Datasets:
Merge branch 'main' of https://huggingface.co/datasets/MITLL/LADI-v2-dataset
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README.md
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@@ -83,15 +83,31 @@ A single example in the v2a dataset looks like this:
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Examples in the v1 datasets are analogous, with classes drawn from their respective tasks (infrastructure and damage).
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## Using the Dataset
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###
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```python
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from datasets import load_dataset
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ds = load_dataset("MITLL/LADI-v2-dataset", "v2a_resized",
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```
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You can browse the bucket here: [https://ladi.s3.amazonaws.com/index.html](https://ladi.s3.amazonaws.com/index.html). Note that the `v2_resized` dataset is the same as the `v2` dataset, but with lower-resolution images (1800x1200 px). We expect that these images are still more than large enough to support most tasks, and encourage you to use the v2_resized and v2a_resized datasets when possible as the download is about 45x smaller. We try not to download images you don't need, so this will only fetch the v2_resized images, leaving v1 and v2 alone.
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from datasets import load_dataset
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ds = load_dataset("MITLL/LADI-v2-dataset", "v2a_resized",
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trust_remote_code=True)
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```
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Examples in the v1 datasets are analogous, with classes drawn from their respective tasks (infrastructure and damage).
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## Using the Dataset
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### Default Configuration
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The `main` branch of the dataset will load the `v2a` label set with images resized to fit within 1800x1200. For most use cases, this should be sufficient.
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```python
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from datasets import load_dataset
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ds = load_dataset("MITLL/LADI-v2-dataset")
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```
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### Advanced usage
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If you need access to the full resolution images, the v2 label set, or the v1 dataset, you should load from the `script` revision.
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This will use a custom dataset loader script, which will require you to set `trust_remote_code=True`.
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The available configurations for the script are: `v2`, `v2a`, `v2_resized`, `v2a_resized`, `v1_damage`, `v1_infra`.
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You can download the dataset by loading it with `download_ladi=True`, which fetches the compressed data from an s3 bucket and extracts it into your filesystem at `base_dir`:
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```python
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from datasets import load_dataset
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ds = load_dataset("MITLL/LADI-v2-dataset", "v2a_resized",
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revision="script",
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streaming=True,
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download_ladi=True,
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base_dir='./ladi_dataset',
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trust_remote_code=True)
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```
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You can browse the bucket here: [https://ladi.s3.amazonaws.com/index.html](https://ladi.s3.amazonaws.com/index.html). Note that the `v2_resized` dataset is the same as the `v2` dataset, but with lower-resolution images (1800x1200 px). We expect that these images are still more than large enough to support most tasks, and encourage you to use the v2_resized and v2a_resized datasets when possible as the download is about 45x smaller. We try not to download images you don't need, so this will only fetch the v2_resized images, leaving v1 and v2 alone.
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from datasets import load_dataset
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ds = load_dataset("MITLL/LADI-v2-dataset", "v2a_resized",
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revision="script",
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streaming=True,
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base_dir='./ladi_dataset',
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trust_remote_code=True)
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```
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