I am making a Face Liveliness detection program with OpenCV and Keras.
I am stuck with this error:
OpenCV assertion failed with negative values
I tried all the suggested answers but none of them solved my issue.
I have already tried all the solutions which are present on StackOverflow and Github issues but none of them worked out in my case.
video_capture = cv2.VideoCapture(0)
model = load_model()
print("[LOG] COLLECTING images.....")
images = []
for direc, _, files in tqdm(os.walk(dataset)):
for file in files:
if file.endswith("jpg"):
images.append(os.path.join(direc, file))
return model, face_detector, open_eyes_detector, left_eye__detector, right_eye_detector, video_capture, images
def process_and_encode(images):
known_encodings = []
known_names = []
print("[LOG] Encoding faces....")
for image_path in tqdm(images):
image = cv2.imread(image_path)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
boxes = face_recognition.face_locations(image, model='hog')
encoding = face_recognition.face_encodings(image, boxes)
name = image_path.split(os.path.sep)[-2]
if len(encoding) > 0:
known_encodings.append(encoding[0])
known_names.append(name)
return {"encodings": known_encodings, "names": known_names}
def detect_and_display(model, video_capture, face_detector, open_eyes_detector, left_eye_detector, right_eye_detector,
data, eyes_detected):
frame = video_capture.read()
try:
frame = cv2.resize(frame, (0, 0), fx=0.6, fy=0.6)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
faces = face_detector.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=5,
minSize=(50, 50),
flags=cv2.CASCADE_SCALE_IMAGE
)
for (x, y, w, h) in faces:
encoding = face_recognition.face_encodings(rgb, [(y, x + w, y + h, x)])
matches = face_recognition.compare_faces(data["encodings"], encoding)
name = "Unknown"
if True in matches:
matchedIdxs = [i for (i, b) in enumerate(matches) if b]
counts = {}
for i in matchedIdxs:
name = data["names"][i]
counts[name] = counts.get(name, 0) + 1
name = max(counts, key=counts.get)
face = frame[y:y + h, x:x + w]
gray_face = gray[y:y + h, x:x + w]
eyes = []
open_eyes_glasses = open_eyes_detector.detectMultiScale(
gray_face,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE
)
if len(open_eyes_glasses) == 2:
eyes_detected[name] += '1'
for (ex, ey, ew, eh) in open_eyes_glasses:
cv2.rectangle(face, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
# otherwise try detecting eyes using left and right_eye_detector
# which can detect open and closed eyes
else:
# separate the face into left and right sides
left_face = frame[y:y + h, x + int(w / 2):x + w]
left_face_gray = gray[y:y + h, x + int(w / 2):x + w]
right_face = frame[y:y + h, x:x + int(w / 2)]
right_face_gray = gray[y:y + h, x:x + int(w / 2)]
# Detect the left eye
left_eye = left_eye_detector.detectMultiScale(
left_face_gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE
)
# Detect the right eye
right_eye = right_eye_detector.detectMultiScale(
right_face_gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE
)
