kopia lustrzana https://github.com/OpenDroneMap/WebODM
Updated rio-tiler to v2. Added custom NDVI indexes. Started develop of cropping plugin.
teslov
rodzic
af32e3aa29
commit
e84f1e194b
531
app/api/tiler.py
531
app/api/tiler.py
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@ -1,15 +1,19 @@
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import rasterio
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import json
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import numpy
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from rasterio.enums import ColorInterp
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from rasterio.enums import ColorInterp
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import urllib
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import urllib
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import os
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import os
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from django.http import HttpResponse
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from django.http import HttpResponse
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from rio_tiler.errors import TileOutsideBounds
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from rio_tiler.errors import TileOutsideBounds
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from rio_tiler.mercator import get_zooms
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from rio_tiler.utils import has_alpha_band, \
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from rio_tiler import main
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from rio_tiler.utils import array_to_image, get_colormap, expression, linear_rescale, _chunks, _apply_discrete_colormap, has_alpha_band, \
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non_alpha_indexes
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non_alpha_indexes
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from rio_tiler.utils import _stats as raster_stats
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from rio_tiler.models import ImageStatistics
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from rio_tiler.models import Metadata as RioMetadata
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from rio_tiler.profiles import img_profiles
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from rio_tiler.profiles import img_profiles
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from rio_tiler.colormap import cmap as colormap
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from rio_tiler.io import COGReader
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import numpy as np
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import numpy as np
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from app.raster_utils import export_raster_index
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from app.raster_utils import export_raster_index
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@ -23,13 +27,297 @@ from worker.tasks import export_raster_index
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ZOOM_EXTRA_LEVELS = 2
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ZOOM_EXTRA_LEVELS = 2
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colormap = colormap.register(
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{
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"discrete_ndvi": {
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0: [174, 0, 40, 255],
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1: [174, 0, 40, 255],
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2: [174, 0, 40, 255],
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3: [174, 0, 40, 255],
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4: [174, 0, 40, 255],
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5: [174, 0, 40, 255],
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6: [174, 0, 40, 255],
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7: [174, 0, 40, 255],
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8: [174, 0, 40, 255],
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9: [174, 0, 40, 255],
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10: [174, 0, 40, 255],
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11: [174, 0, 40, 255],
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12: [174, 0, 40, 255],
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13: [174, 0, 40, 255],
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14: [174, 0, 40, 255],
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15: [174, 0, 40, 255],
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16: [174, 0, 40, 255],
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17: [174, 0, 40, 255],
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18: [174, 0, 40, 255],
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19: [174, 0, 40, 255],
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20: [174, 0, 40, 255],
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21: [174, 0, 40, 255],
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22: [174, 0, 40, 255],
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23: [174, 0, 40, 255],
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24: [174, 0, 40, 255],
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25: [174, 0, 40, 255],
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26: [174, 0, 40, 255],
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27: [174, 0, 40, 255],
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28: [174, 0, 40, 255],
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29: [174, 0, 40, 255],
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30: [174, 0, 40, 255],
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31: [174, 0, 40, 255],
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32: [174, 0, 40, 255],
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33: [174, 0, 40, 255],
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34: [174, 0, 40, 255],
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35: [174, 0, 40, 255],
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36: [174, 0, 40, 255],
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37: [174, 0, 40, 255],
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38: [174, 0, 40, 255],
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39: [174, 0, 40, 255],
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40: [174, 0, 40, 255],
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41: [174, 0, 40, 255],
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42: [174, 0, 40, 255],
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43: [174, 0, 40, 255],
