Datasets:

Languages:
English
License:
File size: 11,613 Bytes
4e21c6d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
import re
import datetime
import pytest
import numpy as np
import pandas as pd
import rasterio

from pathlib import Path
from PIL import Image
from PIL.ExifTags import TAGS, GPSTAGS
from numbers import Rational
from math import isclose

from geopy import distance
from sklearn.neighbors import NearestNeighbors

FIELD_ALTITUDE = 587
NUMBER_REGEX = re.compile(r'DJI_(\d*)')

@pytest.fixture
def expected_low_alt_dirs():
    return {
        "15.04.2024": {"2m"},
        "26.04.2024": {"2m"},
        "07.05.2024": {"2m"},
        "14.05.2024": {"2m"},
        "27.05.2024": {"5m", "10m"},
        "06.06.2024": {"5m", "10m", "20m"},
        "12.06.2024": {"5m", "10m", "20m"},
        "24.06.2024": {"5m", "10m", "20m", "40m"},
        "05.07.2024": {"5m", "10m", "20m", "40m"},
        "10.07.2024": {"5m","10m", "40m"}, # "20m" was corrupted
        "16.07.2024": {"5m", "10m", "20m"}, # "40m" was corrupted
        "24.07.2024": {"5m", "10m", "20m", "40m"}
    }

@pytest.fixture
def expected_reconstructed_files():
    return [
            "dsm.tif",
            "result.tif",
            "result_Blue.tif", 
            "result_Green.tif", 
            "result_NIR.tif", 
            "result_Red.tif",
            "result_RedEdge.tif",
            "index_map/GNDVI.tif",
            "index_map/LCI.tif",
            "index_map/NDRE.tif",
            "index_map/NDVI.tif",
            "index_map/OSAVI.tif",
            "index_map_color/GNDVI_local.tif",
            "index_map_color/LCI_local.tif",
            "index_map_color/NDRE_local.tif",
            "index_map_color/NDVI_local.tif",
            "index_map_color/OSAVI_local.tif",
            ]


@pytest.fixture
def dates():
    current_dir = Path('.')
    return [date for date in current_dir.glob("*.2024") if date.is_dir()]


@pytest.fixture
def expected_coordinates(): 
    points_from_clustering =  np.array([
        [42.652493119731815,23.5335933908046],
        [42.65268404501916,23.53364708716476],
        [42.65289795689655,23.53375856321839],
        [42.65308413122605,23.533792892720307],
        [42.65329313601532,23.53381995498084],
        [42.653500840996166,23.533874733716477],
        [42.653682366858234,23.53394230268199],
        [42.6536356321839,23.534255020114948],
        [42.65358158429118,23.53456061494253],
        [42.65336092049809,23.534458518199237],
        [42.65311266283525,23.53438435153257],
        [42.65285994058642,23.534302500771606],
        [42.65277988131313,23.534278771464646],
        [42.65269517624521,23.534265536398472],
        [42.65256960249042,23.53419812931035],
        [42.652472256704975,23.534161837164753],
        [42.65235443582375,23.534092082375487],
        [42.65221295019157,23.534681908045975],
        [42.652479424329506,23.534787376436785],
        [42.652771164750945,23.53494312452108],
        [42.65309712260537,23.535079702107286],
        [42.653323341954014,23.535162461685825],
        [42.65347431034482,23.535213143678156],
        [42.65338250383142,23.53566046743295],
        [42.65322460919539,23.535642157088123],
        [42.653034226053634,23.53558124042146],
        [42.65280317911878,23.535486852490422],
        [42.65260797605364,23.53538108333333],
        [42.6523800124521,23.53529239559387],
        [42.65213938122605,23.53520383429119],
        [42.65214804310344,23.534911490421457],
        [42.65237861302682,23.534422040229884],
    ])
    assert points_from_clustering.shape == (32, 2)
    return points_from_clustering
    

