82 lines
3.3 KiB
Python
82 lines
3.3 KiB
Python
import os
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import re
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import csv
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import pyproj
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import math
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import numpy as np
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def load_metadata(mtl_file):
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mtl_data = {}
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with open(mtl_file) as f:
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mtl = csv.reader(f, delimiter='=')
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try:
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for row in mtl:
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mtl_data[row[0].strip()] = row[1]
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except IndexError:
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pass
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mtl_data['width'] = float(mtl_data['REFLECTIVE_SAMPLES'])
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mtl_data['height'] = float(mtl_data['REFLECTIVE_LINES'])
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mtl_data['lat_lon_corners'] = np.array([
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[float(mtl_data['CORNER_UL_LAT_PRODUCT']), float(mtl_data['CORNER_UL_LON_PRODUCT']), 0],
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[float(mtl_data['CORNER_UR_LAT_PRODUCT']), float(mtl_data['CORNER_UR_LON_PRODUCT']), 0],
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[float(mtl_data['CORNER_LR_LAT_PRODUCT']), float(mtl_data['CORNER_LR_LON_PRODUCT']), 0],
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[float(mtl_data['CORNER_LL_LAT_PRODUCT']), float(mtl_data['CORNER_LL_LON_PRODUCT']), 0]
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])
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mtl_data['ecef'] = pyproj.Proj(proj='geocent', ellps='WGS84', datum='WGS84')
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mtl_data['lla'] = pyproj.Proj(proj='latlong', ellps='WGS84', datum='WGS84')
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x, y, z = pyproj.transform(mtl_data['lla'], mtl_data['ecef'],
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mtl_data['lat_lon_corners'][:, 1],
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mtl_data['lat_lon_corners'][:, 0],
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mtl_data['lat_lon_corners'][:, 2],
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radians=False)
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mtl_data['ecef_corners'] = np.array([x, y, z]).T
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vector_a = mtl_data['vector_a'] = mtl_data['ecef_corners'][1, :] - mtl_data['ecef_corners'][0, :]
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vector_b = mtl_data['vector_b'] = mtl_data['ecef_corners'][2, :] - mtl_data['ecef_corners'][0, :]
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vector_c = mtl_data['vector_c'] = mtl_data['ecef_corners'][3, :] - mtl_data['ecef_corners'][0, :]
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altitude = mtl_data['altitude'] = 710e3
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vector_s = mtl_data['vector_s'] = (vector_a + vector_c) / 2 - altitude * np.cross(vector_a, vector_c) / np.linalg.norm(np.cross(vector_a, vector_c))
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b = np.array([vector_b - (vector_a + vector_c)])
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A = np.array([vector_a - vector_s, vector_c - vector_s, vector_b - vector_s])
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mnt = np.linalg.solve(A.T, b.T)
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print(mnt)
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mtl_data['mu'], mtl_data['nu'] = mnt[0][0], mnt[1][0]
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return mtl_data
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def lat_lot_to_pixel(lat, lon, mtl_data):
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target_vector = np.array([lat, lon, 0])
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x1, y1, z1 = pyproj.transform(mtl_data['lla'], mtl_data['ecef'],
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target_vector[1], target_vector[0], target_vector[2], radians=False)
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x2, y2, z2 = pyproj.transform(mtl_data['lla'], mtl_data['ecef'],
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mtl_data['lat_lon_corners'][0, 1], mtl_data['lat_lon_corners'][0, 0], mtl_data['lat_lon_corners'][0, 2], radians=False)
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x = np.array([x1-x2, y1-y2, z1-z2])
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v = np.cross(mtl_data['vector_c'], mtl_data['vector_a'])
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xh = np.divide(np.dot(v.T, x), np.linalg.norm(v))
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x1, y1, z1 = pyproj.transform(mtl_data['lla'], mtl_data['ecef'],
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target_vector[1], target_vector[0], -xh, radians=False)
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x = np.array([x1-x2, y1-y2, z1-z2])
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A = np.array([
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(1+mtl_data['mu'])*mtl_data['vector_a'] - mtl_data['mu']*mtl_data['vector_s'],
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(1+mtl_data['nu'])*mtl_data['vector_c'] - mtl_data['nu']*mtl_data['vector_s'],
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x-mtl_data['vector_s']
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]).T
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z = np.linalg.solve(A, x.T)
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k = round(z[0], 4)
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r = round(z[1], 4)
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target_x = min([max([1, round(k*mtl_data['width'] + 0.5)]), mtl_data['width']])
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target_y = min([max([1, round(r*mtl_data['height'] + 0.5)]), mtl_data['height']])
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return target_x, target_y
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