ReforesTree#
- class torchgeo.datasets.ReforesTree(root='data', transforms=None, download=False, checksum=False)[source]#
Bases:
NonGeoDatasetReforesTree dataset.
The ReforesTree dataset contains drone imagery that can be used for tree crown detection, tree species classification and Aboveground Biomass (AGB) estimation.
Dataset features:
100 high resolution RGB drone images at 2 cm/pixel of size 4,000 x 4,000 px
more than 4,600 tree crown box annotations
tree crown matched with field measurements of diameter at breast height (DBH), and computed AGB and carbon values
Dataset format:
images are three-channel pngs
annotations are csv file
Dataset Classes:
other
banana
cacao
citrus
fruit
timber
If you use this dataset in your research, please cite the following paper:
Added in version 0.3.
- __init__(root='data', transforms=None, download=False, checksum=False)[source]#
Initialize a new ReforesTree dataset instance.
- Parameters:
root (str | PathLike[str]) – root directory where dataset can be found
transforms (Callable[[dict[str, Any]], dict[str, Any]] | None) – a function/transform that takes input sample and its target as entry and returns a transformed version
download (bool) – if True, download dataset and store it in the root directory
checksum (bool) – if True, check the MD5 of the downloaded files (may be slow)
- Raises:
DatasetNotFoundError – If dataset is not found and download is False.
- __len__()[source]#
Return the number of data points in the dataset.
- Returns:
length of the dataset
- Return type: