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Extracted colormaps from main code. Added as side util class

pull/1063/head
teslov 2021-10-03 18:32:51 +03:00
rodzic 92064410dc
commit 734b7ebd86
3 zmienionych plików z 53 dodań i 298 usunięć
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297
app/api/custom_colormaps.py
Wyświetl plik

@ -1,297 +0,0 @@
import matplotlib
import numpy
ndvi = matplotlib.colors.LinearSegmentedColormap.from_list(
'ndvi', [
'#AD0028',
'#C5142A',
'#E02D2C',
'#EF4C3A',
'#FE6C4A',
'#FF8D5A',
'#FFAB69',
'#FFC67D',
'#FFE093',
'#FFEFAB',
'#FDFEC2',
'#EAF7AC',
'#FDFEC2',
'#EAF7AC',
'#D5EF94',
'#B9E383',
'#9BD873',
'#B9E383',
'#9BD873',
'#77CA6F',
'#53BD6B',
'#14AA60',
'#009755',
'#007E47',
],
256,
)
x = numpy.linspace(0, 1, 256)
cmap_vals = ndvi(x)[:, :]
cmap_uint8 = (cmap_vals * 255).astype('uint8')
ndvi_dict = {idx: value.tolist() for idx, value in enumerate(cmap_uint8)}
custom_colormaps = [{"discrete_ndvi": {
0: [174, 0, 40, 255],
1: [174, 0, 40, 255],
2: [174, 0, 40, 255],
3: [174, 0, 40, 255],
4: [174, 0, 40, 255],
5: [174, 0, 40, 255],
6: [174, 0, 40, 255],
7: [174, 0, 40, 255],
8: [174, 0, 40, 255],
9: [174, 0, 40, 255],
10: [174, 0, 40, 255],
11: [174, 0, 40, 255],
12: [174, 0, 40, 255],
13: [174, 0, 40, 255],
14: [174, 0, 40, 255],
15: [174, 0, 40, 255],
16: [174, 0, 40, 255],
17: [174, 0, 40, 255],
18: [174, 0, 40, 255],
19: [174, 0, 40, 255],
20: [174, 0, 40, 255],
21: [174, 0, 40, 255],
22: [174, 0, 40, 255],
23: [174, 0, 40, 255],
24: [174, 0, 40, 255],
25: [174, 0, 40, 255],
26: [174, 0, 40, 255],
27: [174, 0, 40, 255],
28: [174, 0, 40, 255],
29: [174, 0, 40, 255],
30: [174, 0, 40, 255],
31: [174, 0, 40, 255],
32: [174, 0, 40, 255],
33: [174, 0, 40, 255],
34: [174, 0, 40, 255],
35: [174, 0, 40, 255],
36: [174, 0, 40, 255],
37: [174, 0, 40, 255],
38: [174, 0, 40, 255],
39: [174, 0, 40, 255],
40: [174, 0, 40, 255],
41: [174, 0, 40, 255],
42: [174, 0, 40, 255],
43: [174, 0, 40, 255],
44: [174, 0, 40, 255],
45: [174, 0, 40, 255],
46: [174, 0, 40, 255],
47: [174, 0, 40, 255],
48: [174, 0, 40, 255],
49: [174, 0, 40, 255],
50: [174, 0, 40, 255],
51: [254, 142, 86, 255],
52: [254, 142, 86, 255],
53: [254, 142, 86, 255],
54: [254, 142, 86, 255],
55: [254, 142, 86, 255],
56: [254, 142, 86, 255],
57: [254, 142, 86, 255],
58: [254, 142, 86, 255],
59: [254, 142, 86, 255],
60: [254, 142, 86, 255],
61: [254, 142, 86, 255],
62: [254, 142, 86, 255],
63: [254, 142, 86, 255],
64: [254, 142, 86, 255],
65: [254, 142, 86, 255],
66: [254, 142, 86, 255],
67: [254, 142, 86, 255],
68: [254, 142, 86, 255],
69: [254, 142, 86, 255],
70: [254, 142, 86, 255],
71: [254, 142, 86, 255],
72: [254, 142, 86, 255],
73: [254, 142, 86, 255],
74: [254, 142, 86, 255],
75: [254, 142, 86, 255],
76: [254, 142, 86, 255],
77: [254, 142, 86, 255],
78: [254, 142, 86, 255],
79: [254, 142, 86, 255],
80: [254, 142, 86, 255],
81: [254, 142, 86, 255],
82: [254, 142, 86, 255],
83: [254, 142, 86, 255],
84: [254, 142, 86, 255],
85: [254, 142, 86, 255],
86: [254, 142, 86, 255],
87: [254, 142, 86, 255],
88: [254, 142, 86, 255],
89: [254, 142, 86, 255],
90: [254, 142, 86, 255],
91: [254, 142, 86, 255],
