I need to understand cv2.waitkey() in python with cv2
faceCascade = cv2.CascadeClassifier(cascPath)
video_capture = cv2.VideoCapture(0)
while True:
# Capture frame-by-frame
ret, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=8,
minSize=(40, 40),
#flags=cv2.cv.CV_HAAR_SCALE_IMAGE
flags = 0
)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(gray, (x, y), (x+w, y+h), (0, 255, 0), 2)
# Display the resulting frame
cv2.imshow('Video', gray)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
if cv2.waitKey(1) & 0xFF == ord('b'):
cv2.imwrite('example.png',gray)
cv2.waitKey() when I press b it doesn't save picture but press q works . Please help!
You are calling waitKey() twice. With your code, press any key but q then press b and it will save the image.
Only call waitKey(1) once, and save the result in a variable, then test that variable, e.g.:
keypress = cv2.waitKey(1)
if keypress & 0xFF == ord('q'):
break
if keypress & 0xFF == ord('b'):
cv2.imwrite('example.png',gray)
Related
I'm currently practicing opencv and tried the face recognition code and it's working fine. I'd like to get notified if I'm away from the screen for more than 2 mins. I'm trying to play an audio file when I'm away and stop it when I'm back.
import cv2 as cv
import sys
cascPath = sys.argv[1]
faceCascade = cv2.CascadeClassifier(cascPath)
video_capture = cv.VideoCapture(0)
while True:
# Capture frame-by-frame
ret, frame = video_capture.read()
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv.CASCADE_SCALE_IMAGE
)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
# Display the resulting frame
cv.imshow('Video', frame)
# check if the tuple faces is empty
if len(faces) == 0:
start_time = time.time()
while len(faces) == 0:
print('person is away for ',time.time()-start_time)
d_time = time.time()
if d_time-start_time > 120:
pygame.mixer.init()
sound = pygame.mixer.Sound("Recording.mp3")
sound.play(5)
if cv.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv.destroyAllWindows()
I am working on a face detection use case and want to print a message when the face is not detected in the frame, and draw the bounding box when the face is detected. I am using open-cv for the same
Here is my code so far, please let me know what changes need to be made.
import cv2
cascPath = 'haarcascade_frontalface_dataset.xml'
faceCascade = cv2.CascadeClassifier(cascPath)
video_capture = cv2.VideoCapture(0)
while True :
_, frame = video_capture.read(0)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# cv2.imshow("face detection", frame)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE
)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
if w == 0:
cv2.putText(frame,'No face',(0,130), font, 1, (200,255,155))
else:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
# Display the resulting frame in browser
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()
I figured out the solution, go through it if you want to have a look , just add this if statement before for loop, it writes no face in the window if no face is detected
if len(faces) == 0:
cv2.putText(frame,'No face',(0,130), 4,1, (200,255,155))
This guide in geeksforgeeks can help you. Also you can follow link on tproger, so I recommend to use google transltator.
https://www.geeksforgeeks.org/python-opencv-cv2-puttext-method/
https://tproger.ru/translations/opencv-python-guide/#text
import cv2
import sys
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
video_capture = cv2.VideoCapture(0)
img_counter = 0
while True:
# Capture frame-by-frame
ret, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
k = cv2.waitKey(1)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.5,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE
)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
# Display the resulting frame
cv2.imshow('FaceDetection', frame)
if k%256 == 27: #ESC Pressed
break
elif k%256 == 32:
# SPACE pressed
img_name = "facedetect_webcam_{}.png".format(img_counter)
cv2.imwrite(img_name, frame)
print("{} written!".format(img_name))
img_counter += 1
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()
after running the code in python the image of my webcam turn into this
Your code works for me without any problems.
The output image looks like there is a problem with the data type of the input image.
Something similar was discussed here:
https://answers.opencv.org/question/174027/c-ycbcr422-to-rgb-convert-from-raw-data-file/
Can you please also post your input frame grayscale image?
What camera are you using?
try add this code after video_capture.read() and post output.
print(frame.dtype)
print(frame.shape)
Mine is: dtype - uint8, shape - (480, 640, 3).
You can have a problem with the number of channels (for example RGBA) and rectangle function.
These are just my ideas of what could be wrong. But for me, your code works fine.
br Jozef
I am trying to detect objects from an mp4 video file using OpenCV in Python. I am able to detect the objects in the video.
I would like to get the timestamp of the position at which the object was detected in the video file and write it to a text file.
Here is my code so far:
import cv2
my_cascade = cv2.CascadeClassifier('toy.xml')
def detect(gray, frame):
toys= my_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in toys:
cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
#Logic to write time stamp to file goes here
return frame
video_capture = cv2.VideoCapture('home.mp4')
cv2.startWindowThread()
while True:
_, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
canvas = detect(gray, frame)
cv2.imshow('Video', canvas)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
I tried to use VideoCapture's method get() using property identifier like this:
video_capture.get(CV_CAP_PROP_POS_MSEC)
but get an error name 'CV_CAP_PROP_POS_MSEC' is not defined
Seems like cv2 does not have this method or property identifier implemented.
Is there any other way in cv2 to implement what I want?
Please help.
SOLVED
This will print timestamp of the position of object everytime it is detected in the video.
Here is the working code:
import cv2
my_cascade = cv2.CascadeClassifier('toy.xml')
def detect(gray, frame):
toys= my_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in toys:
cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
print("Toy Detected at: "+str(video_capture.get(cv2.CAP_PROP_POS_MSEC)))
return frame
video_capture = cv2.VideoCapture('home.mp4')
cv2.startWindowThread()
while True:
_, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
canvas = detect(gray, frame)
cv2.imshow('Video', canvas)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
cv2 does have the property implemented, but the full name needs to be used.
This should work
import cv2
my_cascade = cv2.CascadeClassifier('toy.xml')
def detect(gray, frame):
toys= my_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in toys:
cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
#Logic to write time stamp to file goes here
return frame
video_capture = cv2.VideoCapture('home.mp4')
cv2.startWindowThread()
while True:
_, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
canvas = detect(gray, frame)
print (video_capture.get(cv2.CAP_PROP_POS_MSEC))
cv2.imshow('Video', canvas)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
i.e. you want the property of the instance video_capture not the generic class VideoCapture and the property name is prefixed by the class cv2.. The property name is either CAP_PROP_POS_MSECor CV_CAP_PROP_MSEC - depending on the OpenCV version (see Can't get VideoCapture property as the property identifier are not defined ).
using opencv2, I tried to detect the human faces from webcam using the below code:-
import cv2
import sys
cascPath = sys.argv[1]
faceCascade = cv2.CascadeClassifier(cascPath)
video_capture = cv2.VideoCapture(0)
while True:
ret, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray,scaleFactor=1.1,minNeighbors=5,
minSize=(30, 30), flags=cv2.cv.CV_HAAR_SCALE_IMAGE)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
I am unable to execute the complete code as i got an error at the below step:-
ret, frame = video_capture.read() //error msg **expected an intended block**
Thanks,
breeze
Indenting is very important in Python, it forms the structure of the code. Your script would need to be indented something like as follows:
import cv2
import sys
cascPath = sys.argv[1]
faceCascade = cv2.CascadeClassifier(cascPath)
video_capture = cv2.VideoCapture(0)
while True:
ret, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, scaleFactor=1.1,
minNeighbors=5, minSize=(30, 30),
flags= cv2.cv.CV_HAAR_SCALE_IMAGE)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
To run this script for face recognition:
python myscript.py C:\opencv\build\etc\haarcascades\haarcascade_frontalface_default.xml