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44: [174, 0, 40, 255],
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45: [174, 0, 40, 255],
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46: [174, 0, 40, 255],
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47: [174, 0, 40, 255],
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48: [174, 0, 40, 255],
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49: [174, 0, 40, 255],
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50: [174, 0, 40, 255],
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51: [254, 142, 86, 255],
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52: [254, 142, 86, 255],
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53: [254, 142, 86, 255],
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54: [254, 142, 86, 255],
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55: [254, 142, 86, 255],
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56: [254, 142, 86, 255],
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57: [254, 142, 86, 255],
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58: [254, 142, 86, 255],
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59: [254, 142, 86, 255],
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60: [254, 142, 86, 255],
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61: [254, 142, 86, 255],
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62: [254, 142, 86, 255],
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63: [254, 142, 86, 255],
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64: [254, 142, 86, 255],
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65: [254, 142, 86, 255],
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66: [254, 142, 86, 255],
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67: [254, 142, 86, 255],
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68: [254, 142, 86, 255],
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69: [254, 142, 86, 255],
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70: [254, 142, 86, 255],
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71: [254, 142, 86, 255],
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72: [254, 142, 86, 255],
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73: [254, 142, 86, 255],
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74: [254, 142, 86, 255],
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75: [254, 142, 86, 255],
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76: [254, 142, 86, 255],
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77: [254, 142, 86, 255],
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78: [254, 142, 86, 255],
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79: [254, 142, 86, 255],
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80: [254, 142, 86, 255],
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81: [254, 142, 86, 255],
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82: [254, 142, 86, 255],
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83: [254, 142, 86, 255],
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84: [254, 142, 86, 255],
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85: [254, 142, 86, 255],
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86: [254, 142, 86, 255],
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87: [254, 142, 86, 255],
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88: [254, 142, 86, 255],
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89: [254, 142, 86, 255],
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90: [254, 142, 86, 255],
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91: [254, 142, 86, 255],
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92: [254, 142, 86, 255],
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93: [254, 142, 86, 255],
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94: [254, 142, 86, 255],
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95: [254, 142, 86, 255],
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96: [254, 142, 86, 255],
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97: [254, 142, 86, 255],
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98: [254, 142, 86, 255],
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99: [254, 142, 86, 255],
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100: [254, 142, 86, 255],
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101: [254, 142, 86, 255],
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102: [236, 246, 177, 255],
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103: [236, 246, 177, 255],
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104: [236, 246, 177, 255],
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105: [236, 246, 177, 255],
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106: [236, 246, 177, 255],
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107: [236, 246, 177, 255],
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108: [236, 246, 177, 255],
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109: [236, 246, 177, 255],
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110: [236, 246, 177, 255],
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111: [236, 246, 177, 255],
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112: [236, 246, 177, 255],
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113: [236, 246, 177, 255],
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114: [236, 246, 177, 255],
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115: [236, 246, 177, 255],
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116: [236, 246, 177, 255],
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117: [236, 246, 177, 255],
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118: [236, 246, 177, 255],
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119: [236, 246, 177, 255],
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120: [236, 246, 177, 255],
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121: [236, 246, 177, 255],
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122: [236, 246, 177, 255],
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123: [236, 246, 177, 255],
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124: [236, 246, 177, 255],
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125: [236, 246, 177, 255],
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126: [236, 246, 177, 255],
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127: [236, 246, 177, 255],
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128: [236, 246, 177, 255],
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129: [236, 246, 177, 255],
