def main():
last_time = time.time()
a = 1
while (True):
a = 2
screenshot = ImageGrab.grab(bbox=(0, 40, 800, 640))
new_screen, m1, m2 = process(screenshot)
#cv2.imshow("Edges",new_screen)
#cv2.imshow("window",cv2.cvtColor(np.array(screenshot),cv2.COLOR_BGR2RGB))
#print("Frame took seconds = " , end = '')
#print(time.time()-last_time)
#print(m1,m2)
#print(m1,m2)
if abs(m1) - abs(m2) == 0:
#none()
print('reversing')
print(m1 + m2)
if abs(m2) > abs(m1):
#right()
print('right')
print(m1 + m2)
elif abs(m2) < abs(m1):
#left()
print("left")
print(m1 + m2)
last_time = time.time()
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyALLWindows()
break
def showVideo():
try:
print('카메라를 구동합니다')
cap = cv2.VideoCapture(0)
except:
print('카메라 구동 실패')
return
cap.set(3, 480)
cap.set(4, 320)
while True:
ret, frame = cap.read()
if not ret:
print('비디오 읽기 오류')
break
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imshow('video', gray)
k = cv2.waitKey(1) & OXFF
if k == 27:
break
cap.release()
cv2.destroyALLWindows()
def showimage():
imgfile = 'images/7-1.jpg'
img = cv2.imread(imgfile, cv2.IMREAD_UNCHANGED) #이미지 읽기 플래그는 총 3가지가 있다.
cv2.namedWindow('7-1', cv2.WINDOW_AUTOSIZE) #이미지 크기를 변경
cv2.imshow('7-1', img)
cv2.waitKey(0)
cv2.destroyALLWindows()
def main(template, ImageA):
aImage = cv2.imread(ImageA)
temp = cv2.imread(template, 0)
aCopy = aImage.copy()
aImage = cv2.cvtColor(aImage, cv2.COLOR_BGR2GRAY)
th, tw = temp.shape[:2]
match = cv2.matchTemplate(aImage, temp, cv2.TM_SQDIFF)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(match)
topcorner = min_loc
bottomcorner = (topcorner[0] + tw, topcorner[1] + th)
cv2.rectangle(aCopy, topcorner, bottomcorner, (0, 0, 255), 2)
cv2.imshow('template', aCopy)
if cv2.waitKey(0) & 0xFF == ord('q'):
cv2.imwrite('template.jpg', aCopy)
cv2.destroyALLWindows()
def main():
gpu_options = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=1)
sess = tf.compat.v1.Session(config=tf.compat.v1.ConfigProto(gpu_options=gpu_options))
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
print("GPU device: ", tf.test.gpu_device_name())
font = cv2.FONT_HERSHEY_SIMPLEX
cap = cv2.VideoCapture(0)
fps_start_time = datetime.datetime.now()
fps = 0
total_frames = 0
while True:
ret, frame = cap.read()
total_frames = total_frames+1
fps_end_time = datetime.datetime.now()
time_diff = fps_end_time - fps_start_time
if time_diff.seconds == 0:
fps = 0.0
else:
fps = total_frames/time_diff.seconds
fps_text = "FPS: {:.2f}".format(fps)
cv2.putText(frame, fps_text, (5,30), font, 1, (0, 0, 255), 1, cv2.LINE_AA)
cv2.imshow("Application", frame)
key = cv2.waitKey(1)
if key == ord('q'):
break
cv2.destroyALLWindows()
import cv2
import numpy as np
cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
cap.open(0)
while cap.isOpened():
flag, frame = cap.read()
if not flag:
break
key_pressed = cv2.waitKey(60)
print('blackboard is ', key_pressed)
frame = cv2.Canny(frame, 20, 40)
frame = np.dstack((frame, frame, frame))
cv2.imshow('mygook', frame)
if key_pressed == 27:
break
cap.release()
cv2.destroyALLWindows()
#Reading Videos
import cv2 as cv #importing openCV library
capture = cv.VideoCapture('Videos/dog.mp4') #defining video for the program
while True:
isTrue, frame = capture.read() #divides the video frame by frame
cv.imshow('Video', frame) #reading frames of video
if cv.waitKey(20) & 0xFF == ord(
'd'): #if letter d is pressed break the loop
break
capture.release() #release capture device
cv.destroyALLWindows() #close the window
def main():
# note make sure the img_shape = (225, 225)
# if you are chaning this make sure to update the code in the model
model = load_model("rock-paper-scissors-model.h5")
#_________________________________
# once you have written the code to play the game uncommend the below lines
# and place them where required so that the model can predict
# pred = model.predict(np.array([img]))
# move_made_by_you = mapper(np.argmax(pred[0]))
# ______________________
cap = cv2.VideoCapture(0)
prev_move = None
while True:
ret, frame = cap.read()
if not ret:
continue
cv2.rectangle(frame, (100, 100), (500, 500), (255, 255, 255), 2) #user
cv2.rectangle(frame, (800, 100), (1200, 500), (255, 255, 255),
2) #computer
roi = frame[100:500, 100:500]
img = cv2.cvtColor(roi, cv2.COLOR_BGR2RGB)
img = cv2.GaussianBlur(img, (5, 5), 0)
img = cv2.Canny(img, 50, 60)
img = cv2.resize(img, (255, 255))
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img = cv2.resize(img, (255, 255))
pred = model.predict(np.array([img]))
user_move = mapper(np.argmax(pred[0]))
# ..and the winner is:
if prev_move != user_move:
if user_move != 'empty':
computer_move = choice(['rock', 'paper', 'scissor'])
winner = find_winner(user_move, computer_move)
else:
computer_move = 'empty'
winner = 'waiting...'
