#
## Altitude of the dataset [m].
alt = fmd[0]['alt'] # [m]
## The pixel mask.
pixel_mask = {}
with open(dp.get_input_path() + "/masked_pixels.txt", "r") as mpf:
rows = mpf.readlines()
for row in rows:
vals = [int(val) for val in row.strip().split("\t")]
x = vals[0]; y = vals[1]; X = (256*y) + x; C = 1
pixel_mask[X] = C
## The frames from the dataset.
frames = ds.getFrames((lat, lon, alt), pixelmask = pixel_mask)
lg.info(" * Found %d datafiles." % (len(frames)))
## A list of frames.
mds = []
## A list of clusters.
klusters = []
# Loop over the frames.
for i, f in enumerate(frames):
if i % 50 == 0:
print("*--> '%s': processing frame % 10d..." % (dp.get_name(), i))
lg.info("")
## The dataset to process.
ds = Dataset(datapath)
## Latitude of the test dataset [deg.].
lat = 51.509915
## Longitude of the test dataset [deg.].
lon = -0.142515 # [deg.]
## Altitude of the test dataset [m].
alt = 34.02
## The frames from the dataset.
frames = ds.getFrames((lat, lon, alt))
lg.info("* Found %d datafiles:" % (len(frames)))
## A list of frames.
mds = []
# Clusters
#----------
## A list of clusters.
klusters = []
# Loop over the frames and upload them to the DFC.
for f in frames:
#
## Altitude of the dataset [m].
alt = fmd[0]['alt'] # [m]
## The pixel mask.
pixel_mask = {}
with open(datapath + "/masked_pixels.txt", "r") as mpf:
rows = mpf.readlines()
for row in rows:
vals = [int(val) for val in row.strip().split("\t")]
x = vals[0]; y = vals[1]; X = (256*y) + x; C = 1
pixel_mask[X] = C
## The frames from the dataset.
frames = ds.getFrames((lat, lon, alt), pixelmask = pixel_mask)
lg.info(" * Found %d datafiles." % (len(frames)))
print("* Found %d datafiles." % (len(frames)))
print("*")
if max_frames < 0 or max_frames > len(frames):
max_frames = len(frames)
## A list of frames.
mds = []
# Clusters
#----------