92: [254, 142, 86, 255],
93: [254, 142, 86, 255],
94: [254, 142, 86, 255],
95: [254, 142, 86, 255],
96: [254, 142, 86, 255],
97: [254, 142, 86, 255],
98: [254, 142, 86, 255],
99: [254, 142, 86, 255],
100: [254, 142, 86, 255],
101: [254, 142, 86, 255],
102: [236, 246, 177, 255],
103: [236, 246, 177, 255],
104: [236, 246, 177, 255],
105: [236, 246, 177, 255],
106: [236, 246, 177, 255],
107: [236, 246, 177, 255],
108: [236, 246, 177, 255],
109: [236, 246, 177, 255],
110: [236, 246, 177, 255],
111: [236, 246, 177, 255],
112: [236, 246, 177, 255],
113: [236, 246, 177, 255],
114: [236, 246, 177, 255],
115: [236, 246, 177, 255],
116: [236, 246, 177, 255],
117: [236, 246, 177, 255],
118: [236, 246, 177, 255],
119: [236, 246, 177, 255],
120: [236, 246, 177, 255],
121: [236, 246, 177, 255],
122: [236, 246, 177, 255],
123: [236, 246, 177, 255],
124: [236, 246, 177, 255],
125: [236, 246, 177, 255],
126: [236, 246, 177, 255],
127: [236, 246, 177, 255],
128: [236, 246, 177, 255],
129: [236, 246, 177, 255],
130: [236, 246, 177, 255],
131: [236, 246, 177, 255],
132: [236, 246, 177, 255],
133: [236, 246, 177, 255],
134: [236, 246, 177, 255],
135: [236, 246, 177, 255],
136: [236, 246, 177, 255],
137: [236, 246, 177, 255],
138: [236, 246, 177, 255],
139: [236, 246, 177, 255],
140: [236, 246, 177, 255],
141: [236, 246, 177, 255],
142: [236, 246, 177, 255],
143: [236, 246, 177, 255],
144: [236, 246, 177, 255],
145: [236, 246, 177, 255],
146: [236, 246, 177, 255],
147: [236, 246, 177, 255],
148: [236, 246, 177, 255],
149: [236, 246, 177, 255],
150: [236, 246, 177, 255],
151: [236, 246, 177, 255],
152: [236, 246, 177, 255],
153: [84, 188, 108, 255],
154: [1, 126, 71, 255],
155: [1, 126, 71, 255],
156: [1, 126, 71, 255],
157: [1, 126, 71, 255],
158: [1, 126, 71, 255],
159: [1, 126, 71, 255],
160: [1, 126, 71, 255],
161: [1, 126, 71, 255],
162: [1, 126, 71, 255],
163: [1, 126, 71, 255],
164: [1, 126, 71, 255],
165: [1, 126, 71, 255],
166: [1, 126, 71, 255],
167: [1, 126, 71, 255],
168: [1, 126, 71, 255],
169: [1, 126, 71, 255],
170: [1, 126, 71, 255],
171: [1, 126, 71, 255],
172: [1, 126, 71, 255],
173: [1, 126, 71, 255],
174: [1, 126, 71, 255],
175: [1, 126, 71, 255],
176: [1, 126, 71, 255],
177: [1, 126, 71, 255],
178: [1, 126, 71, 255],
179: [1, 126, 71, 255],
180: [1, 126, 71, 255],
181: [1, 126, 71, 255],
182: [1, 126, 71, 255],
183: [1, 126, 71, 255],
184: [1, 126, 71, 255],
185: [1, 126, 71, 255],
186: [1, 126, 71, 255],
187: [1, 126, 71, 255],
188: [1, 126, 71, 255],
189: [1, 126, 71, 255],
190: [1, 126, 71, 255],
191: [1, 126, 71, 255],
192: [1, 126, 71, 255],
193: [1, 126, 71, 255],
194: [1, 126, 71, 255],
195: [1, 126, 71, 255],
196: [1, 126, 71, 255],
197: [1, 126, 71, 255],
198: [1, 126, 71, 255],
199: [1, 126, 71, 255],
200: [1, 126, 71, 255],
201: [1, 126, 71, 255],
202: [1, 126, 71, 255],
203: [1, 126, 71, 255],
204: [1, 126, 71, 255],
205: [1, 126, 71, 255],
206: [1, 126, 71, 255],
207: [1, 126, 71, 255],
208: [1, 126, 71, 255],
209: [1, 126, 71, 255],
210: [1, 126, 71, 255],
211: [1, 126, 71, 255],
212: [1, 126, 71, 255],
213: [1, 126, 71, 255],
214: [1, 126, 71, 255],
