#Coding4Fun – How to control your #drone with 20 lines of code! (10/N)

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Back to some drone posts! I was kind of busy during the last weeks and now I can get back to write about the drone.

OK, in the last posts I described how to connect and work with the drone camera feed using OpenCV. Now with 2 extra lines of code we can also detect faces. Let’s take a look at the final sample.

drone camera and camera view performing face detection

In the previous image we can see 2 camera feeds. My computer webcam, where you can see how I hold the drone with the drone camera pointing to my face. And the drone camera feed, presented using OpenCV and drawing a frame over each detected face.

Let’s share some code insights:

  • As usual, I resize the camera feed to 320 x 240
  • The average processing time is between 40 and 70 FPS
  • I use a haar cascade classifier to detect the faces in each frame

Note: I need to write about Haar Cascades as part of my face detection post series.

# Bruno Capuano
# detect faces using haar cascades from https://github.com/opencv/opencv/tree/master/data/haarcascades
# enable drone video camera
# display video camera using OpenCV
# display FPS
# detect faces
import cv2
import socket
import time
import threading
def receiveData():
global response
while True:
response, _ = clientSocket.recvfrom(1024)
def readStates():
global battery
while True:
response_state, _ = stateSocket.recvfrom(256)
if response_state != 'ok':
response_state = response_state.decode('ASCII')
list = response_state.replace(';', ':').split(':')
battery = int(list[21])
def sendCommand(command):
global response
timestamp = int(time.time() * 1000)
clientSocket.sendto(command.encode('utf-8'), address)
while response is None:
if (time.time() * 1000) timestamp > 5 * 1000:
return False
return response
def sendReadCommand(command):
response = sendCommand(command)
response = str(response)
return response
def sendControlCommand(command):
response = None
for i in range(0, 5):
response = sendCommand(command)
if response == 'OK' or response == 'ok':
return True
return False
# ———————————————–
# Main program
# ———————————————–
# connection info
UDP_IP = ''
UDP_PORT = 8889
last_received_command = time.time()
address = (UDP_IP, UDP_PORT)
response = None
response_state = None
clientSocket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
clientSocket.bind(('', UDP_PORT))
stateSocket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
stateSocket.bind(('', STATE_UDP_PORT))
# start threads
recThread = threading.Thread(target=receiveData)
recThread.daemon = True
stateThread = threading.Thread(target=readStates)
stateThread.daemon = True
# connect to drone
response = sendControlCommand("command")
print(f'command response: {response}')
response = sendControlCommand("streamon")
print(f'streamon response: {response}')
# drone information
battery = 0
# enable face detection
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
# open UDP
print(f'opening UDP video feed, wait 2 seconds ')
videoUDP = 'udp://'
cap = cv2.VideoCapture(videoUDP)
# open
i = 0
while True:
i = i + 1
start_time = time.time()
_, frameOrig = cap.read()
frame = cv2.resize(frameOrig, (320, 240))
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (top, right, bottom, left) in faces:
# display fps
if (time.time() start_time ) > 0:
fpsInfo = "FPS: " + str(1.0 / (time.time() start_time)) # FPS = 1 / time to process loop
cv2.putText(frame, fpsInfo, (10, 20), font, 0.4, (255, 255, 255), 1)
cv2.imshow('@elbruno – DJI Tello Camera', frame)
print(f'battery: {battery} % – i: {i}{fpsInfo}')
except Exception as e:
print(f'exc: {e}')
if cv2.waitKey(1) & 0xFF == ord('q'):
response = sendControlCommand("streamoff")
print(f'streamon response: {response}')

In my next posts, I’ll add some drone specific behaviors for each face detected.

Happy coding!


El Bruno

More posts in my blog ElBruno.com.

More info in https://beacons.ai/elbruno


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