def get_video_rtsp(rtsp):
'''
excample:
>>> rtsp="rtsp://192.168.1.168:80/0"
>>> get_vedeo_rtsp(rtsp)
'''
import cv2
capture=cv2.videocapture(filename)
while(1):
ret,frame=capture.read()
if frame is None:
break
cv2.imshow('img',frame)
if cv2.waitKey(1) == 27:
break
capture.release()
cv2.destroyAllWindows()
import cv2
import numpy as np
faceDetect=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
cam=cv2.videocapture(0)
id=raw_input('emter user id')
sampleNum=0
while(True):
ret,img=cam.read()
gray=cv2.cvtcolor(img,cv2.COLOR_BGR2GRAY)
faces=faceDetect.detectMultiScale(gray,1.3,5)
for(x,y,w,h) in faces:
sampleNum=sampleNum+1
cv2.imwrite("dataset/user."+str(id)+"."+str(sampleNum)+".jpg")
cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,255),2)
cv2.waitKey(100)
cv2.imshow("face",img)
cv2.waitKey(10)
if(sampleNum>60):
break
cam.release()
cv2.destroyAllWindows()
import cv2
#calling classifirer
casclf = cv2.CascadeClassifier('face.xml')
#loading face data
cap = cv2.videocapture(2)
while cap.isOpened():
status, frame = cap.read()
#applying classifier in live frame
face = casclf.detectMultiscale(frame, 1.13,
5) #classifier turning paramete
# print(face)
for x, y, h, w in face:
cv2.rectangle(frame, (x, y), (x + h, y + w), (0, 0, 255), 2)
#onlyface
#facedata=frame[x:x+h,y:y+w]
#cv2.imshow('f',facedata)
cv2.imshow('face', frame)
if cv2.waitkey(10) & 0xff == ord('q'):
break
cv2.destroyAllWindows()
cap.release()
# Put the coordinates of contour on the screen and have them move with the object
cv2.putText(frame, "X: " + format(x),
(int(x) - 60, int(y) + 50), font, 0.6,
(155, 250, 55), 2, cv2.LINE_AA)
cv2.putText(frame, "Y: " + format(y),
(int(x) - 60, int(y) + 70), font, 0.6,
(155, 255, 155), 2, cv2.LINE_AA)
cv2.putText(frame, "W: " + format(w),
(int(x) - 60, int(y) + 90), font, 0.6,
(215, 250, 55), 2, cv2.LINE_AA)
cv2.putText(frame, "H: " + format(h),
(int(x) - 60, int(y) + 110), font, 0.6,
(155, 250, 155), 2, cv2.LINE_AA)
cX = cX + centerX
cY = cY + centerY
if len(contours) == 2:
cX = cX / 2
cY = cY / 2
return len(contours), cX, cY
if __name__ == 'main':
cap = cv2.videocapture('../video/GOPRO281.mp4')
frame, ret = cap
tasks = Tasks(frame)
data = tasks.findObject("qualGate")
#img, (x,y) , (width,height) (color in bgr) , border_thickness
cv2.rectangle(img, (10, 10), (150, 150), (255, 0, 0), 4)
#img ,text , (x,y), font face,scale(font size) , color in bgr,thickness
cv2.putText(img, "Bahubali", (20, 20), font, 1, (255, 0, 0), 2)
while True:
cv2.imshow('image', img)
#1 ms of delay for windows switching
if cv2.waitKey(1) == 27:
break
cv2.destroyAllWindows()
capture = cv2.videocapture(0)
i = 0
while True:
ret, img = capture.read()
if ret:
cv2.imshow('result', img)
i += 1
cv2.imwrite('img_{}'.format(i), img)
if cv2.waitkey(1) == 27:
break
else:
print('Camera not Working')
cv2.destroyAllWindows()
import cv2
cameracapture = cv2.videocapture(0)
fps = 30
size = (int(cameracapture.get(CAP_PROP_FRAME_WIDTH)),
int(cameracapture.get(CAP_PROP_FRAME_HEIGHT)))
videowriter = cv2.videoWriter('MyOutputVid.avi',
cv2.VideoWriter_fourcc('I', '4', '2', '0'), fps,
size)
success, frame = cameracapture.read()
frames_remaning = 10 * fps - 1
while success and frames_remaning > 0:
videowriter.write(frame)
success, frame = cameracapture.read()
frames_remaning = frames_remaning - 1
cameracapture.release()
# an appropriate timer for capturing the frames is the best way to proceed
#READING AND UNDERSTANDING QR CODE
import cv2
from pyzbar.pyzbar import decode
capture = cv2.videocapture(0) #DEFAULT CAMERA
while True:
_, instantpic = capture.read()
decodeddata = decode(instantpic)
NETDATA = decodeddata[0][0] #FOR ACCESING THE TEXT PART ONLY
cv2.imshow("qr",instantpic)
key = cv2.waitKey(5)
if key == ord(POWER HANDLE): #FIRST RED SWITCH
break
#to read out text
from _tkinter import *
import pyttsx3
engine = pyttsx3.init()
engine.say(NETDATA)
engine.runAndWait()
#FOR CAPTURING EMERGENCY PIC AND SAVING
import time
emergencypic = cv2.videocapture(0)
files = natural_sort(glob.glob(folder))
assert len(files) > 0, "Folder empty, make sure to provide a correct path"
print(f'loading {len(files)} files')
map_length = len(files[1:])
mapped = list(
zip(files, files[1:], [row_stride] * map_length,
[col_stride] * map_length))
with ThreadPool(processes=8) as p:
result = list(tqdm(p.imap(threaded_flow, mapped), total=len(mapped)))
return result
if __name__ == '__main__':
cap = cv.videocapture('video/train.mp4')
ret, frame1 = cap.read()
flows = []
while cap.isopened():
ret, frame2 = cap.read()
if not ret:
break
flow = calc_flow(frame1, frame2)
im = draw_flow(frame1, flow)
avg_flow = calc_avg_flow(flow)
im = draw_avg_flow(frame1, avg_flow)
flows.append(avg_flow)
cv.imshow('avg flow', im)
cv.waitkey(30)