FaceTracking.py

import cv2
import numpy as np
from djitellopy import tello
import time

mendrone = tello.Tello()
mendrone.connect()
print(mendrone.get_battery())

mendrone.streamon()
mendrone.takeoff()
mendrone.send_rc_control(0, 0, 10, 0)
time.sleep(2.2)


w, h = 480, 360
#fbRange = [6200, 6800]
fbRange = [5000, 6400]
pid = [0.4, 0.4, 0]
pError = 0

def findFace(img):
    faceCascade = cv2.CascadeClassifier("Resources/haarcascade_frontalface_default.xml")
    imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = faceCascade.detectMultiScale(imgGray, 1.2, 8)

    myFaceListC = []
    myFaceListArea = []

    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x,y), (x+w, y+h), (0,0,255), 2)
        cx = x + w // 2
        cy = y + h // 2
        area = w * h
        cv2.circle(img, (cx, cy),5,(0,255,0), cv2.FILLED )
        myFaceListC.append([cx,cy])
        myFaceListArea.append(area)
    if len(myFaceListArea) != 0:
        i= myFaceListArea.index(max(myFaceListArea))
        return img, [myFaceListC[i],myFaceListArea[i]]
    else:
        return img, [[0,0],0]

def trackFace( info, w, pid, pError):
    area = info[1]
    x, y = info[0]
    fb = 0

    error = x - w // 2
    speed = pid[0]*error +pid[1]*(error - pError)
    speed = int(np.clip(speed, -100, 100))


    if area > fbRange[0] and area < fbRange[1]:
        fb=0
    elif area > fbRange[1] :
        fb = -15
    elif area < fbRange[0] and area != 0:
        fb = 15
    if x == 0:
        speed = 0
        error = 0

    #print(speed, fb)

    mendrone.send_rc_control(0,fb,0,speed)
    return error

#cap = cv2.VideoCapture(1)

while True:
    # _, img = cap.read()
    img = mendrone.get_frame_read().frame
    img = cv2.resize(img, (w, h))
    img, info = findFace(img)
    pError= trackFace( info, w, pid, pError)
    #print("Center", info[0] , "Area", info[1])

    cv2.imshow("Output", img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        mendrone.land()
        break