def degrees_to_decimal(degrees: Rational, minutes: Rational, seconds: Rational, direction: str):
    assert(isinstance(degrees, Rational)) # PIL.TiffImagePlugin.IFDRational is a subtype of Rational
    assert(isinstance(minutes, Rational))
    assert(isinstance(seconds, Rational))
    degrees = float(degrees)
    minutes = float(minutes)
    seconds = float(seconds)

    return (degrees + minutes / 60 + seconds / 3600) * (-1 if direction in ['W', 'S'] else 1)


def get_exif_data(path):
    image = Image.open(path)
    exif_data = {}
    
    exif = image.getexif()
    assert exif is not None, path

    for tag, value in exif.items():
        tag_name = TAGS.get(tag, tag)
        exif_data[tag_name] = value

    assert 'DateTime' in exif_data, path
    exif_data['DateTime'] = datetime.datetime.strptime(exif_data['DateTime'], '%Y:%m:%d %H:%M:%S')
    
    assert 'GPSInfo' in exif_data
    gps_info = {}    

    for key,value in exif.get_ifd(0x8825).items():
        decode = GPSTAGS.get(key, key)
        gps_info[decode] = value

    assert 'GPSLatitude' in gps_info, path
    assert 'GPSLongitude' in gps_info, path
    assert 'GPSAltitude' in gps_info, path

    for key in gps_info.keys():
        if key == 'GPSLatitude':
            decim = degrees_to_decimal(*gps_info[key], gps_info['GPSLatitudeRef'])
            gps_info[key] = decim
        if key == 'GPSLongitude':
            decim = degrees_to_decimal(*gps_info[key], gps_info['GPSLongitudeRef'])
            gps_info[key] = decim

    exif_data['decoded_gps_info'] = gps_info    
    return exif_data


def test_all_dates_are_present(dates):
    assert len(dates) == 12        


def test_lowalt_folder_integrity(dates, expected_low_alt_dirs, expected_coordinates):
    NUM_NEIGHBORS = 2
    neighbors = NearestNeighbors(n_neighbors=NUM_NEIGHBORS).fit(expected_coordinates)
    
    points = []
    for d in dates:
        low_alt_dirs = { lad for lad in d.glob("*m") if lad.is_dir() }
        
        assert len(low_alt_dirs) > 0
        assert {n.name for n in low_alt_dirs} == expected_low_alt_dirs[d.name], d.name

        for low_alt_dir in low_alt_dirs:
            altitude = int(low_alt_dir.name[:-1]) + FIELD_ALTITUDE

            jpegs = list(low_alt_dir.glob("*.JPG"))
            jpegs.sort() # needed for consistency between windows and linux (latter may fail without it)
            assert len(jpegs) == 32

            tifs = list(low_alt_dir.glob("*.TIF"))
            assert len(tifs) == 160

            found_coordinates = {}
            for f in jpegs:
                ed = get_exif_data(f)
                assert ed['DateTime'].strftime("%d.%m.%Y") == d.name

                gps = ed['decoded_gps_info']
                assert isclose(gps['GPSAltitude'], altitude, rel_tol=0.02), f'{low_alt_dir}, {f}'

                point = (gps['GPSLatitude'], gps['GPSLongitude'])
                indices = neighbors.kneighbors(np.expand_dims(point, 0), return_distance=False).flatten()
                
                for i in range(NUM_NEIGHBORS):
                    nearest_point = tuple(expected_coordinates[indices[i]])
                    if nearest_point not in found_coordinates:
                        found_coordinates[nearest_point] = point
                        break
                    else:
                        print((
                                f"WARN: {f} nearest point {nearest_point} for {point} is already claimed by {found_coordinates[nearest_point]}. "
                                f"Distance: {distance.distance(point, nearest_point).m}"
                            )
                        )
                        
                assert nearest_point is not None, (f, point)
                assert distance.distance(point, nearest_point).m < 5.95, (f, point, nearest_point)

