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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
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