def parse_dem_path(path):
"""
Return datetime and type from DEM path.
"""
datestr = re.findall(r'([0-9]{8})', glimpse.helpers.strip_path(path))[0]
# HACK: Aerial and satellite imagery taken around local noon (~ 22:00 UTC)
t = datetime.datetime.strptime(datestr + str(22), '%Y%m%d%H')
typestr = re.findall(r'dem-([^\/]+)', path)[0]
return dict(datetime=t, type=typestr)
def parse_image_path(path, sequence=False):
"""
Return metadata parsed from image path.
Arguments:
path (str): Image path or basename
sequence (bool): Whether to include sequence metadata (camera, service, ...)
"""
basename = glimpse.helpers.strip_path(path)
station, date_str, time_str = re.findall('^([^_]+)_([0-9]{8})_([0-9]{6})',
basename)[0]
capture_time = datetime.datetime.strptime(date_str + time_str,
'%Y%m%d%H%M%S')
results = dict(basename=basename,
station=station,
date_str=date_str,
time_str=time_str,
datetime=capture_time)
if sequence:
sequences = Sequences()
is_row = ((sequences.station == station) &
(sequences.first_time_utc <= capture_time) &
(sequences.last_time_utc >= capture_time))
rows = np.where(is_row)[0]
if len(rows) != 1:
raise ValueError(
'Image path has zero or multiple sequence matches: ' + path)
results = glimpse.helpers.merge_dicts(sequences.loc[rows[0]].to_dict(),
results)
return results
# 'CG05_20050811_130000',
# 'CG05_20050811_190000',
# NOTE: More clarity than CG05_20050827_190000
'CG05_20050826_190000',
'CG06_20060712_195953',
'CG06_20060727_195951'
)
clahe = cv2.createCLAHE(clipLimit=1.0, tileGridSize=(20, 20))
# ---- Select DEMs and Orthos ----
# Prepare DEMs
dem_paths = glob.glob(os.path.join(root, 'dem-aerometric', 'data', '*.tif'))
dem_paths += glob.glob(os.path.join(root, 'dem-arcticdem', 'data', '*.tif'))
dem_paths += glob.glob(os.path.join(root, 'dem-ifsar', 'data', '*.tif'))
dem_dates = [datetime.datetime.strptime(re.findall(r'([0-9]{8})', path)[0], '%Y%m%d')
for path in dem_paths]
# Prepare orthophotos
ortho_paths = glob.glob(os.path.join(root, 'ortho', '*.tif'))
ortho_paths += glob.glob(os.path.join(root, 'ortho-ifsar', 'data', '*.tif'))
ortho_dates = [datetime.datetime.strptime(re.findall(r'([0-9]{8})', path)[0], '%Y%m%d')
for path in ortho_paths]
# ---- Control synths (ideal camera) ----
for image in images:
print(image)
start = timeit.default_timer()
basename = os.path.join('svg-synth', image)
if os.path.isfile(basename + '-synth.JPG'):
# NOTE: 20050811 ortho messed up
# 'CG05_20050811_130000',
# 'CG05_20050811_190000',
# NOTE: More clarity than CG05_20050827_190000
'CG05_20050826_190000',
'CG06_20060712_195953',
'CG06_20060727_195951')
# ---- Select DEMs and Orthos ----
# Prepare DEMs
dem_paths = glob.glob(os.path.join(root, 'dem-aerometric', 'data', '*.tif'))
dem_paths += glob.glob(os.path.join(root, 'dem-arcticdem', 'data', '*.tif'))
dem_paths += glob.glob(os.path.join(root, 'dem-ifsar', 'data', '*.tif'))
dem_dates = [
datetime.datetime.strptime(re.findall(r'([0-9]{8})', path)[0], '%Y%m%d')
for path in dem_paths
]
# Prepare orthophotos
ortho_paths = glob.glob(os.path.join(root, 'ortho', '*.tif'))
ortho_paths += glob.glob(os.path.join(root, 'ortho-ifsar', 'data', '*.tif'))
ortho_dates = [
datetime.datetime.strptime(re.findall(r'([0-9]{8})', path)[0], '%Y%m%d')
for path in ortho_paths
]
# ---- Validation synths (calibrated camera) ----
for image in images:
basename = os.path.join('images', image)
glimpse.helpers.elevate_geojson(geo, elevation=dem)
for coords in glimpse.helpers.geojson_itercoords(geo):
if any(np.isnan(coords[:, 2])):
print('Missing elevations in ' + path)
geo2 = glimpse.helpers.ordered_geojson(geo)
glimpse.helpers.write_geojson(geo2,
path=os.path.splitext(path)[0] + '.geojson',
decimals=(7, 7, 2), crs=32606)
# ---- Ground control points ----
GCP_DEM_PATH = '/volumes/science-b/data/columbia/_new/ArcticDEM/v2.0/tiles/merged_projected_clipped.tif'
dem_ref = glimpse.Raster.read(GCP_DEM_PATH)
geo = glimpse.helpers.read_geojson('geojson/gcp.geojson', crs=32606, key='id')
keys = [key for key in geo['features'] if re.findall('T' + DATE_STR, key)]
keys.sort()
for key in keys:
coords = geo['features'][key]['geometry']['coordinates']
coords[:, 2] = dem.sample(coords[:, 0:2])
if any(np.isnan(coords[:, 2])):
print('Missing elevation for ' + key)
# Check for gross errors
z = np.vstack([geo['features'][key]['geometry']['coordinates'][:, 2] for key in keys])
z_ref = np.vstack([dem_ref.sample(geo['features'][key]['geometry']['coordinates'][:, 0:2]) for key in keys])
z - z_ref
geo2 = glimpse.helpers.ordered_geojson(geo, properties=('id', 'valid', 'notes'))
glimpse.helpers.write_geojson(geo2, path='geojson/gcp.geojson',
decimals=(7, 7, 2), crs=32606)
('20141114_20141130', 'golive'), # some holes
('20150322_20150423', 'golive'), # many holes
('20150430_20150516', 'golive'), # some holes
('20150502_20150518', 'golive'), # some holes
('20150617_20150703', 'golive'),
('20150703_20150719', 'golive'),
('20150719_20150804', 'golive'),
('20150804_20150820', 'golive'),
('20150907_20150923', 'golive'),
('20150923_20151025', 'golive'),
('20160621_20160707', 'golive'),
('20161009_20161025', 'golive')
]
# Add all Krimmel velocities
velocity_keys += [
(re.findall(r'([0-9]{8}_[0-9]{8})', path)[0], 'krimmel')
for path in glob.glob(
os.path.join(root, 'velocities-krimmel', 'data', '*_vx.tif'))
]
# Add all early McNabb landsat velocities
velocity_keys += [
(re.findall(r'([0-9]{8}_[0-9]{8})', path)[0], 'landsat')
for path in glob.glob(
os.path.join(root, 'velocities-landsat', 'data', '*_vx.tif'))
if re.findall(r'([0-9]{8}_[0-9]{8})', path)[0] < '20110101'
]
# Sort by time
velocity_keys.sort(key=lambda x: x[0])
# ---- Read and sample at template ----
# t: start, end, mid