eye_status = '1' # we suppose the eyes are open
# For each eye check wether the eye is closed.
# If one is closed we conclude the eyes are closed
for (ex, ey, ew, eh) in right_eye:
color = (0, 255, 0)
pred = predict(right_face[ey:ey + eh, ex:ex + ew], model)
if pred == 'closed':
eye_status = '0'
color = (0, 0, 255)
cv2.rectangle(right_face, (ex, ey), (ex + ew, ey + eh), color, 2)
for (ex, ey, ew, eh) in left_eye:
color = (0, 255, 0)
pred = predict(left_face[ey:ey + eh, ex:ex + ew], model)
if pred == 'closed':
eye_status = '0'
color = (0, 0, 255)
cv2.rectangle(left_face, (ex, ey), (ex + ew, ey + eh), color, 2)
eyes_detected[name] += eye_status
# Each time, we check if the person has blinked
# If yes, we display its name
if isBlinking(eyes_detected[name], 3):
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
# Display name
y = y - 15 if y - 15 > 15 else y + 15
cv2.putText(frame, name, (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 255, 0), 2)
return frame
except Exception as e:
print(str(e))
if __name__ == "__main__":
(model, face_detector, open_eyes_detector, left_eye_detector, right_eye_detector, video_capture, images) = init()
data = process_and_encode(images)
eyes_detected = defaultdict(str)
while True:
frame = detect_and_display(model, video_capture, face_detector, open_eyes_detector, left_eye_detector,
right_eye_detector, data, eyes_detected)
cv2.imshow("Face Liveness Detector", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.destroyAllWindows()
video_capture.stop()
Error message:-
Expected cv::UMat for argument 'src'
Traceback (most recent call last):
File "C:/Users/Saksham Dubey/PycharmProjects/FacePay/FaceLive.py", line 190, in
cv2.imshow("Face Liveness Detector", frame)
cv2.error: OpenCV(4.1.0) C:\projects\opencv-python\opencv\modules\highgui\src\window.cpp:352: error: (-215:Assertion failed) size.width>0 && size.height>0 in function 'cv::imshow'
[ WARN:0] terminating async callback
That could probably be because you try to use imshow() but there have been no imwite() before. Not exactly a solution but a working example. Take a look:
import cv2 # pip install opencv-python
import datetime
from cv2.data import haarcascades as hc
import requests
cap = cv2.VideoCapture(0)
faceCascade = cv2.CascadeClassifier("%s/haarcascade_frontalface_default.xml" % hc)
eye_cascade = cv2.CascadeClassifier('%s/haarcascade_eye.xml' % hc)
profile_cascade = cv2.CascadeClassifier('%s/haarcascade_profileface.xml' % hc)
fullbody_cascade = cv2.CascadeClassifier('%s/haarcascade_fullbody.xml' % hc)
smile_cascade = cv2.CascadeClassifier('%s/haarcascade_smile.xml' % hc)
eyesglasses_cascade = cv2.CascadeClassifier('%s/haarcascade_eye_tree_eyeglasses.xml' % hc)
mouth_cascade = cv2.CascadeClassifier('%s/haarcascade_mcs_mouth.xml' % hc)
filename = 'output/'+datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S')
def recognizer():
while True:
ret, frame = cap.read()
profile_count = recognize_profile(frame)
face_count, eye_count = recognize_face(frame, True)
cv2.imwrite('%s.png' % filename, frame)
image = cv2.imread('%s.png' % filename)
cv2.imshow('image', image)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
def recognize_profile(frame):
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
profiles = profile_cascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30)
# flags = cv2.CV_HAAR_SCALE_IMAGE
)
for (x, y, w, h) in profiles:
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
return len(profiles)
def recognize_face(frame, recognize_eyes=None):
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30)
# flags = cv2.CV_HAAR_SCALE_IMAGE
)
eyes = []
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
if recognize_eyes:
roi_gray = gray[y:y + h, x:x + w]
roi_color = frame[y:y + h, x:x + w]
eyes = eye_cascade.detectMultiScale(roi_gray)
# draw bounding boxes around detected features
for (ex, ey, ew, eh) in eyes:
eye_center = (ex + ew // 2, ey + eh // 2)
radius = int(round((ew + eh) * 0.25))
cv2.circle(roi_color, eye_center, radius, (0, 0, 255), 4)
return len(faces), len(eyes)
def snapshot():
while True:
# Capture frame-by-frame
ret, frame = cap.read()
recognize_profile(frame)
recognize_face(frame, True)
cv2.imwrite('%s.png' % filename, frame)
# if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
def live_video_recognizer():
frame_width = int(cap.get(3))