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130: [236, 246, 177, 255],
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131: [236, 246, 177, 255],
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132: [236, 246, 177, 255],
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133: [236, 246, 177, 255],
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134: [236, 246, 177, 255],
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135: [236, 246, 177, 255],
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136: [236, 246, 177, 255],
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137: [236, 246, 177, 255],
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138: [236, 246, 177, 255],
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139: [236, 246, 177, 255],
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140: [236, 246, 177, 255],
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141: [236, 246, 177, 255],
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142: [236, 246, 177, 255],
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143: [236, 246, 177, 255],
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144: [236, 246, 177, 255],
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145: [236, 246, 177, 255],
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146: [236, 246, 177, 255],
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147: [236, 246, 177, 255],
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148: [236, 246, 177, 255],
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149: [236, 246, 177, 255],
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150: [236, 246, 177, 255],
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151: [236, 246, 177, 255],
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152: [236, 246, 177, 255],
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153: [84, 188, 108, 255],
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154: [1, 126, 71, 255],
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155: [1, 126, 71, 255],
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156: [1, 126, 71, 255],
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157: [1, 126, 71, 255],
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158: [1, 126, 71, 255],
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159: [1, 126, 71, 255],
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160: [1, 126, 71, 255],
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161: [1, 126, 71, 255],
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162: [1, 126, 71, 255],
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163: [1, 126, 71, 255],
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164: [1, 126, 71, 255],
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165: [1, 126, 71, 255],
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166: [1, 126, 71, 255],
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167: [1, 126, 71, 255],
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168: [1, 126, 71, 255],
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169: [1, 126, 71, 255],
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170: [1, 126, 71, 255],
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171: [1, 126, 71, 255],
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172: [1, 126, 71, 255],
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173: [1, 126, 71, 255],
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174: [1, 126, 71, 255],
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175: [1, 126, 71, 255],
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176: [1, 126, 71, 255],
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177: [1, 126, 71, 255],
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178: [1, 126, 71, 255],
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179: [1, 126, 71, 255],
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180: [1, 126, 71, 255],
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181: [1, 126, 71, 255],
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182: [1, 126, 71, 255],
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183: [1, 126, 71, 255],
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184: [1, 126, 71, 255],
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185: [1, 126, 71, 255],
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186: [1, 126, 71, 255],
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187: [1, 126, 71, 255],
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188: [1, 126, 71, 255],
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189: [1, 126, 71, 255],
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190: [1, 126, 71, 255],
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191: [1, 126, 71, 255],
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192: [1, 126, 71, 255],
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193: [1, 126, 71, 255],
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194: [1, 126, 71, 255],
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195: [1, 126, 71, 255],
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196: [1, 126, 71, 255],
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197: [1, 126, 71, 255],
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198: [1, 126, 71, 255],
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199: [1, 126, 71, 255],
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200: [1, 126, 71, 255],
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201: [1, 126, 71, 255],
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202: [1, 126, 71, 255],
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203: [1, 126, 71, 255],
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204: [1, 126, 71, 255],
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205: [1, 126, 71, 255],
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206: [1, 126, 71, 255],
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207: [1, 126, 71, 255],
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208: [1, 126, 71, 255],
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209: [1, 126, 71, 255],
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210: [1, 126, 71, 255],
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211: [1, 126, 71, 255],
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212: [1, 126, 71, 255],
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213: [1, 126, 71, 255],
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214: [1, 126, 71, 255],
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215: [1, 126, 71, 255],