215: [1, 126, 71, 255],
216: [1, 126, 71, 255],
217: [1, 126, 71, 255],
218: [1, 126, 71, 255],
219: [1, 126, 71, 255],
220: [1, 126, 71, 255],
221: [1, 126, 71, 255],
222: [1, 126, 71, 255],
223: [1, 126, 71, 255],
224: [1, 126, 71, 255],
225: [1, 126, 71, 255],
226: [1, 126, 71, 255],
227: [1, 126, 71, 255],
228: [1, 126, 71, 255],
229: [1, 126, 71, 255],
230: [1, 126, 71, 255],
231: [1, 126, 71, 255],
232: [1, 126, 71, 255],
233: [1, 126, 71, 255],
234: [1, 126, 71, 255],
235: [1, 126, 71, 255],
236: [1, 126, 71, 255],
237: [1, 126, 71, 255],
238: [1, 126, 71, 255],
239: [1, 126, 71, 255],
240: [1, 126, 71, 255],
241: [1, 126, 71, 255],
242: [1, 126, 71, 255],
243: [1, 126, 71, 255],
244: [1, 126, 71, 255],
245: [1, 126, 71, 255],
246: [1, 126, 71, 255],
247: [1, 126, 71, 255],
248: [1, 126, 71, 255],
249: [1, 126, 71, 255],
250: [1, 126, 71, 255],
251: [1, 126, 71, 255],
252: [1, 126, 71, 255],
253: [1, 126, 71, 255],
254: [1, 126, 71, 255],
255: [1, 126, 71, 255]
}}, {"better_discrete_ndvi": ndvi_dict}]

52
app/api/custom_colormaps_helper.py 100644
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@ -0,0 +1,52 @@
import matplotlib
import numpy
def generate_discrete_color_map_from_list_of_hex(list_of_hex_colors):
colormap = matplotlib.colors.ListedColormap(list_of_hex_colors)
color_map_dict = extract_colormap_dict_from_arr(colormap)
return color_map_dict
def generate_linerar_segmented_color_map_from_list_of_hex(list_of_hex_colors, name_of_colormap="default_name", N=256):
colormap = matplotlib.colors.LinearSegmentedColormap.from_list(name_of_colormap, list_of_hex_colors, N)
color_map_dict = extract_colormap_dict_from_arr(colormap)
return color_map_dict
def extract_colormap_dict_from_arr(colormap):
x = numpy.linspace(0, 1, 256)
cmap_vals = colormap(x)[:, :]
cmap_uint8 = (cmap_vals * 255).astype('uint8')
ndvi_dict = {idx: value.tolist() for idx, value in enumerate(cmap_uint8)}
return ndvi_dict
ndvi_arr = [
'#AD0028',
'#C5142A',
'#E02D2C',
'#EF4C3A',
'#FE6C4A',
'#FF8D5A',
'#FFAB69',
'#FFC67D',
'#FFE093',
'#FFEFAB',
'#FDFEC2',
'#EAF7AC',
'#D5EF94',
'#B9E383',
'#9BD873',
'#77CA6F',
'#53BD6B',
'#14AA60',
'#009755',
'#007E47'
]
contrast_ndvi_arr = [
'#AD0028',
'#FFAB69',
'#FDFEC2',
'#77CA6F',
'#014729'
]
custom_colormaps = [
{"discrete_ndvi": generate_discrete_color_map_from_list_of_hex(contrast_ndvi_arr)},
{"better_discrete_ndvi": generate_discrete_color_map_from_list_of_hex(ndvi_arr)},
#add custom maps here
]

2
app/api/tiler.py
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@ -14,7 +14,7 @@ from rio_tiler.profiles import img_profiles
from rio_tiler.colormap import cmap as colormap from rio_tiler.colormap import cmap as colormap
from rio_tiler.io import COGReader from rio_tiler.io import COGReader
import numpy as np import numpy as np
from custom_colormaps import custom_colormaps from app.api.custom_colormaps_helper import custom_colormaps
from app.raster_utils import export_raster_index from app.raster_utils import export_raster_index
from .hsvblend import hsv_blend from .hsvblend import hsv_blend
from .hillshade import LightSource from .hillshade import LightSource