frame_height = int(cap.get(4))
out = cv2.VideoWriter('%s.avi' % filename, cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 10, (frame_width, frame_height))
while True:
ret, frame = cap.read()
recognize_profile(frame)
recognize_face(frame, True)
if ret is True:
out.write(frame)
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
break
cap.release()
out.release()
cv2.destroyAllWindows()
recognizer()
# snapshot()
# live_video_recognizer()
Related
I'm using
OS : Ubuntu
Python : 3.8*
Opencv version: 4.6.0
What I'm trying to do is capture the emotion & save the feed..For that I've used opencv 4.0
Code I've
while True:
ret, frame = cap.read()
frame = cv2.resize(frame, (720, 480))
if not ret:
break
grayFrame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
rects = detector(grayFrame, 0)
for rect in rects:
shape = predictor(grayFrame, rect)
points = shapePoints(shape)
(x, y, w, h) = rectPoints(rect)
grayFace = grayFrame[y:y + h, x:x + w]
try:
grayFace = cv2.resize(grayFace, (emotionTargetSize))
except:
continue
grayFace = grayFace.astype('float32')
grayFace = grayFace / 255.0
grayFace = (grayFace - 0.5) * 2.0
grayFace = np.expand_dims(grayFace, 0)
grayFace = np.expand_dims(grayFace, -1)
emotion_prediction = emotionClassifier.predict(grayFace)
emotion_probability = np.max(emotion_prediction)
if (emotion_probability > 0.36):
emotion_label_arg = np.argmax(emotion_prediction)
color = emotions[emotion_label_arg]['color']
cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
cv2.line(frame, (x, y + h), (x + 20, y + h + 20),
color,
thickness=2)
cv2.rectangle(frame, (x + 20, y + h + 20), (x + 110, y + h + 40),
color, -1)
cv2.putText(frame, emotions[emotion_label_arg]['emotion'],
(x + 25, y + h + 36), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
(255, 255, 255), 1, cv2.LINE_AA)
else:
color = (255, 255, 255)
cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
out.write(frame)
#Wait for user input - q, then you will stop the loop
k = cv2.waitKey(1)
if k == 27:
break
cap.release()
if args["isVideoWriter"] == True:
videoWrite.release()
cv2.destroyAllWindows()
Here Issue with wait key ...when I hit on esc program is not exiting...I've tried all the possible methods...the only method that working is keyboard interruption i.e, ctrl+c
Method1: Not working :(
c = cv2.waitKey(0) % 256
if c == ord('a'):
break
Method 2: Not working :(
if cv2.waitKey(0) & 0xFF == ord('q'):
break
Did i missing anything?...Thanks in advance
i am trying face recognition with opencv's LBPH with GUI made by tkinter. the first time my program runs . but when i exit camera with 'q' button and start again with push button in GUI it gives error. i have tried many workarounds but still no answer. can someone help me out?
HERE IS MY CODE
recognizer.read('C:/data.yml')
id = 0
# set text style
fontface = cv2.FONT_HERSHEY_SIMPLEX
fontscale = 1
fontcolor = (203, 23, 252)
cam = cv2.VideoCapture(0)
name_to_track=value_.get()
print(name_to_track)
# get data from sqlite by ID
while (True):
# camera read
ret, img = cam.read()
rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
result = face.process(rgb)
if result.detections:
for id_, detect in enumerate(result.detections):
bbox_ = detect.location_data.relative_bounding_box
ih, iw, ic = img.shape
bbox = int(bbox_.xmin * iw), int(bbox_.ymin * ih), \
int(bbox_.width * iw), int(bbox_.height * ih)
x = bbox[0]
y = bbox[1]
w = bbox[2]
h = bbox[3]
cv2.rectangle(img, bbox, (255, 0, 255), 2)
img_size=gray[y:y + h, x:x + w]
img_size=np.array(img_size)
print("x:"+str(x)+"y:"+str(y))
if(x<0 or y<0 or w <0 or h<0):
continue
id, conf = recognizer.predict(gray[y:y + h, x:x + w])
#print(conf)
if (conf < 50):
profile = getProfile(id)
# set text to window
if (profile != None):
# cv2.PutText(cv2.fromarray(img),str(id),(x+y+h),font,(0,0,255),2);
cv2.putText(img, "ID: " + str(profile[0]) + ' Acc:' + str(round(float(1 - conf / 100), 2)),
(x, y + h + 30), fontface, fontscale, fontcolor, 2)
if (profile[1] == name_to_track):
cv2.putText(img, "Tracking", (x, y + h + 60), fontface, fontscale, fontcolor, 2)
else:
cv2.putText(img, "Name " + str(profile[1]), (x, y + h + 60), fontface, fontscale, fontcolor, 2)
else:
cv2.putText(img, "Unknown", (x, y + h + 30), fontface, fontscale, [255, 0, 0], 2)
cv2.imshow("face", img)
if cv2.waitKey(1) == ord('q'):
break
cam.release()
cv2.destroyAllWindows()
THANKS!!
