def load_all(self, flight_dir="", image_dir=""):
self.flight_dir = flight_dir
self.image_dir = image_dir
data, flight_format = flight_loader.load(flight_dir)
#data = flight_data.load('aura', flight_dir)
self.interp = flight_interp.FlightInterpolate()
self.interp.build(data)
#self.load_gps()
#self.load_filter()
self.load_events()
self.load_images()
loader = 'sentera1'
path = args.sentera_flight
elif args.sentera2_flight:
loader = 'sentera2'
path = args.sentera2_flight
elif args.umn_flight:
loader = 'umn1'
path = args.umn_flight
else:
loader = None
path = None
if 'recalibrate' in args:
recal_file = args.recalibrate
else:
recal_file = None
data = flight_loader.load(loader, path, recal_file)
print "imu records:", len(data['imu'])
print "gps records:", len(data['gps'])
if 'air' in data:
print "airdata records:", len(data['air'])
print "filter records:", len(data['filter'])
if 'pilot' in data:
print "pilot records:", len(data['pilot'])
if 'act' in data:
print "act records:", len(data['act'])
if len(data['imu']) == 0 and len(data['gps']) == 0:
print "not enough data loaded to continue."
quit()
interp = flight_interp.FlightInterpolate()
interp.build(data)
help='resample rate (hz)')
parser.add_argument('--xmin', type=float, help='start time')
parser.add_argument('--xmax', type=float, help='end time')
parser.add_argument('--plot', action='store_true', help='plot results.')
args = parser.parse_args()
g = 9.81
r2d = 180.0 / math.pi
if 'recalibrate' in args:
recal_file = args.recalibrate
else:
recal_file = None
# load the flight data
data, flight_format = flight_loader.load(args.flight, recal_file)
print("imu records:", len(data['imu']))
print("gps records:", len(data['gps']))
print("filter records:", len(data['gps']))
if len(data['imu']) == 0:
print("not enough data loaded to continue.")
quit()
# build the interpolation tables
interp = flight_interp.FlightInterpolate()
interp.build(data)
# read the events-0.csv file to determine when aircraft becomes airborne
# (so we can ignore preflight values.) Update: also to read the IMU
# serial number.
xmin = None
help='Directory containing the images')
parser.add_argument('--hz', default=100, type=int, help='sample rate')
parser.add_argument('--shift-time', type=float, help='manual time shift')
parser.add_argument('--no-plot',
dest='plot',
action='store_false',
help='do not show correlation plots')
parser.add_argument('--write',
action='store_true',
help='update geotags on source images')
parser.set_defaults(plot=True)
args = parser.parse_args()
# load flight data
print 'Loading flight data:', args.flight
data, flight_format = flight_loader.load(args.flight)
interp = flight_interp.FlightInterpolate()
interp.build(data)
# load camera triggers (from the events file)
triggers = []
airborne = False
ap = False
event_file = os.path.join(args.flight, "event-0.csv")
if os.path.exists(event_file):
with open(event_file, 'rb') as fevent:
reader = csv.DictReader(fevent)
for row in reader:
tokens = row['message'].split()
if len(tokens) == 2 and tokens[0] == 'mission:' and tokens[
1] == 'airborne':
# while loop.
k += 1
# proper cleanup
filter.close()
run_end = time.time()
elapsed_sec = run_end - run_start
return data_dict, elapsed_sec
path = args.flight
if 'recalibrate' in args:
recal_file = args.recalibrate
else:
recal_file = None
data, flight_format = flight_loader.load(path, recal_file)
print "imu records:", len(data['imu'])
print "gps records:", len(data['gps'])
if 'air' in data:
print "airdata records:", len(data['air'])
if 'filter' in data:
print "filter records:", len(data['filter'])
if 'pilot' in data:
print "pilot records:", len(data['pilot'])
if 'act' in data:
print "act records:", len(data['act'])
if len(data['imu']) == 0 and len(data['gps']) == 0:
print "not enough data loaded to continue."
quit()