I am trying to detect faces in opencv,but I'm running in some issues:
1-When I put the following syntax:gray = cv2.cvtColor(frames,cv2.COLOR_BGR2GRAY),it shows up in red and does not work.
2-The haarcascade also shows up in red:faces = face_cascade.detectMultiScale( gray,scaleFactor=1.1,minNeighbors=5,minSize=(30, 30),flags = cv2.CV_HAAR_SCALE_IMAGE).I tried to do like in some tutorials but it does not work.Would you have any idea?
Here is my code:
#importing packages
import cv2
import numpy as np
#variables
webcam = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
w_size = (700,500)
#turn the webcam on
while (True):
#reading camera and turing into frames
ret,frames = webcam.read()
frames = cv2.resize(frames,w_size)
#detection
gray = cv2.cvtColor(frames,cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale( gray,scaleFactor=1.1,minNeighbors=5,minSize=(30, 30),flags = cv2.CV_HAAR_SCALE_IMAGE)
for (x, y, w, h) in faces:
cv2.rectangle(frames, (x, y), (x+w, y+h), (0, 255, 0), 2)
cv2.imshow('face_recognition',frames)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
#running script
webcam.release()
cv2.destroyAllWindows()
i simply:
added cv2.data.haarcascades as prefix of the type CascadeClassifier
deleted cv2.CV_HAAR_SCALE_IMAGE (parameter not used anymore)
Code:
import cv2
import numpy as np
import cv2.data
#variables
webcam = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades+'haarcascade_frontalface_default.xml')
w_size = (700,500)
#turn the webcam on
while (True):
#reading camera and turing into frames
ret,frames = webcam.read()
frames = cv2.resize(frames,w_size)
#detection
gray = cv2.cvtColor(frames,cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale( gray,scaleFactor=1.1,minNeighbors=5,minSize=(30, 30))
for (x, y, w, h) in faces:
cv2.rectangle(frames, (x, y), (x+w, y+h), (0, 255, 0), 2)
cv2.imshow('face_recognition',frames)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
#running script
webcam.release()
cv2.destroyAllWindows()
Related
so, I'm trying to code face detection but its not working. this is my code:
import cv2
import sys
cascPath = sys.argv[0]
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'm very new to coding so I don't know if I'm missing something obvious
Change your code as follows:
faceCascade = cv2.CascadeClassifier(cv2.data.haarcascades + cascPath)
This worked for me.
I am trying to detect the human body through OpenCV. The code throws no error. The camera also starts but it is unable to detect anything.
import cv2
classifier = cv2.CascadeClassifier(r'C:\Users\dhruv\Desktop\DataScience\haarcascade_fullbody.xml')
video_captured = cv2.VideoCapture(0)
while (True):
ret, frame = video_captured.read()
frame = cv2.resize(frame,(640,360))
gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# pass the frame to the classifier
persons_detected = classifier.detectMultiScale(gray_frame)
# check if people were detected on the frame
for (x, y, w, h) in persons_detected:
cv2.rectangle(frame, (x,y), (x+w, y+h), (255, 0, 0), 2)
cv2.imshow('Video footage', frame)
if (cv2.waitKey(1) & 0xFF == ord('q')):
break
#cv2.VideoCapture(0).release()
I highly suspect its an indentation error. The camera does start, but your code to draw the bounding boxes of the faces are outside of the loop. Just indent that code. In addition, you'll need to free the camera resource properly or the next time you run the code, the camera will not be able to capture frames properly. I've changed the release call so that it releases the grabbed resource.
import cv2
classifier = cv2.CascadeClassifier(r'C:\Users\dhruv\Desktop\DataScience\haarcascade_fullbody.xml')
video_captured = cv2.VideoCapture(0)
while True:
ret, frame = video_captured.read()
frame = cv2.resize(frame,(640,360))
gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# pass the frame to the classifier
persons_detected = classifier.detectMultiScale(gray_frame)
# check if people were detected on the frame
for (x, y, w, h) in persons_detected:
cv2.rectangle(frame, (x,y), (x+w, y+h), (255, 0, 0), 2)
cv2.imshow('Video footage', frame)
if (cv2.waitKey(1) & 0xFF == ord('q')):
break
video_captured.release() # Changed so that you're releasing the grabbed resource
I am detecting a face from the camera and draw a rectangle around it.
Code below:
face_cascade = cv2.CascadeClassifier('face_classifier.xml')
def detect(gray, frame):
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in stops: # For each detected face:
cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
return frame
video_capture = cv2.VideoCapture(0)
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
Are there any functions in OpenCV that can print text?
When it detects a face on the screen say "Hi"?
Thank you for your time.
Should have done this first before asking the question but after some Googling and trying out a few things, here is the solution:
face_cascade = cv2.CascadeClassifier('face_classifier.xml')
def detect(gray, frame):
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in stops: # For each detected face:
cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
font = cv2.FONT_HERSHEY_COMPLEX_SMALL
cv2.putText(frame,'Hello There!',(x+w, h),font, 0.8,(255,0,0),2,cv2.LINE_AA)
return frame
video_capture = cv2.VideoCapture(0)
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
This will add "Hello There!" to the top right corner of the detection frame rectangle.
This code is to detect face and eyes using webcam but getting this error
Traceback (most recent call last):
File "D:/Acads/7.1 Sem/BTP/FaceDetect-master/6.py", line 28, in <module>
eyes = eyeCascade.detectMultiScale(roi)
NameError: name 'roi' is not defined
but when i use this code do detect faces and eyes in a image its working properly without any error
import matplotlib
import matplotlib.pyplot as plt
import cv2
import sys
import numpy as np
import os
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eyeCascade= cv2.CascadeClassifier('haarcascade_eye.xml')
video_capture = cv2.VideoCapture(0)
while True:
# Capture frame-by-frame
ret, frame = video_capture.read()
faces = faceCascade.detectMultiScale(frame)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
roi = frame[y:y+h, x:x+w]
eyes = eyeCascade.detectMultiScale(roi)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi,(ex,ey),(ex+ew,ey+eh), 255, 2)
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
I think it is just a problem of indentation.
roi is out of scope when you go out of the faces loop.
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
roi = frame[y:y+h, x:x+w]
# eyes detection runs for each face
eyes = eyeCascade.detectMultiScale(roi)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi,(ex,ey),(ex+ew,ey+eh), 255, 2)
I used the following code to detect a face using Haar cascade classifiers provided by OpenCv Python. But the faces are not detected and the square around the face is not drawn. How to solve this?
import cv2
index=raw_input("Enter the index No. : ")
cascPath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascPath)
cap = cv2.VideoCapture(0)
cont=0
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
# Our operations on the frame come here
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=10,
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.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
# Display the resulting frame
cv2.imshow('frame',frame)
inpt=cv2.waitKey(1)
if inpt & 0xFF == ord('q'):
break
elif inpt & 0xFF == ord('s') :
#name='G:\XCODRA\Integrated_v_01\EigenFaceRecognizer\img2'+index+"."+(str(cont))+".png"
name='IC_image\\'+index+"."+(str(cont))+".png"
resized = cv2.resize(gray,None,fx=200, fy=200, interpolation = cv2.INTER_AREA)
img=cv2.equalizeHist(resized)
cv2.imwrite(name,img)
print cont
cont+=1
Use the full path for the classifier.