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saget-antoine/francecrops-float16

FranceCrops Float16 Dataset Memory-efficient version of the FranceCrops dataset stored in float16 format. Usage from datasets import load_dataset # Load dataset dataset = load_dataset("saget-antoine/francecrops-float16") # Load with specific format (recommended for training) # As float32 dataset = dataset.with_format('torch', dtype=torch.float32) # Or as float16 for memory efficiency dataset = dataset.with_format('torch', dtype=torch.float16) # Or as bfloat16… See the full description on the dataset page: https://huggingface.co/datasets/saget-antoine/francecrops-float16.

sourceHugging Faceupdated 2y agoView on Hugging Face

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Dataset Card

FranceCrops Float16 Dataset

Memory-efficient version of the FranceCrops dataset stored in float16 format.

Dataset Description

—Each sample contains Sentinel-2 time series data (shape: 100, 60, 12) and corresponding crop type labels
—Features stored in float16 format for reduced memory usage
—Labels stored as int16

Usage

python

from datasets import load_dataset

# Load dataset
dataset = load_dataset("saget-antoine/francecrops-float16")

# Load with specific format (recommended for training)
# As float32
dataset = dataset.with_format('torch', dtype=torch.float32)
# Or as float16 for memory efficiency
dataset = dataset.with_format('torch', dtype=torch.float16)
# Or as bfloat16 for TPU compatibility
dataset = dataset.with_format('torch', dtype=torch.bfloat16)

Memory Usage

Using float16 format reduces the memory footprint by approximately 50% compared to float32, while maintaining sufficient precision for most agricultural monitoring tasks.

Citation

If you use this dataset, please cite the original FranceCrops paper.