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--- |
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pretty_name: FranceCrops |
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license: cc-by-sa-4.0 |
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tags: |
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- earth-observation |
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- remote-sensing |
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- agriculture |
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- timeseries |
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- geospatial |
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task_categories: |
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- image-classification |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Dataset Card for FranceCrops |
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## Dataset Summary |
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FranceCrops is a satellite imagery time series dataset for crop classification in France. |
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Each sample in the dataset consists of: |
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- **Input Features (`x`)**: 3D arrays of shape (100, 60, 12) in float16: |
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- 100: number of timeseries sampled within an agricultural field |
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- 60: temporal dimension (measurements every 5 days from 01/02/2022 to 30/11/2022) |
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- 12: spectral bands from Sentinel-2 satellite |
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- **Labels (`y`)**: Integer class labels (int16), one of 20 crop types |
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## Splits |
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π§ Work in Progress π§ |
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- `train`: 20,000 samples (~3.4GB) |
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## Usage |
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```python |
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from datasets import load_dataset |
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# Load the dataset |
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dataset = load_dataset("saget-antoine/francecrops", split="train") |
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# Example of accessing a single sample |
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sample = dataset[0] |
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x = sample["x"] # Get the input features |
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y = sample["y"] # Get the label |
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``` |
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Typical usage with PyTorch: |
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```python |
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import torch |
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from torch.utils.data import DataLoader |
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from datasets import load_dataset |
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dataset = load_dataset("saget-antoine/francecrops", split="train").with_format("torch", columns=["x", "y"], dtype=torch.float16) |
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train_loader = DataLoader(dataset, batch_size=1024, shuffle=True, num_workers=8) |
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``` |
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## Dataset Creation |
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### Source Data |
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π§ Work in Progress π§ |
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- Features: Sentinel-2 L2A satellite imagery extracted using GEE |
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- Labels: Crop type classification from the 2022French Registre Parcellaire Graphique (RPG) |
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### Preprocessing |
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π§ Work in Progress π§ |
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- Remove clouds, shadows, and missing data time steps |
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- Temporal alignment |
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- Temporal interpolation when missing |
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## License |
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Creative Commons Attribution-ShareAlike 4.0 International (CC-BY-SA-4.0) |
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