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video_recorder.py
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video_recorder.py
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from dronekit import connect,VehicleMode,mavutil,LocationGlobal,Command,LocationGlobalRelative
import time
import numpy as np
import math
import cv2
import sys
from plane_functions import *
'''old_stdout = sys.stdout
log_file = open("/home/pi/Desktop/auto-mission-updater-opencv/log.txt","w")
sys.stdout = log_file'''
connection_string="/dev/serial/by-id/usb-Hex_ProfiCNC_CubeOrange_3E0040001151303437363830-if00"
print("Connecting to İHA...")
iha=connect(connection_string,wait_ready=True,timeout=100,baud=115200)
print("..........................")
print("Connected to İHA!")
print("Mode: %s" % iha.mode)
print("Attitude: %s" % iha.attitude)
print("Velocity: %s" % iha.velocity)
print("Global Location (relative altitude) %s" % iha.location.global_relative_frame)
print("..........................\n")
last_rangefinder_distance=0
@iha.on_attribute('rangefinder')
def rangefinder_callback(self,attr_name):
global last_rangefinder_distance
if last_rangefinder_distance == round(self.rangefinder.distance, 1):
return
last_rangefinder_distance = round(self.rangefinder.distance, 1)
attitude = iha.attitude
@iha.on_attribute('attitude')
def attitude_listener(self, name, msg):
global attitude
if attitude.pitch == round(self.attitude.pitch,2) or attitude.roll == round(self.attitude.roll,2):
return
attitude = self.attitude
global_location = iha.location.global_relative_frame
@iha.on_attribute('location.global_relative_frame')
def location_listener(self, name, msg):
global global_location
global_location = self.location.global_relative_frame
video = cv2.VideoCapture(0)
if (video.isOpened() == False):
print("Error reading video file")
video.set(3,1920)
video.set(4,1080)
while True:
time.sleep(1)
if last_rangefinder_distance>=5:
break
start = time.time()
count = 1
telemetry_count = 1
saved_coordinates = []
send_or_not = 1
repeater = 0
while(True):
_, imageFrame = video.read()
hsvFrame = cv2.cvtColor(imageFrame, cv2.COLOR_BGR2HSV)
red_lower,red_upper = np.array([136, 87, 111], np.uint8) , np.array([180, 255, 255], np.uint8)
red_mask = cv2.inRange(hsvFrame, red_lower, red_upper)
kernal = np.ones((5, 5), "uint8")
red_mask = cv2.dilate(red_mask, kernal)
res_red = cv2.bitwise_and(imageFrame, imageFrame,
mask = red_mask)
contours, hierarchy = cv2.findContours(red_mask,
cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
contours = sorted(contours, key=cv2.contourArea, reverse=True)
count+=1
if (time.time()-start)>240:
break
for pic, contour in enumerate(contours[:1]):
area = cv2.contourArea(contour)
if (area > 30000) and (area<500000):
repeater += 1
x, y, w, h = cv2.boundingRect(contour)
cx = x + w/2
cy = y + h/2
radius = w/2
coordinates = (int(x+w/2), int(y+h/2))
center_point = (int(imageFrame.shape[1])//2,int(imageFrame.shape[0])//2)
xdist , ydist = coordinates[0] - center_point[0],center_point[1] - coordinates[1]
pixel_distance = math.sqrt(xdist**2 + ydist**2)
xreal,yreal=(1.25*xdist/radius),(1.25*ydist/radius)
real_distance = math.sqrt(xreal**2 + yreal**2)
east_d = math.cos(-attitude.yaw)*xreal - math.sin(-attitude.yaw)*yreal
north_d = math.sin(-attitude.yaw)*xreal + math.cos(-attitude.yaw)*yreal
dist_target = math.sqrt(east_d**2+north_d**2)
red_carpet_loc = get_location_meters(global_location,north_d,east_d)
info = """
x_d = {} y_d = {} p_d = {} \n
x_r = {} y_r = {} r_d = {} \n
pitch = {} yaw = {} roll = {} \n
east_t = {} north_t = {} t_d = {} \n
time = {} \n
p_l = {} \n
c_l = {} \n
pixel_num = {}
""".format(round(xdist,2),round(ydist,2),round(pixel_distance,2),
round(xreal,2),round(yreal,2),round(real_distance,2),round(attitude.pitch,2),round(attitude.yaw,2),round(attitude.roll,2),
round(east_d,2),round(north_d,2),round(dist_target,2),
round(time.time()-start,2),
[global_location.lat,global_location.lon,global_location.alt],
[red_carpet_loc.lat,red_carpet_loc.lon,red_carpet_loc.alt],
area)
print("Red carpet seen")
y0, dy = 7, 15
for i, line in enumerate(info.split('\n')):
ky = y0 + i*dy
cv2.putText(imageFrame, line, (0,ky), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,255,0),2)
cv2.circle(imageFrame,(x+w//2,y+h//2),int(radius),(255,0,255),3)
cv2.putText(imageFrame,str(east_d)+" "+str(north_d)+" "+str(dist_target),((center_point[0]),(center_point[1])), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2)
cv2.line(imageFrame,((center_point[0]),(center_point[1])),coordinates,(0,255,0),2)
else:
repeater = 0
cv2.imwrite("/home/pi/Desktop/auto-mission-updater-opencv/framesrecord/frame{}.jpg".format(count),imageFrame)
endlast = time.time()
print("Video recording has been finished!")
print("Flight notes: ")
print("********************************************************")
print("Flight time: %s" % (endlast-start))
print("Total distance taken: %s" % get_distance_meters(iha.home_location, iha.location.global_relative_frame))
print("Home location: %s" % iha.home_location)
if len(saved_coordinates)==0:
print("No red carpet found!")
else:
print("Red carpet found {} times!".format(len(saved_coordinates)))
print("Coordinates: ")
for i in saved_coordinates:
print("lat: {}, lon: {}, alt: {}".format(i.lat,i.lon,i.alt))
lats,lons,alts=[],[],[]
for i in saved_coordinates:
lats.append(i.lat)
lons.append(i.lon)
alts.append(i.alt)
act_lat = sum(lats)/len(lats)
act_lon = sum(lons)/len(lons)
act_alt = sum(alts)/len(alts)
print("Actual location: {} {} {}".format(act_lat,act_lon,act_alt))
print("********************************************************")
# When everything done, release
# the video capture and video
# write objects
video.release()
# Closes all the frames
cv2.destroyAllWindows()
'''sys.stdout = old_stdout
log_file.close()'''