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216: [1, 126, 71, 255],
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217: [1, 126, 71, 255],
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218: [1, 126, 71, 255],
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219: [1, 126, 71, 255],
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220: [1, 126, 71, 255],
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221: [1, 126, 71, 255],
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222: [1, 126, 71, 255],
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223: [1, 126, 71, 255],
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224: [1, 126, 71, 255],
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225: [1, 126, 71, 255],
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226: [1, 126, 71, 255],
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227: [1, 126, 71, 255],
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228: [1, 126, 71, 255],
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229: [1, 126, 71, 255],
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230: [1, 126, 71, 255],
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231: [1, 126, 71, 255],
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232: [1, 126, 71, 255],
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233: [1, 126, 71, 255],
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234: [1, 126, 71, 255],
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235: [1, 126, 71, 255],
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236: [1, 126, 71, 255],
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237: [1, 126, 71, 255],
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238: [1, 126, 71, 255],
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239: [1, 126, 71, 255],
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240: [1, 126, 71, 255],
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241: [1, 126, 71, 255],
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242: [1, 126, 71, 255],
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243: [1, 126, 71, 255],
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244: [1, 126, 71, 255],
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245: [1, 126, 71, 255],
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246: [1, 126, 71, 255],
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247: [1, 126, 71, 255],
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248: [1, 126, 71, 255],
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249: [1, 126, 71, 255],
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250: [1, 126, 71, 255],
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251: [1, 126, 71, 255],
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252: [1, 126, 71, 255],
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253: [1, 126, 71, 255],
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254: [1, 126, 71, 255],
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255: [1, 126, 71, 255]
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}
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}
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)
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colormap = colormap.register({
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"better_discrete_ndvi": {
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0: [174, 0, 40, 255],
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17: [223, 45, 44, 255],
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34: [254, 109, 72, 255],
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51: [254, 199, 125, 255],
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68: [255, 223, 146, 255],
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85: [255, 239, 173, 255],
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102: [234, 248, 171, 255],
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119: [212, 240, 148, 255],
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136: [182, 227, 136, 255],
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153: [155, 216, 114, 255],
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170: [120, 202, 111, 255],
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187: [121, 200, 115, 255],
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204: [83, 189, 108, 255],
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221: [22, 170, 94, 255],
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238: [0, 151, 84, 255],
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255: [1, 126, 71, 255],
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}
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})
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def get_zoom_safe(src_dst):
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def get_zoom_safe(src_dst):
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minzoom, maxzoom = get_zooms(src_dst)
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minzoom, maxzoom = src_dst.spatial_info["minzoom"], src_dst.spatial_info["maxzoom"]
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if maxzoom < minzoom:
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if maxzoom < minzoom:
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maxzoom = minzoom
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maxzoom = minzoom
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return minzoom, maxzoom
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return minzoom, maxzoom
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def get_tile_url(task, tile_type, query_params):
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def get_tile_url(task, tile_type, query_params):
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url = '/api/projects/{}/tasks/{}/{}/tiles/{{z}}/{{x}}/{{y}}.png'.format(task.project.id, task.id, tile_type)
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url = '/api/projects/{}/tasks/{}/{}/tiles/{{z}}/{{x}}/{{y}}.png'.format(task.project.id, task.id, tile_type)
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params = {}
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params = {}
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@ -43,13 +331,13 @@ def get_tile_url(task, tile_type, query_params):
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return url
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return url
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def get_extent(task, tile_type):
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def get_extent(task, tile_type):
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extent_map = {
