Source code for torchgeo.datasets.naip
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""National Agriculture Imagery Program (NAIP) dataset."""
from typing import Any, Dict, Optional
import matplotlib.pyplot as plt
from .geo import RasterDataset
[docs]class NAIP(RasterDataset):
"""National Agriculture Imagery Program (NAIP) dataset.
The `National Agriculture Imagery Program (NAIP)
<https://catalog.data.gov/dataset/national-agriculture-imagery-program-naip>`_
acquires aerial imagery during the agricultural growing seasons in the continental
U.S. A primary goal of the NAIP program is to make digital ortho photography
available to governmental agencies and the public within a year of acquisition.
NAIP is administered by the USDA's Farm Service Agency (FSA) through the Aerial
Photography Field Office in Salt Lake City. This "leaf-on" imagery is used as a base
layer for GIS programs in FSA's County Service Centers, and is used to maintain the
Common Land Unit (CLU) boundaries.
If you use this dataset in your research, please cite it using the following format:
* https://www.fisheries.noaa.gov/inport/item/49508/citation
"""
# https://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs141p2_015644.pdf
# https://planetarycomputer.microsoft.com/dataset/naip#Storage-Documentation
filename_glob = "m_*.*"
filename_regex = r"""
^m
_(?P<quadrangle>\d+)
_(?P<quarter_quad>[a-z]+)
_(?P<utm_zone>\d+)
_(?P<resolution>\d+)
_(?P<date>\d+)
(?:_(?P<processing_date>\d+))?
\..*$
"""
# Plotting
all_bands = ["R", "G", "B", "NIR"]
rgb_bands = ["R", "G", "B"]
[docs] def plot(
self,
sample: Dict[str, Any],
show_titles: bool = True,
suptitle: Optional[str] = None,
) -> plt.Figure:
"""Plot a sample from the dataset.
Args:
sample: a sample returned by :meth:`RasterDataset.__getitem__`
show_titles: flag indicating whether to show titles above each panel
suptitle: optional string to use as a suptitle
Returns:
a matplotlib Figure with the rendered sample
.. versionchanged:: 0.3
Method now takes a sample dict, not a Tensor. Additionally, possible to
show subplot titles and/or use a custom suptitle.
"""
image = sample["image"][0:3, :, :].permute(1, 2, 0)
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(4, 4))
ax.imshow(image)
ax.axis("off")
if show_titles:
ax.set_title("Image")
if suptitle is not None:
plt.suptitle(suptitle)
return fig