My original idea can be seen in the code below but it's still detecting eyes on the lower half of my face. The goal is to make it only scan the upper half of my face, therefore weeding out incorrect matches.
import cv2
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
cap = cv2.VideoCapture(0) # sets up webcam
while 1: # capture frame, converts to greyscale, looks for faces
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces: # draws box around face
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
roi_gray = gray[y:y + h, x:x + w]
roi_color = img[y:y + h, x:x + w]
half_point = y
print("half point: " + str(half_point))
eyes = eye_cascade.detectMultiScale(roi_gray) # looks for eyes
for (ex, ey, ew, eh) in eyes: # draws boxes around eyes
check_point = ey
print("check_point: " + str(check_point))
if check_point > half_point:
pass
else:
cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
cv2.imshow('img', img)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
I only modified the line 15 and 16
cv2.rectangle(img, (x, y), (x + w, y + int(h / 2)), (255, 0, 0), 2)
roi_gray = gray[y:y + int(h / 2), x:x + w]
The full code:
import cv2
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
cap = cv2.VideoCapture(0) # sets up webcam
while 1: # capture frame, converts to greyscale, looks for faces
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces: # draws box around face
cv2.rectangle(img, (x, y), (x + w, y + int(h / 2)), (255, 0, 0), 2) #Modified
roi_gray = gray[y:y + int(h / 2), x:x + w] #Modified
roi_color = img[y:y + h, x:x + w]
half_point = y
print("half point: " + str(half_point))
eyes = eye_cascade.detectMultiScale(roi_gray) # looks for eyes
for (ex, ey, ew, eh) in eyes: # draws boxes around eyes
check_point = ey
print("check_point: " + str(check_point))
if check_point > half_point:
pass
else:
cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
cv2.imshow('img', img)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
But, I recommend to use dlib insead. It's more reliable.
Here is my example:
import numpy as np
import cv2
import dlib
cap = cv2.VideoCapture(0)
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
detector = dlib.get_frontal_face_detector()
def draw_on_frame(eye):
coordinates = np.array([])
for i in eye:
x = landmarks.part(i).x
y = landmarks.part(i).y
cv2.circle(frame, (x, y), 3, (0, 0, 255), -1)
coordinates = np.append(coordinates, [x, y])
x1, y1, w1, h1 = cv2.boundingRect(coordinates.reshape(-1, 2).astype(int))
cv2.rectangle(frame, (x1, y1), (x1 + w1, y1 + h1), (0, 255, 0), 1)
return x1, y1, w1, h1
while (cap.isOpened()):
ret, frame = cap.read()
if ret == True:
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = detector(gray)
for face in faces:
landmarks = predictor(gray, face)
left_eye = range(36, 42)
right_eye = range(42, 48)
left = draw_on_frame(left_eye)
right = draw_on_frame(right_eye)
roi_left = frame[left[1]:left[1]+left[3], left[0]:left[0]+left[2]]
roi_right = frame[right[1]:right[1] + right[3], right[0]:right[0] + right[2]]
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
break
cap.release()
cv2.destroyAllWindows()
I have three IP cameras around my house and I want to capture an image when a motion is detected. I want to run the motion capture algorithm in the same time for all 3 cameras.