prev_move = user_move
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(frame, "Your Move: " + user_move, (50, 50), font, 1.2,
(255, 255, 255), 2, cv2.LINE_AA)
cv2.putText(frame, "Computer's Move: " + computer_move, (750, 50),
font, 1.2, (255, 255, 255), 2, cv2.LINE_AA)
cv2.putText(frame, "Winner: " + winner, (400, 600), font, 2,
(0, 0, 255), 4, cv2.LINE_AA)
if computer_move != 'empty':
computer_img = cv2.imread(
'E:/Projects/RPS/computer_images/{}.jpg'.format(computer_move))
computer_img = cv2.resize(computer_img, (400, 400))
frame[100:500, 800:1200] = computer_img
cv2.imshow("rock paper scissor", frame)
k = cv2.waitKey(10)
if k == ord('q'):
break
cap.release()
cv2.destroyALLWindows()
GPIO.output(23, 0)
i=GPIO.input(18)
if i==True:
if obj==True:
while(True):
f,frame=cap.read()
if f == False:
break
cv2.namedWindow("test", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("test", cv2.WND_PROP_FULLSCREEN, cv2.cv.CV_WINDOW_FULLSCREEN)
cv2.imshow("test", frame)
ch=cv2.waitKey(10)
if ch==27:
break
cap.release()
cv2.destroyALLWindows()
GPIO.output(23, 1)
time.sleep(1)
print "GPIO.cleanup()"
GPIO.cleanup()
def Main():
consumer_key = 'xxxx'
consumer_secret = 'xxxx'
access_token_key = 'xxxx'
access_token_secret = 'xxxx'
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token_key, access_token_secret)
HOST = socket.gethostbyname('0.0.0.0')
PORT = int(5000)
s = socket.socket(socket.AF_INET,
socket.SOCK_STREAM) #create socket (family,type)
print('Socket created')
s.bind(('', 5000)) #bind socket to adress
print('Socket bind complete')
s.listen(1) #listen to the connections made to the socket
print('Socket now listening')
conn, addr = s.accept(
) #accept a conection-conn is a new socket object , address bound to the socket on the other end of the connection
mess = "Thank you for connecting"
conn.send(mess.encode())
data = b'' #bites literal
c = 0
payload_size = struct.calcsize("L") #unsigned long size
while True:
while len(data) < payload_size:
data += conn.recv(
4096) #recv data from socket - 4096 max amount of data
c = c + 1
packed_msg_size = data[:payload_size]
data = data[payload_size:]
msg_size = struct.unpack(
"L", packed_msg_size)[0] #unpack according to the str
while len(data) < msg_size:
data += conn.recv(4096)
frame_data = data[:msg_size]
data = data[msg_size:]
img = pickle.loads(
frame_data,
encoding='latin1') #read a pickled object hierarchy from a string
face_cascade = cv2.CascadeClassifier(
'C:/Users/Alex/Desktop/face.txt') #load face cascade
eye_cascade = cv2.CascadeClassifier(
'C:/Users/Alex/Desktop/eye.txt') #load eye cascade
gray = cv2.cvtColor(
img, cv2.COLOR_BGR2GRAY) #convert data from camera to gray
faces = face_cascade.detectMultiScale(
gray
) #Detects faces of different sizes in the input image returned as a list of rectangles
if len(faces) > 0:
api = tweepy.API(auth)
t = time.strftime("%d-%m-%Y %H:%M:%S", time.gmtime())
facess = str(faces)
msg = "Alert !! Face detected at " + t + " : " + facess
# api.update_status(msg)
cv2.imwrite('opencv.png', img)
api.update_with_media('opencv.png', msg)
os.system("shutdown.exe /l")
for (x, y, w, h) in faces:
if c < 5:
cv2.rectangle(
img, (x, y), (x + w, y + h), (255, 0, 0), 2
) #draw rectangle (x,y) start point, end point, blue, alignment
roi_gray = gray[y:y + h, x:x + w] #start point, end point
roi_color = img[y:y + h, x:x + w] #for reimpose
eyes = eye_cascade.detectMultiScale(
roi_gray
) #Detects eyes of different sizes in the input image returned as a list of rectangles
print(c)
for (ex, ey, ew, eh) in eyes:
cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh),
(0, 255, 0), 2) #draw green rectangle
cv2.imshow('img', img)
k = cv2.waitKey(
30
) & 0xff #waits for specified milliseconds for any keyboard event (esc)
if k == 27:
break
cv2.destroyALLWindows() #destroys all of the opened HighGUI windows
