Rgb

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import hvplot.xarray  # noqa

rgb can be used to display images that are distributed as three separate “channels” or “bands”.

from hvplot.sample_data import landuse

da = landuse(landuse='airplane', id=90).read()
da

<xarray.DataArray (y: 256, x: 256, channel: 3)>
array([[[123, 113, 106],
        [120, 110, 103],
        [119, 107, 103],
        ...,
        [172, 160, 148],
        [174, 162, 150],
        [174, 163, 152]],

       [[124, 114, 107],
        [124, 112, 106],
        [120, 107, 104],
        ...,
        [171, 159, 147],
        [172, 161, 149],
        [173, 162, 151]],

       [[118, 109, 104],
        [114, 104,  98],
        [114, 103,  98],
        ...,
...
        ...,
        [ 91,  77,  62],
        [ 92,  75,  64],
        [ 91,  75,  66]],

       [[164, 156, 148],
        [172, 165, 155],
        [174, 167, 156],
        ...,
        [ 89,  74,  61],
        [ 90,  72,  61],
        [ 89,  71,  61]],

       [[164, 157, 148],
        [158, 151, 141],
        [156, 150, 139],
        ...,
        [ 88,  74,  60],
        [ 88,  69,  58],
        [ 89,  70,  58]]], dtype=uint8)
Coordinates:
  * y        (y) int64 0 1 2 3 4 5 6 7 8 ... 247 248 249 250 251 252 253 254 255
  * x        (x) int64 0 1 2 3 4 5 6 7 8 ... 247 248 249 250 251 252 253 254 255
  * channel  (channel) int64 0 1 2

xarray.DataArray

• y: 256
• x: 256
• channel: 3

• 123 113 106 120 110 103 119 107 103 119 ... 88 74 60 88 69 58 89 70 58

  array([[[123, 113, 106],
          [120, 110, 103],
          [119, 107, 103],
          ...,
          [172, 160, 148],
          [174, 162, 150],
          [174, 163, 152]],
  
         [[124, 114, 107],
          [124, 112, 106],
          [120, 107, 104],
          ...,
          [171, 159, 147],
          [172, 161, 149],
          [173, 162, 151]],
  
         [[118, 109, 104],
          [114, 104,  98],
          [114, 103,  98],
          ...,
  ...
          ...,
          [ 91,  77,  62],
          [ 92,  75,  64],
          [ 91,  75,  66]],
  
         [[164, 156, 148],
          [172, 165, 155],
          [174, 167, 156],
          ...,
          [ 89,  74,  61],
          [ 90,  72,  61],
          [ 89,  71,  61]],
  
         [[164, 157, 148],
          [158, 151, 141],
          [156, 150, 139],
          ...,
          [ 88,  74,  60],
          [ 88,  69,  58],
          [ 89,  70,  58]]], dtype=uint8)

• Coordinates: (3)
  • y
    (y)
    int64
    0 1 2 3 4 5 ... 251 252 253 254 255

    array([  0,   1,   2, ..., 253, 254, 255])

  • x
    (x)
    int64
    0 1 2 3 4 5 ... 251 252 253 254 255

    array([  0,   1,   2, ..., 253, 254, 255])

  • channel
    (channel)
    int64
    0 1 2

    array([0, 1, 2])

• Indexes: (3)
  • y
    PandasIndex

    PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
           ...
           246, 247, 248, 249, 250, 251, 252, 253, 254, 255],
          dtype='int64', name='y', length=256))

  • x
    PandasIndex

    PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
           ...
           246, 247, 248, 249, 250, 251, 252, 253, 254, 255],
          dtype='int64', name='x', length=256))

  • channel
    PandasIndex

    PandasIndex(Index([0, 1, 2], dtype='int64', name='channel'))

• Attributes: (0)

Since rgb images are stored starting at the top left pixel, we should start there when plotting to make sure that we get the picture in the correct orientation. To accomplish this, we use flip_yaxis.

da.hvplot.rgb(x='x', y='y', bands='channel', data_aspect=1, flip_yaxis=True, xaxis=False, yaxis=None)

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Download this notebook from GitHub (right-click to download).