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convert.py
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convert.py
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#!/usr/bin/python3
import csv
import json
import math
import time
import argparse
import sys
import os
from pathlib import Path
import base64
from math import radians, cos, sin, asin, sqrt
import re
def haversine(lon1, lat1, lon2, lat2):
"""
Calculate the great circle distance in kilometers between two points
on the earth (specified in radians)
"""
# convert decimal degrees to radians
# lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
# haversine formula
dlon = lon2 - lon1
dlat = lat2 - lat1
a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
c = 2 * asin(sqrt(a))
r = 6371 # Radius of earth in kilometers. Use 3956 for miles. Determines return value units.
return c * r
folderprefix='HyperLapse_Path_'
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'
parser = argparse.ArgumentParser(description = "This script (https://github.com/tobst/waypoint-converter) is meant to convert csv-data into Hyperlapse Waypoint missions. It is still under development. If your mission does not show, try different lengths, and experiment with interval and duration. Provide feedback if you understand how these work together in order to create missions that always work. ")
parser.add_argument("inputfile", type=str, nargs='+', help = "(one ore more) DroneHarmony wpt CSV input file(s)")
parser.add_argument("-o", help = "Output json file. Written to default directory (current time since epoch in millies) if omitted")
parser.add_argument("-t", type=float, default = 0.0, help = "Height offset [m] added to CSV height")
parser.add_argument("-m", type=int, default = 1, help = "Multiply every waypoint this many times")
parser.add_argument("-i", action="store_true", help = "Generate an image for each index")
parser.add_argument("-p", type=float, help = "Gimpal pitch [deg]")
parser.add_argument("-s", type=int, default = 1, help = "Number of altitude steps, will create multiple files with altitude incremented by dh")
parser.add_argument("-dh", type=float, default = 2, help = "Altitude delta [m] for creation of multiple files")
parser.add_argument("-int", type=int, default = 20, help = "Interval between single pictures [s/10], with a fixed duration, this should have influence on the speed of the mission")
parser.add_argument("-dur", type=int, default = 30, help = "Duration of the timelapse [s/10] with 25fps, 210 will result in 21s video and 525 pictures")
parser.add_argument("-maxl", type=int, default = 2000, help = "target length of track [m], will be split into multiple files")
parser.add_argument("-ignf", type=bool, default = False, help = "Ignore first waypoint")
parser.add_argument("-ignl", type=bool, default = False, help = "Ignore last waypoint")
args = parser.parse_args()
inputfile = args.inputfile
# currtime = 1662086546034
j = 1
while j <= args.s:
deltah = (j-1)*args.dh
j = j+1
currtime = int(time.time()*1000)
wpts =[]
wpts_out =[]
index_ts = currtime
for inputfile in args.inputfile:
csvfile = open(inputfile, newline='')
csvdta = csv.reader(csvfile, delimiter=',')
filewpts = 0
header = next(csvdta)
print("Header: ")
print(header)
latitude_index = header.index('Latitude')
longitude_index = header.index('Longitude')
altitude_index = header.index('Altitude')
azimuth_index = header.index('Azimuth')
if "GimbalPitch" in header:
pitch_index = header.index('GimbalPitch')
if "Pitch" in header:
pitch_index = header.index('Pitch')
if args.ignf:
next(csvdta)
for row in csvdta:
for i in range(args.m):
wpt = {}
wpt["index"]=index_ts
wpt["px"] = 0.0
wpt["py"] = 0.0
wpt["pz"] = 0.0
wpt["height"] = float(row[altitude_index])
if args.p == None:
wpt["gimbal_pitch"] = float(row[pitch_index])
else:
wpt["gimbal_pitch"] = args.p
wpt["gimbal_roll"] = 0.0
wpt["gimbal_yaw"] = float(row[azimuth_index])
wpt["longitude"] = float(row[longitude_index]) * math.pi/180
wpt["latitude"] = float(row[latitude_index]) * math.pi/180
wpt["altitude"] = float(row[altitude_index]) + args.t + deltah
wpt["traj_id"] = 0
wpts.append(wpt)
index_ts += 1
filewpts += 1
if args.ignl:
for i in range(args.m):
wpts.pop()
print("Read " + str(filewpts) + " WPTs from " + inputfile, file=sys.stderr)
# calculate total length of track
length = 0
total_length = 0
waypoints_begin = (args.m)
num_track = 1
for i in range(waypoints_begin, len(wpts)):
length += haversine(wpts[i-1]["longitude"], wpts[i-1]["latitude"], wpts[i]["longitude"], wpts[i]["latitude"])
if int(length*1000) > args.maxl:
print("Length of track " + str(num_track) + " : ", "length = {:.3f}".format(length), " km")
total_length += length
num_track += 1
length = 0
wpts_out.append(wpts[waypoints_begin-(args.m):i])
waypoints_begin=i
print("Length of track " + str(num_track) + " : ", "length = {:.3f}".format(length), " km")
total_length += length
wpts_out.append(wpts[waypoints_begin-(args.m):])
print("Total length of tracks: ", "total_length = {:.3f}".format(total_length), " km")
num_track=1
for shortened_wpts in wpts_out:
currtime = int(time.time()*1000)
filenameprefix = str(currtime)
foldername = folderprefix+filenameprefix
os.makedirs(foldername)
filename= filenameprefix+".json"
outstruct = {}
outstruct["name"] = Path(inputfile).stem + "_o" + str(int(args.t)+deltah) + "_i" + str(args.int) + "_d" + str(args.dur) + "_n" + str(num_track)# + "_pitch_" + str(int(args.p))
outstruct["date"] = currtime
outstruct["forward"] = True
outstruct["interval"] = args.int
outstruct["duration"] = args.dur
outstruct["list"] = shortened_wpts
outstruct["hash"] ="25B9CCE9B38D64CED21DC4213C6E3D2F"
print("Number of WPTs written: " + str(len(shortened_wpts)) + " (multiply used: " + str(args.m) +")", file=sys.stderr)
if args.o == None:
#print(json.dumps(outstruct, indent=2))
with open(os.path.join(foldername, filename), 'w') as json_file:
json.dump(outstruct, json_file, separators=(',',':'))
else:
with open(args.o, 'w') as json_file:
json.dump(outstruct, json_file, separators=(',',':'))
if args.i:
print("Generating images", file=sys.stderr)
bindata = base64.b64decode(imagedata)
for i in wpts:
imgfile = open(os.path.join(foldername, str(i["index"])), "wb")
imgfile.write(bindata)
imgfile.close()
num_track+=1