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extent_map = {
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'orthophoto': task.orthophoto_extent,
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'orthophoto': task.orthophoto_extent,
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'dsm': task.dsm_extent,
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'dsm': task.dsm_extent,
|
||||||
'dtm': task.dtm_extent,
|
'dtm': task.dtm_extent,
|
||||||
}
|
}
|
||||||
|
|
||||||
if not tile_type in extent_map:
|
if not tile_type in extent_map:
|
||||||
raise exceptions.NotFound()
|
raise exceptions.NotFound()
|
||||||
|
|
||||||
|
|
@ -60,47 +348,11 @@ def get_extent(task, tile_type):
|
||||||
|
|
||||||
return extent
|
return extent
|
||||||
|
|
||||||
|
|
||||||
def get_raster_path(task, tile_type):
|
def get_raster_path(task, tile_type):
|
||||||
return task.get_asset_download_path(tile_type + ".tif")
|
return task.get_asset_download_path(tile_type + ".tif")
|
||||||
|
|
||||||
|
|
||||||
def rescale_tile(tile, mask, rescale = None):
|
|
||||||
if rescale:
|
|
||||||
try:
|
|
||||||
rescale_arr = list(map(float, rescale.split(",")))
|
|
||||||
except ValueError:
|
|
||||||
raise exceptions.ValidationError("Invalid rescale value")
|
|
||||||
|
|
||||||
rescale_arr = list(_chunks(rescale_arr, 2))
|
|
||||||
if len(rescale_arr) != tile.shape[0]:
|
|
||||||
rescale_arr = ((rescale_arr[0]),) * tile.shape[0]
|
|
||||||
|
|
||||||
for bdx in range(tile.shape[0]):
|
|
||||||
if mask is not None:
|
|
||||||
tile[bdx] = np.where(
|
|
||||||
mask,
|
|
||||||
linear_rescale(
|
|
||||||
tile[bdx], in_range=rescale_arr[bdx], out_range=[0, 255]
|
|
||||||
),
|
|
||||||
0,
|
|
||||||
)
|
|
||||||
else:
|
|
||||||
tile[bdx] = linear_rescale(
|
|
||||||
tile[bdx], in_range=rescale_arr[bdx], out_range=[0, 255]
|
|
||||||
)
|
|
||||||
tile = tile.astype(np.uint8)
|
|
||||||
|
|
||||||
return tile, mask
|
|
||||||
|
|
||||||
|
|
||||||
def apply_colormap(tile, color_map = None):
|
|
||||||
if color_map is not None and isinstance(color_map, dict):
|
|
||||||
tile = _apply_discrete_colormap(tile, color_map)
|
|
||||||
elif color_map is not None:
|
|
||||||
tile = np.transpose(color_map[tile][0], [2, 0, 1]).astype(np.uint8)
|
|
||||||
|
|
||||||
return tile
|
|
||||||
|
|
||||||
class TileJson(TaskNestedView):
|
class TileJson(TaskNestedView):
|
||||||
def get(self, request, pk=None, project_pk=None, tile_type=""):
|
def get(self, request, pk=None, project_pk=None, tile_type=""):
|
||||||
"""
|
"""
|
||||||
|
|
@ -112,8 +364,8 @@ class TileJson(TaskNestedView):
|
||||||
if not os.path.isfile(raster_path):
|
if not os.path.isfile(raster_path):
|
||||||
raise exceptions.NotFound()
|
raise exceptions.NotFound()
|
||||||
|
|
||||||
with rasterio.open(raster_path) as src_dst:
|
with COGReader(raster_path) as src:
|
||||||
minzoom, maxzoom = get_zoom_safe(src_dst)
|
minzoom, maxzoom = get_zoom_safe(src)
|
||||||
|
|
||||||
return Response({
|
return Response({
|
||||||
'tilejson': '2.1.0',
|
'tilejson': '2.1.0',
|
||||||
|
|
@ -126,6 +378,7 @@ class TileJson(TaskNestedView):
|
||||||
'bounds': get_extent(task, tile_type).extent
|
'bounds': get_extent(task, tile_type).extent
|
||||||
})
|
})
|
||||||
|
|
||||||
|
|
||||||
class Bounds(TaskNestedView):
|
class Bounds(TaskNestedView):
|
||||||
def get(self, request, pk=None, project_pk=None, tile_type=""):
|
def get(self, request, pk=None, project_pk=None, tile_type=""):
|
||||||
"""
|
"""
|
||||||
|
|
@ -138,13 +391,13 @@ class Bounds(TaskNestedView):
|
||||||
'bounds': get_extent(task, tile_type).extent
|
'bounds': get_extent(task, tile_type).extent
|
||||||
})
|
})
|
||||||
|
|
||||||
|
|
||||||
class Metadata(TaskNestedView):
|
class Metadata(TaskNestedView):
|
||||||
def get(self, request, pk=None, project_pk=None, tile_type=""):
|
def get(self, request, pk=None, project_pk=None, tile_type=""):
|
||||||
"""
|
"""
|
||||||
Get the metadata for this tasks's asset type
|
Get the metadata for this tasks's asset type
|
||||||
"""
|
"""
|
||||||
task = self.get_and_check_task(request, pk)
|
task = self.get_and_check_task(request, pk)
|
||||||
|
|
||||||
formula = self.request.query_params.get('formula')
|
formula = self.request.query_params.get('formula')
|
||||||
bands = self.request.query_params.get('bands')
|
bands = self.request.query_params.get('bands')
|
||||||
|
|
||||||
|
|
@ -161,19 +414,34 @@ class Metadata(TaskNestedView):
|
||||||
|
|
||||||
if not os.path.isfile(raster_path):
|
if not os.path.isfile(raster_path):
|
||||||
raise exceptions.NotFound()
|
raise exceptions.NotFound()
|
||||||
|
|
||||||
try:
|
try:
|
||||||
with rasterio.open(raster_path, "r") as src:
|
with COGReader(raster_path) as src:
|
||||||
band_count = src.meta['count']
|
band_count = src.metadata()['count']
|
||||||
if has_alpha_band(src):
|
if has_alpha_band(src.dataset):
|
||||||
band_count -= 1
|
band_count -= 1
|
||||||
|
|
||||||
nodata = None
|
nodata = None
|
||||||
# Workaround for https://github.com/OpenDroneMap/WebODM/issues/894
|
# Workaround for https://github.com/OpenDroneMap/WebODM/issues/894
|
||||||
if tile_type == 'orthophoto':
|
if tile_type == 'orthophoto':
|
||||||
nodata = 0
|
nodata = 0
|
||||||
|
|
||||||
info = main.metadata(src, pmin=pmin, pmax=pmax, histogram_bins=255, histogram_range=hrange, expr=expr, nodata=nodata)
|
# info = src.metadata(pmin=pmin, pmax=pmax, histogram_bins=255, histogram_range=hrange, expr=expr,
|
||||||
|
# nodata=nodata)
|
||||||
|
histogram_options = {"bins": 255, "range": hrange}
|
||||||
|
metadata = src.metadata(pmin=pmin, pmax=pmax, hist_options=histogram_options, nodata=nodata)
|
||||||
|
if expr is not None:
|
||||||
|
data, mask = src.preview(expression=expr)
|
||||||
|
data = numpy.ma.array(data)
|
||||||
|
data.mask = mask == 0
|
||||||
|
expression_bloc = expr.lower().split(",")
|
||||||
|
stats = {
|
||||||
|
f"{expression_bloc[b]}": raster_stats(data[b], percentiles=(2, 98))
|
||||||
|
for b in range(data.shape[0])
|
||||||
|
}
|
||||||
|
stats = {b: ImageStatistics(**s) for b, s in stats.items()}
|
||||||
|
metadata = RioMetadata(statistics=stats, **src.info().dict())
|
||||||
|
print(metadata)
|
||||||
|
print(metadata.json())
|
||||||
|
info = json.loads(metadata.json())
|
||||||
except IndexError as e:
|
except IndexError as e:
|
||||||
# Caught when trying to get an invalid raster metadata
|
# Caught when trying to get an invalid raster metadata
|
||||||
raise exceptions.ValidationError("Cannot retrieve raster metadata: %s" % str(e))
|
raise exceptions.ValidationError("Cannot retrieve raster metadata: %s" % str(e))
|
||||||
|
|
@ -191,6 +459,9 @@ class Metadata(TaskNestedView):
|
||||||
"rdylgn": "RdYlGn",
|
"rdylgn": "RdYlGn",
|
||||||
"rdylgn_r": "RdYlGn (Reverse)",
|
