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Updated ChesapeakeCVPR to use NLCD colormap #1690

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merged 10 commits into from
Jan 20, 2024
Merged

Updated ChesapeakeCVPR to use NLCD colormap #1690

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625a7a9
Updated ChesapeakeCVPR to use NLCD colormap
alhridoy Oct 22, 2023
ca1b6d7
Reused NLCD colormap in ChesapeakeCVPR dataset
alhridoy Nov 14, 2023
70dd625
Updated ChesapeakeCVPR to use NLCD colormap
alhridoy Nov 15, 2023
3b7570c
Merge branch 'main' into ncld-colormap
alhridoy Nov 15, 2023
770b214
Update chesapeake.py
alhridoy Nov 15, 2023
f256b32
updated as suggested
alhridoy Jan 16, 2024
b8b0a2d
updated as suggested
alhridoy Jan 16, 2024
74287b2
Fixed NLCD colors
alhridoy Jan 17, 2024
a928867
Updated as suggested
alhridoy Jan 17, 2024
de54b15
removed nlcd_cmap attribute from ChesapeakeCVPR class
alhridoy Jan 20, 2024
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12 changes: 3 additions & 9 deletions torchgeo/datasets/chesapeake.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@
from matplotlib.figure import Figure
from rasterio.crs import CRS
from torch import Tensor

from .nlcd import NLCD
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from .geo import GeoDataset, RasterDataset
from .utils import BoundingBox, download_url, extract_archive

Expand Down Expand Up @@ -121,7 +121,6 @@ def __init__(
self.paths = paths
self.download = download
self.checksum = checksum

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self._verify()

colors = []
Expand Down Expand Up @@ -574,7 +573,7 @@ def __init__(
self.cache = cache
self.download = download
self.checksum = checksum

self.cmap = NLCD.cmap
self._verify()

super().__init__(transforms)
Expand All @@ -584,11 +583,6 @@ def __init__(
lc_colors = lc_colors[:, :3] / 255
self._lc_cmap = ListedColormap(lc_colors)

nlcd_colors = np.zeros((max(self.nlcd_cmap.keys()) + 1, 4))
nlcd_colors[list(self.nlcd_cmap.keys())] = list(self.nlcd_cmap.values())
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nlcd_colors = nlcd_colors[:, :3] / 255
self._nlcd_cmap = ListedColormap(nlcd_colors)

# Add all tiles into the index in epsg:3857 based on the included geojson
mint: float = 0
maxt: float = sys.maxsize
Expand Down Expand Up @@ -793,7 +787,7 @@ def plot(
img = mask[:, :, 0]
mask = mask[:, :, 1:]
axs[i].imshow(
img, vmin=0, vmax=95, cmap=self._nlcd_cmap, interpolation="none"
img, vmin=0, vmax=95, cmap=self.cmap, interpolation="none"
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)
axs[i].axis("off")
elif layer == "lc":
Expand Down