tmp_video = filename + "_tmp." + ext
output_video = filename + "_hud." + ext
camera = camera.VirtualCamera()
camera.load(args.camera, local_config, args.scale)
cam_yaw, cam_pitch, cam_roll = camera.get_ypr()
K = camera.get_K()
dist = camera.get_dist()
print('Camera:', camera.get_name())
print('K:\n', K)
print('dist:', dist)
if os.path.exists(ekf_error):
correction.load_horiz(ekf_error)
data, flight_format = flight_loader.load(args.flight)
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.InterpolationGroup(data)
iter = flight_interp.IterateGroup(data)
from aurauas_flightdata import flight_loader, flight_interp
parser = argparse.ArgumentParser(description='nav filter')
parser.add_argument('flight', help='flight data log')
parser.add_argument('--wind-time',
type=float,
help='force a wind re-estimate with this time factor.')
args = parser.parse_args()
r2d = 180.0 / math.pi
d2r = math.pi / 180.0
m2nm = 0.0005399568034557235 # meters to nautical miles
mps2kt = 1.94384 # m/s to kts
path = args.flight
data, flight_format = flight_loader.load(path)
print("imu records:", len(data['imu']))
imu_dt = (data['imu'][-1]['time'] - data['imu'][0]['time']) \
/ float(len(data['imu']))
print("imu dt: %.3f" % imu_dt)
print("gps records:", len(data['gps']))
if 'air' in data:
print("airdata records:", len(data['air']))
if len(data['imu']) == 0 and len(data['gps']) == 0:
print("not enough data loaded to continue.")
quit()
# make data frames for easier plotting
df0_imu = pd.DataFrame(data['imu'])
df0_imu.set_index('time', inplace=True, drop=False)