"rdylgn_r": "RdYlGn (Reverse)",
|
||||||
"spectral": "Spectral",
|
"spectral": "Spectral",
|
||||||
|
"discrete_ndvi": "Contrast NDVI",
|
||||||
|
"better_discrete_ndvi": "Custom NDVI Index",
|
||||||
|
"rplumbo": "Rplumbo (Better NDVI)",
|
||||||
"spectral_r": "Spectral (Reverse)",
|
"spectral_r": "Spectral (Reverse)",
|
||||||
"pastel1": "Pastel",
|
"pastel1": "Pastel",
|
||||||
}
|
}
|
||||||
|
|
@ -200,7 +471,8 @@ class Metadata(TaskNestedView):
|
||||||
if tile_type in ['dsm', 'dtm']:
|
if tile_type in ['dsm', 'dtm']:
|
||||||
colormaps = ['jet', 'terrain', 'gist_earth', 'pastel1']
|
colormaps = ['jet', 'terrain', 'gist_earth', 'pastel1']
|
||||||
elif formula and bands:
|
elif formula and bands:
|
||||||
colormaps = ['rdylgn', 'spectral', 'rdylgn_r', 'spectral_r']
|
colormaps = ['rdylgn', 'spectral', 'rdylgn_r', 'spectral_r', 'rplumbo', 'discrete_ndvi',
|
||||||
|
'better_discrete_ndvi']
|
||||||
algorithms = *get_algorithm_list(band_count),
|
algorithms = *get_algorithm_list(band_count),
|
||||||
|
|
||||||
info['color_maps'] = []
|
info['color_maps'] = []
|
||||||
|
|
@ -211,13 +483,12 @@ class Metadata(TaskNestedView):
|
||||||
try:
|
try:
|
||||||
info['color_maps'].append({
|
info['color_maps'].append({
|
||||||
'key': cmap,
|
'key': cmap,
|
||||||
'color_map': get_colormap(cmap, format="gdal"),
|
'color_map': colormap.get(cmap).values(),
|
||||||
'label': cmap_labels.get(cmap, cmap)
|
'label': cmap_labels.get(cmap, cmap)
|
||||||
})
|
})
|
||||||
except FileNotFoundError:
|
except FileNotFoundError:
|
||||||
raise exceptions.ValidationError("Not a valid color_map value: %s" % cmap)
|
raise exceptions.ValidationError("Not a valid color_map value: %s" % cmap)
|
||||||
|
|
||||||
del info['address']
|
|
||||||
info['name'] = task.name
|
info['name'] = task.name
|
||||||
info['scheme'] = 'xyz'
|
info['scheme'] = 'xyz'
|
||||||
info['tiles'] = [get_tile_url(task, tile_type, self.request.query_params)]
|
info['tiles'] = [get_tile_url(task, tile_type, self.request.query_params)]
|
||||||
|
|
@ -226,41 +497,40 @@ class Metadata(TaskNestedView):
|
||||||
info['maxzoom'] = info['minzoom']
|
info['maxzoom'] = info['minzoom']
|
||||||
info['maxzoom'] += ZOOM_EXTRA_LEVELS
|
info['maxzoom'] += ZOOM_EXTRA_LEVELS
|
||||||
info['minzoom'] -= ZOOM_EXTRA_LEVELS
|
info['minzoom'] -= ZOOM_EXTRA_LEVELS
|
||||||
|
info['bounds'] = {'value': src.bounds, 'crs': src.dataset.crs}
|
||||||
return Response(info)
|
return Response(info)
|
||||||
|
|
||||||
|
|
||||||
def get_elevation_tiles(elevation, url, x, y, z, tilesize, nodata, resampling, padding):
|
def get_elevation_tiles(elevation, url, x, y, z, tilesize, nodata, resampling, padding):
|
||||||
tile = np.full((tilesize * 3, tilesize * 3), nodata, dtype=elevation.dtype)
|
tile = np.full((tilesize * 3, tilesize * 3), nodata, dtype=elevation.dtype)
|
||||||
|
with COGReader(url) as src:
|
||||||
|
try:
|
||||||
|
left, _ = src.tile(x - 1, y, z, indexes=1, tilesize=tilesize, nodata=nodata,
|
||||||
|
resampling_method=resampling, padding=padding)
|
||||||
|
tile[tilesize:tilesize * 2, 0:tilesize] = left
|
||||||
|
except TileOutsideBounds:
|
||||||
|
pass
|
||||||
|
|
||||||
try:
|
try:
|
||||||
left, _ = main.tile(url, x - 1, y, z, indexes=1, tilesize=tilesize, nodata=nodata,
|
right, _ = src.tile(x + 1, y, z, indexes=1, tilesize=tilesize, nodata=nodata,
|
||||||
resampling_method=resampling, tile_edge_padding=padding)
|
resampling_method=resampling, padding=padding)
|
||||||
tile[tilesize:tilesize*2,0:tilesize] = left
|
tile[tilesize:tilesize * 2, tilesize * 2:tilesize * 3] = right
|
||||||
except TileOutsideBounds:
|
except TileOutsideBounds:
|
||||||
pass
|
pass
|
||||||
|
try:
|
||||||
|
bottom, _ = src.tile(x, y + 1, z, indexes=1, tilesize=tilesize, nodata=nodata,
|
||||||
|
resampling_method=resampling, padding=padding)
|
||||||
|
tile[tilesize * 2:tilesize * 3, tilesize:tilesize * 2] = bottom
|
||||||
|
except TileOutsideBounds:
|
||||||
|
pass
|
||||||
|
try:
|
||||||
|
top, _ = src.tile(x, y - 1, z, indexes=1, tilesize=tilesize, nodata=nodata,
|
||||||
|
resampling_method=resampling, padding=padding)
|
||||||
|
tile[0:tilesize, tilesize:tilesize * 2] = top
|
||||||
|
except TileOutsideBounds:
|
||||||
|
pass
|
||||||
|
|
||||||
try:
|
tile[tilesize:tilesize * 2, tilesize:tilesize * 2] = elevation
|
||||||
right, _ = main.tile(url, x + 1, y, z, indexes=1, tilesize=tilesize, nodata=nodata,
|
|
||||||
resampling_method=resampling, tile_edge_padding=padding)
|
|
||||||
tile[tilesize:tilesize*2,tilesize*2:tilesize*3] = right
|
|
||||||
except TileOutsideBounds:
|
|
||||||
pass
|
|
||||||
|
|
||||||
try:
|
|
||||||
bottom, _ = main.tile(url, x, y + 1, z, indexes=1, tilesize=tilesize, nodata=nodata,
|
|
||||||
resampling_method=resampling, tile_edge_padding=padding)
|
|
||||||
tile[tilesize*2:tilesize*3,tilesize:tilesize*2] = bottom
|
|
||||||
except TileOutsideBounds:
|
|
||||||
pass
|
|
||||||
|
|
||||||
try:
|
|
||||||
top, _ = main.tile(url, x, y - 1, z, indexes=1, tilesize=tilesize, nodata=nodata,
|
|
||||||
resampling_method=resampling, tile_edge_padding=padding)
|
|
||||||
tile[0:tilesize,tilesize:tilesize*2] = top
|
|
||||||
except TileOutsideBounds:
|
|
||||||
pass
|
|
||||||
|
|
||||||
tile[tilesize:tilesize*2,tilesize:tilesize*2] = elevation
|
|
||||||
|
|
||||||
return tile
|
return tile
|
||||||
|
|
||||||
|
|
@ -315,67 +585,63 @@ class Tiles(TaskNestedView):
|
||||||
if nodata is not None:
|
if nodata is not None:
|
||||||
nodata = np.nan if nodata == "nan" else float(nodata)
|
nodata = np.nan if nodata == "nan" else float(nodata)
|
||||||
tilesize = scale * 256
|
tilesize = scale * 256
|
||||||
|
|
||||||
url = get_raster_path(task, tile_type)
|
url = get_raster_path(task, tile_type)
|
||||||
|
with COGReader(url) as src:
|
||||||
|
if not src.tile_exists(z, x, y):
|
||||||
|
raise exceptions.NotFound("Outside of bounds")
|
||||||
|
|
||||||
if not os.path.isfile(url):
|
if not os.path.isfile(url):
|
||||||
raise exceptions.NotFound()
|
raise exceptions.NotFound()
|
||||||
|
|
||||||
with rasterio.open(url) as src:
|
with COGReader(url) as src:
|
||||||
minzoom, maxzoom = get_zoom_safe(src)
|
minzoom, maxzoom = get_zoom_safe(src)
|
||||||
has_alpha = has_alpha_band(src)
|
has_alpha = has_alpha_band(src.dataset)
|
||||||
if z < minzoom - ZOOM_EXTRA_LEVELS or z > maxzoom + ZOOM_EXTRA_LEVELS:
|
if z < minzoom - ZOOM_EXTRA_LEVELS or z > maxzoom + ZOOM_EXTRA_LEVELS:
|
||||||
raise exceptions.NotFound()
|
raise exceptions.NotFound()
|
||||||
|
|
||||||
# Handle N-bands datasets for orthophotos (not plant health)
|
# Handle N-bands datasets for orthophotos (not plant health)
|
||||||
if tile_type == 'orthophoto' and expr is None:
|
if tile_type == 'orthophoto' and expr is None:
