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--- |
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license: cc-by-4.0 |
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pretty_name: Ground-based Imaging data |
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tags: |
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- astronomy |
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- compression |
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- images |
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--- |
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# GBI-16-2D Dataset |
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SGBI-16-2D is a dataset which is part of the AstroCompress project. It contains data assembled from the Keck Telescope. <TODO>Describe data format</TODO> |
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# Usage |
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You first need to install the `datasets` and `astropy` packages: |
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```bash |
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pip install datasets astropy |
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``` |
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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. |
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## Local Use (RECOMMENDED) |
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You can clone this repo and use directly without connecting to hf: |
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```bash |
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git clone https://huggingface.co/datasets/AstroCompress/GBI-16-2D |
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``` |
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```bash |
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git lfs pull |
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``` |
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Then `cd SBI-16-3D` and start python like: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("./GBI-16-2D.py", "tiny", data_dir="./data/", writer_batch_size=1, trust_remote_code=True) |
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ds = dataset.with_format("np") |
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``` |
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Now you should be able to use the `ds` variable like: |
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```python |
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ds["test"][0]["image"].shape # -> (TBD) |
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``` |
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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. |
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## Use from Huggingface Directly |
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This method may only be an option when trying to access the "tiny" version of the dataset. |
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To directly use from this data from Huggingface, you'll want to log in on the command line before starting python: |
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```bash |
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huggingface-cli login |
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``` |
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or |
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``` |
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import huggingface_hub |
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huggingface_hub.login(token=token) |
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``` |
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Then in your python script: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("AstroCompress/GBI-16-2D", "tiny", writer_batch_size=1, trust_remote_code=True) |
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ds = dataset.with_format("np") |
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``` |
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## Demo Colab Notebook |
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We provide a demo collab notebook to get started on using the dataset [here](https://colab.research.google.com/drive/1SuFBPZiYZg9LH4pqypc_v8Sp99lShJqZ?usp=sharing). |
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## Utils scripts |
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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`. |
