import numpy as np
import cv2 as cv
import tello_drone as tello
host = ''
port = 9000
local_address = (host, port)
# Pass the is_dummy flag to run the face detection on a local camera
drone = tello.Tello(host, port, is_dummy=False)
def adjust_tello_position(offset_x, offset_y, offset_z):
"""
Adjusts the position of the tello drone based on the offset values given from the frame
:param offset_x: Offset between center and face x coordinates
:param offset_y: Offset between center and face y coordinates
:param offset_z: Area of the face detection rectangle on the frame
"""
if not -90 <= offset_x <= 90 and offset_x is not 0:
if offset_x < 0:
drone.rotate_ccw(10)
elif offset_x > 0:
drone.rotate_cw(10)
if not -70 <= offset_y <= 70 and offset_y is not -30:
if offset_y < 0:
drone.move_up(20)
elif offset_y > 0:
drone.move_down(20)
def dji_a():
#!/usr/bin/env python
# coding: utf-8
# In[ ]:
import numpy as np
import cv2 as cv
import cv2
import tello_drone as tello
import dlib
import pyautogui
host = ''
port = 9000
local_address = (host, port)
detector = dlib.get_frontal_face_detector()
recog = cv2.face.LBPHFaceRecognizer_create()
recog.read("train.yml")
font = cv2.FONT_HERSHEY_SIMPLEX
# Pass the is_dummy flag to run the face detection on a local camera
drone = tello.Tello(host, port, is_dummy=False)
def adjust_tello_position(offset_x, offset_y, offset_z):
"""
Adjusts the position of the tello drone based on the offset values given from the frame
:param offset_x: Offset between center and face x coordinates
:param offset_y: Offset between center and face y coordinates
:param offset_z: Area of the face detection rectangle on the frame
"""
if not -90 <= offset_x <= 90 and offset_x is not 0:
if offset_x < 0:
drone.rotate_ccw(10)
elif offset_x > 0:
drone.rotate_cw(10)
if not -70 <= offset_y <= 70 and offset_y is not -30:
if offset_y < 0:
drone.move_up(20)
elif offset_y > 0:
drone.move_down(20)
if not 15000 <= offset_z <= 30000 and offset_z is not 0:
if offset_z < 15000:
drone.move_forward(20)
elif offset_z > 30000:
drone.move_backward(20)
face_cascade = cv.CascadeClassifier(
'cascades/haarcascade_frontalface_default.xml')
frame_read = drone.get_frame_read()
while True:
# frame = cv.cvtColor(frame_read.frame, cv.COLOR_BGR2RGB)
frame = frame_read.frame
cap = drone.get_video_capture()
height = cap.get(cv.CAP_PROP_FRAME_HEIGHT)
width = cap.get(cv.CAP_PROP_FRAME_WIDTH)
frame_d = frame.copy()
detected = detector(frame_d, 1)
if len(detected) > 0:
for i, d in enumerate(detected):
x1, y1, x2, y2, w, h = d.left(), d.top(), d.right(), d.bottom(
), d.width(), d.height()
cv2.rectangle(frame_d, (x1, y1), (x2, y2), (0, 255, 0), 2)
gray = cv2.cvtColor(frame_d[y1:y2, x1:x2], cv2.COLOR_BGR2GRAY)
Id, confidence = recog.predict(gray)
if (Id == 1):
Id = "Debanik {0:.2f}%".format(round(100 - confidence, 2))
im1 = pyautogui.screenshot()
im1.save("screen_short/" + "Debanik" + '.png')
if (Id == 2):
Id = "Payel {0:.2f}%".format(round(100 - confidence, 2))
im2 = pyautogui.screenshot()
im2.save("screen_short/" + "Payel" + '.png')
cv2.putText(frame_d, str(Id), (x1, y1 - 40), font, 1,
(0, 0, 255), 3)
# Calculate frame center
center_x = int(width / 2)
center_y = int(height / 2)
# Draw the center of the frame
cv.circle(frame, (center_x, center_y), 10, (0, 255, 0))
# Convert frame to grayscale in order to apply the haar cascade
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, minNeighbors=5)
# If a face is recognized, draw a rectangle over it and add it to the face list
face_center_x = center_x
face_center_y = center_y
z_area = 0
for face in faces:
(x, y, w, h) = face
cv.rectangle(frame, (x, y), (x + w, y + h), (255, 255, 255), 2)
face_center_x = x + int(h / 2)
face_center_y = y + int(w / 2)
z_area = w * h
cv.circle(frame, (face_center_x, face_center_y), 10, (0, 0, 255))
# Calculate recognized face offset from center
offset_x = face_center_x - center_x
# Add 30 so that the drone covers as much of the subject as possible
offset_y = face_center_y - center_y - 30
cv.putText(frame, f'[{offset_x}, {offset_y}, {z_area}]', (10, 50),
cv.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255), 2, cv.LINE_AA)
adjust_tello_position(offset_x, offset_y, z_area)
# Display the resulting frame
cv.imshow('Tello detection...', frame)
cv.imshow('Tello detection_face...', frame_d)
if cv.waitKey(1) == ord('q'):
break
# Stop the BackgroundFrameRead and land the drone
drone.end()
cv.destroyAllWindows()