|
||||||
ci = src.colorinterp
|
ci = src.dataset.colorinterp
|
||||||
|
|
||||||
# More than 4 bands?
|
# More than 4 bands?
|
||||||
if len(ci) > 4:
|
if len(ci) > 4:
|
||||||
# Try to find RGBA band order
|
# Try to find RGBA band order
|
||||||
if ColorInterp.red in ci and \
|
if ColorInterp.red in ci and \
|
||||||
ColorInterp.green in ci and \
|
ColorInterp.green in ci and \
|
||||||
ColorInterp.blue in ci:
|
ColorInterp.blue in ci:
|
||||||
indexes = (ci.index(ColorInterp.red) + 1,
|
indexes = (ci.index(ColorInterp.red) + 1,
|
||||||
ci.index(ColorInterp.green) + 1,
|
ci.index(ColorInterp.green) + 1,
|
||||||
ci.index(ColorInterp.blue) + 1,)
|
ci.index(ColorInterp.blue) + 1,)
|
||||||
else:
|
else:
|
||||||
# Fallback to first three
|
# Fallback to first three
|
||||||
indexes = (1, 2, 3, )
|
indexes = (1, 2, 3,)
|
||||||
elif has_alpha:
|
elif has_alpha:
|
||||||
indexes = non_alpha_indexes(src)
|
indexes = non_alpha_indexes(src.dataset)
|
||||||
|
|
||||||
# Workaround for https://github.com/OpenDroneMap/WebODM/issues/894
|
# Workaround for https://github.com/OpenDroneMap/WebODM/issues/894
|
||||||
if nodata is None and tile_type =='orthophoto':
|
if nodata is None and tile_type == 'orthophoto':
|
||||||
nodata = 0
|
nodata = 0
|
||||||
|
|
||||||
resampling="nearest"
|
resampling = "nearest"
|
||||||
padding=0
|
padding = 0
|
||||||
if tile_type in ["dsm", "dtm"]:
|
if tile_type in ["dsm", "dtm"]:
|
||||||
resampling="bilinear"
|
resampling = "bilinear"
|
||||||
padding=16
|
padding = 16
|
||||||
|
|
||||||
try:
|
try:
|
||||||
if expr is not None:
|
with COGReader(url) as src:
|
||||||
tile, mask = expression(
|
if expr is not None:
|
||||||
url, x, y, z, expr=expr, tilesize=tilesize, nodata=nodata, tile_edge_padding=padding, resampling_method=resampling
|
tile = src.tile(x, y, z, expression=expr, tilesize=tilesize, nodata=nodata,
|
||||||
)
|
padding=padding,
|
||||||
else:
|
resampling_method=resampling)
|
||||||
tile, mask = main.tile(
|
else:
|
||||||
url, x, y, z, indexes=indexes, tilesize=tilesize, nodata=nodata, tile_edge_padding=padding, resampling_method=resampling
|
tile = src.tile(x, y, z, indexes=indexes, tilesize=tilesize, nodata=nodata,
|
||||||
)
|
padding=padding, resampling_method=resampling)
|
||||||
except TileOutsideBounds:
|
except TileOutsideBounds:
|
||||||
raise exceptions.NotFound("Outside of bounds")
|
raise exceptions.NotFound("Outside of bounds")
|
||||||
|
|
||||||
if color_map:
|
if color_map:
|
||||||
try:
|
try:
|
||||||
color_map = get_colormap(color_map, format="gdal")
|
colormap.get(color_map)
|
||||||
except FileNotFoundError:
|
except FileNotFoundError:
|
||||||
raise exceptions.ValidationError("Not a valid color_map value")
|
raise exceptions.ValidationError("Not a valid color_map value")
|
||||||
|
|
||||||
intensity = None
|
intensity = None
|
||||||
|
|
||||||
if hillshade is not None:
|
if hillshade is not None:
|
||||||
try:
|
try:
|
||||||
hillshade = float(hillshade)
|
hillshade = float(hillshade)
|
||||||
|
|
@ -385,7 +651,8 @@ class Tiles(TaskNestedView):
|
||||||
raise exceptions.ValidationError("Invalid hillshade value")
|
raise exceptions.ValidationError("Invalid hillshade value")
|
||||||
|
|
||||||
if tile.shape[0] != 1:
|
if tile.shape[0] != 1:
|
||||||
raise exceptions.ValidationError("Cannot compute hillshade of non-elevation raster (multiple bands found)")
|
raise exceptions.ValidationError(
|
||||||
|
"Cannot compute hillshade of non-elevation raster (multiple bands found)")
|
||||||
|
|
||||||
delta_scale = (maxzoom + ZOOM_EXTRA_LEVELS + 1 - z) * 4
|
delta_scale = (maxzoom + ZOOM_EXTRA_LEVELS + 1 - z) * 4
|
||||||
dx = src.meta["transform"][0] * delta_scale
|
dx = src.meta["transform"][0] * delta_scale
|
||||||
|
|
@ -397,26 +664,34 @@ class Tiles(TaskNestedView):
|
||||||
# requires neighbor tiles to be rendered seamlessly
|
# requires neighbor tiles to be rendered seamlessly
|
||||||
elevation = get_elevation_tiles(tile[0], url, x, y, z, tilesize, nodata, resampling, padding)
|
elevation = get_elevation_tiles(tile[0], url, x, y, z, tilesize, nodata, resampling, padding)
|
||||||
intensity = ls.hillshade(elevation, dx=dx, dy=dy, vert_exag=hillshade)
|
intensity = ls.hillshade(elevation, dx=dx, dy=dy, vert_exag=hillshade)
|
||||||
intensity = intensity[tilesize:tilesize*2,tilesize:tilesize*2]
|
intensity = intensity[tilesize:tilesize * 2, tilesize:tilesize * 2]
|
||||||
|
|
||||||
|
|
||||||
rgb, rmask = rescale_tile(tile, mask, rescale=rescale)
|
|
||||||
rgb = apply_colormap(rgb, color_map)
|
|
||||||
|
|
||||||
if intensity is not None:
|
if intensity is not None:
|
||||||
# Quick check
|
# Quick check
|
||||||
if rgb.shape[0] != 3:
|
if tile.data.shape[0] != 3:
|
||||||
raise exceptions.ValidationError("Cannot process tile: intensity image provided, but no RGB data was computed.")
|
raise exceptions.ValidationError(
|
||||||
|
"Cannot process tile: intensity image provided, but no RGB data was computed.")