                points.append(
                    {
                        'date': d.name,
                        'altitude': gps['GPSAltitude'],
                        'height': altitude - FIELD_ALTITUDE,
                        'file':  str(f),
                        'geometry': point,
                        'x': point[0],
                        'y': point[1],
                        'ref_x': nearest_point[0],
                        'ref_y': nearest_point[1],
                    }
                )
                
                jpeg_number = int(NUMBER_REGEX.match(f.name).group(1))
                assert jpeg_number > 0 and jpeg_number < 9999
                tif_files = [f.parent / f"DJI_{jpeg_number + i:04d}.TIF" for i in range(1, 6)]
                
                for tif in tif_files:
                    assert tif.exists(), tif
                    tif_ed = get_exif_data(tif)
                    assert tif_ed['DateTime'].strftime("%d.%m.%Y") == d.name, tif
                    tif_gps = tif_ed['decoded_gps_info']

                    # expected that coords and altitude will be an exact match, but turned out there are slight differences
                    assert isclose(tif_gps['GPSAltitude'], gps['GPSAltitude'], rel_tol=1e-3), tif
                    assert isclose(tif_gps['GPSLatitude'], gps['GPSLatitude'], rel_tol=1e-7), tif
                    assert isclose(tif_gps['GPSLongitude'], gps['GPSLongitude'], rel_tol=1e-7), tif
            assert len(found_coordinates) == 32, (d.name, low_alt_dir.name)
    
    pd.DataFrame(points).to_csv('points.csv', index=False)


def test_aerial_folder_integrity(dates):
    for d in dates:
        aerial  = d / "aerial"
        assert aerial.exists()
        
        jpegs = list(aerial.glob("*.JPG"))
        assert len(jpegs) == 36

        tifs = list(aerial.glob("*.TIF"))
        assert len(tifs) == 180

        for f in jpegs + tifs:
            ed = get_exif_data(f)
            assert ed['DateTime'].strftime("%d.%m.%Y") == d.name


def test_terra_folder_integrity(dates, expected_reconstructed_files):
    for d in dates:
        for subdir in [d / "terra/default", d / "terra/lu"]:
            assert subdir.exists()
            assert subdir.is_dir()
            
            assert {f.name for f in subdir.iterdir()} == {"map", "mission.json"}, subdir 
            assert {f.name for f in (subdir / "map").iterdir() if f.is_dir()} == {"index_map", "index_map_color" }, subdir / "map"
            assert {f.name for f in (subdir / "map/index_map").iterdir() if f.is_dir()} == set(), subdir / "map/index_map"
            assert {f.name for f in (subdir / "map/index_map_color").iterdir() if f.is_dir()} == set(), subdir / "map/index_map_color"
            assert (subdir / "map/SDK_Log.txt").exists() == False, subdir

            for f in [subdir / "map" / f for f in expected_reconstructed_files]:     
                assert f.exists()
                assert f.is_file()
                dataset = rasterio.open(f)
                if not str(f).endswith("dsm.tif"):    
                    assert dataset.width >= 3532 and dataset.width <= 3682, f
                    assert dataset.height >=3656 and dataset.height <= 3833, f
                
                if not str(f).endswith("_local.tif"):
                    assert dataset.crs.to_epsg() == 4326, f
                    b = dataset.bounds
                    assert isclose(b.left, 23.533500842872694, rel_tol=1e-5), f
                    assert isclose(b.right, 23.536542466168836, rel_tol=1e-5), f
                    assert isclose(b.top, 42.65398844980852, rel_tol=1e-5), f
                    assert isclose(b.bottom, 42.65168278534697, rel_tol=1e-5), f
                    assert f.with_suffix(".prj").exists()
                    assert f.with_suffix(".tfw").exists()
                
                if "index_map" in str(f) and "index_map_color" not in str(f): # vegetation indices should be in [-1, 1]
                    data = dataset.read()
                    assert np.nanmin(data) >= -1
                    assert np.nanmax(data) <= 1 


def test_extra_folder_exists(dates):
    for d in dates:
        extra_dir = (d / "extra")
        assert extra_dir.exists() == False, extra_dir.absolute()   # Not part of the published dataset