16-3D Dataset
SBI-16-3D is a dataset which is part of the AstroCompress project. It contains data assembled from the James Webb Space Telescope (JWST). Describe data format
Usage
You first need to install the datasets
and astropy
packages:
pip install datasets astropy
There are two datasets: tiny
and full
, each with train
and test
splits. The tiny
dataset has 2 4D images in the train
and 1 in the test
. The full
dataset contains all the images in the data/
directory.
Local Use (RECOMMENDED)
You can clone this repo and use directly without connecting to hf:
git clone https://huggingface.co/datasets/AnonAstroData/SBI-16-3D
git lfs pull
Then cd SBI-16-3D
and start python like:
from datasets import load_dataset
import numpy
dataset = load_dataset("./SBI-16-3D.py", "tiny", data_dir="./data/", writer_batch_size=1, trust_remote_code=True)
ds = dataset.with_format("np", dtype=numpy.uint16)
Now you should be able to use the ds
variable like:
ds["test"][0]["image"].shape # -> (5, 2048, 2048)
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
This method may only be an option when trying to access the "tiny" version of the dataset.
To directly use from this data from Huggingface, you'll want to log in on the command line before starting python:
huggingface-cli login
or
import huggingface_hub
huggingface_hub.login(token=token)
Then in your python script:
from datasets import load_dataset
import numpy
dataset = load_dataset("AstroCompress/SBI-16-3D", "tiny", writer_batch_size=1, trust_remote_code=True)
ds = dataset.with_format("np", columns=["image"], dtype=numpy.uint16)
# or torch
import torch
dst = dataset.with_format("torch", columns=["image"], dtype=torch.uint16)
# or pandas
dsp = dataset.with_format("pandas", columns=["image"], dtype=numpy.uint16)
Demo Colab Notebook
We provide a demo collab notebook to get started on using the dataset here.
Utils scripts
Note that utils scripts such as eval_baselines.py
must be run from the parent directory of utils
, i.e. python utils/eval_baselines.py
.
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