|
||||||
|
|
||||||
intensity = intensity * 255.0
|
intensity = intensity * 255.0
|
||||||
rgb = hsv_blend(rgb, intensity)
|
rgb = hsv_blend(tile.data, intensity)
|
||||||
|
|
||||||
options = img_profiles.get(driver, {})
|
options = img_profiles.get(driver, {})
|
||||||
|
rescale_arr = tuple(map(float, rescale.split(",")))
|
||||||
|
if color_map is not None and isinstance(color_map, dict):
|
||||||
|
return HttpResponse(
|
||||||
|
tile.post_process(in_range=(rescale_arr,)).render(img_format=driver, colormap=color_map, **options),
|
||||||
|
content_type="image/{}".format(ext)
|
||||||
|
)
|
||||||
|
elif color_map is not None:
|
||||||
|
return HttpResponse(
|
||||||
|
tile.post_process(in_range=(rescale_arr,)).render(img_format=driver, colormap=colormap.get(color_map),
|
||||||
|
**options),
|
||||||
|
content_type="image/{}".format(ext)
|
||||||
|
)
|
||||||
return HttpResponse(
|
return HttpResponse(
|
||||||
array_to_image(rgb, rmask, img_format=driver, **options),
|
tile.post_process(in_range=(rescale_arr,)).render(img_format=driver, **options),
|
||||||
content_type="image/{}".format(ext)
|
content_type="image/{}".format(ext)
|
||||||
)
|
)
|
||||||
|
|
||||||
|
|
||||||
class Export(TaskNestedView):
|
class Export(TaskNestedView):
|
||||||
def post(self, request, pk=None, project_pk=None):
|
def post(self, request, pk=None, project_pk=None):
|
||||||
"""
|
"""
|
||||||
|
|
@ -452,4 +727,4 @@ class Export(TaskNestedView):
|
||||||
raise exceptions.NotFound()
|
raise exceptions.NotFound()
|
||||||
|
|
||||||
celery_task_id = export_raster_index.delay(url, expr).task_id
|
celery_task_id = export_raster_index.delay(url, expr).task_id
|
||||||
return Response({'celery_task_id': celery_task_id})
|
return Response({'celery_task_id': celery_task_id})
|
||||||
|
|
|
||||||
|
|
@ -20,7 +20,7 @@ djangorestframework==3.9.1
|
||||||
djangorestframework-jwt==1.9.0
|
djangorestframework-jwt==1.9.0
|
||||||
drf-nested-routers==0.11.1
|
drf-nested-routers==0.11.1
|
||||||
funcsigs==1.0.2
|
funcsigs==1.0.2
|
||||||
futures==3.0.5
|
futures==3.1.1
|
||||||
geojson==2.3.0
|
geojson==2.3.0
|
||||||
gunicorn==19.7.1
|
gunicorn==19.7.1
|
||||||
itypes==1.1.0
|
itypes==1.1.0
|
||||||
|
|
@ -32,10 +32,10 @@ openapi-codec==1.1.7
|
||||||
packaging==16.8
|
packaging==16.8
|
||||||
piexif==1.0.13
|
piexif==1.0.13
|
||||||
pilkit==2.0
|
pilkit==2.0
|
||||||
Pillow==6.2.2
|
Pillow==8.3.2
|
||||||
pip-autoremove==0.9.0
|
pip-autoremove==0.9.0
|
||||||
psycopg2==2.8.4
|
psycopg2==2.8.6
|
||||||
psycopg2-binary==2.8.4
|
psycopg2-binary==2.8.6
|
||||||
PyJWT==1.5.3
|
PyJWT==1.5.3
|
||||||
pyodm==1.5.6
|
pyodm==1.5.6
|
||||||
pyparsing==2.1.10
|
pyparsing==2.1.10
|
||||||
|
|
@ -53,13 +53,13 @@ tzlocal==1.3
|
||||||
uritemplate==3.0.0
|
uritemplate==3.0.0
|
||||||
vine==1.3.0
|
vine==1.3.0
|
||||||
webcolors==1.5
|
webcolors==1.5
|
||||||
-e git://github.com/OpenDroneMap/rio-tiler.git#egg=rio-tiler
|
rio-tiler==2.1.2
|
||||||
rio-color==1.0.0
|
rio-color==1.0.4
|
||||||
rio-cogeo==1.1.8
|
rio-cogeo==2.3.1
|
||||||
rasterio==1.1.5 ; sys_platform == 'linux' or sys_platform == 'darwin'
|
rasterio==1.2.8
|
||||||
https://download.lfd.uci.edu/pythonlibs/s2jqpv5t/rasterio-1.1.3-cp37-cp37m-win_amd64.whl ; sys_platform == "win32"
|
|
||||||
https://download.lfd.uci.edu/pythonlibs/s2jqpv5t/GDAL-3.0.4-cp37-cp37m-win_amd64.whl ; sys_platform == "win32"
|
|
||||||
Shapely==1.7.0 ; sys_platform == "win32"
|
Shapely==1.7.0 ; sys_platform == "win32"
|
||||||
eventlet==0.25.1 ; sys_platform == "win32"
|
eventlet==0.25.1 ; sys_platform == "win32"
|
||||||
pyopenssl==19.1.0 ; sys_platform == "win32"
|
pyopenssl==19.1.0 ; sys_platform == "win32"
|
||||||
numpy==1.21.1
|
numpy==1.21.1
|
||||||
|
urllib3~=1.24.1
|
||||||
|
numexpr~=2.7.3
|
||||||
Ładowanie…
Reference in New Issue