I manage to do the job for one camera - Open the stream + motion detection algorithm + store image in case of detection :
import cv2
cap3 = cv2.VideoCapture('http://X.X.X.X:XXXX/stream.mjpg')
ret3, frame31 = cap3.read()
ret3, frame32 = cap3.read()
while (True):
diff3 = cv2.absdiff(frame31, frame32)
gray3 = cv2.cvtColor(diff3, cv2.COLOR_BGR2GRAY)
blur3 = cv2.GaussianBlur(gray3, (5, 5), 0)
_, tresh3 = cv2.threshold(blur3, 30, 255, cv2.THRESH_BINARY)
dilated3 = cv2.dilate(tresh3, None, iterations=3)
contours3, _ = cv2.findContours(dilated3, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours3:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 800:
continue
cv2.rectangle(frame31, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame31, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = "RASP" + str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame31)
frame31 = frame32
ret3, frame32 = cap3.read()
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap3.release()
cv2.destroyAllWindows()
The problem I have is when I try to do the same job in parallel for the three cameras.
What I do is duplicating the same process in the while loop for the three cameras and when I do so, it starts running for a few seconds and then I get this error :
Traceback (most recent call last):
File "C:/Users/Guillaume/PycharmProjects/IPCAM/IPCAM2.py", line 54, in <module>
gray2 = cv2.cvtColor(diff2, cv2.COLOR_BGR2GRAY)
cv2.error: OpenCV(4.2.0) C:\projects\opencv-python\opencv\modules\imgproc\src\color.cpp:182: error: (-215:Assertion failed) !_src.empty() in function 'cv::cvtColor'
The code I run in below :
import cv2
import numpy as np
from datetime import datetime
import time
cap2 = cv2.VideoCapture('rtsp://') # IPCAM2
cap = cv2.VideoCapture('rtsp://') # IPCAM1
cap3 = cv2.VideoCapture('http://') # RASP
def rescale_frame(frame, percent=75):
width = int(frame.shape[1] * percent / 100)
height = int(frame.shape[0] * percent / 100)
dim = (width, height)
return cv2.resize(frame, dim, interpolation=cv2.INTER_AREA)
while (True):
ret1, frame11 = cap.read()
ret1, frame12 = cap.read()
ret2, frame21 = cap2.read()
ret2, frame22 = cap2.read()
ret3, frame31 = cap3.read()
ret3, frame32 = cap3.read()
diff1 = cv2.absdiff(frame11, frame12)
gray1 = cv2.cvtColor(diff1, cv2.COLOR_BGR2GRAY)
blur1 = cv2.GaussianBlur(gray1, (5, 5), 0)
_, tresh1 = cv2.threshold(blur1, 40, 255, cv2.THRESH_BINARY)
dilated1 = cv2.dilate(tresh1, None, iterations=3)
contours1, _ = cv2.findContours(dilated1, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours1:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 1000:
continue
cv2.rectangle(frame11, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame11, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame11)
# cv2.line(frame, (0, 300), (200, 200), (0, 255, 0), 5)
resizedframe11 = rescale_frame(frame11, percent=75)
cv2.imshow('frame', resizedframe11)
frame11 = frame12
ret1, frame12 = cap.read()
diff2 = cv2.absdiff(frame21, frame22)
gray2 = cv2.cvtColor(diff2, cv2.COLOR_BGR2GRAY)
blur2 = cv2.GaussianBlur(gray2, (5, 5), 0)
_, tresh2 = cv2.threshold(blur2, 40, 255, cv2.THRESH_BINARY)
dilated2 = cv2.dilate(tresh2, None, iterations=3)
contours2, _ = cv2.findContours(dilated2, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours2:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 1000:
continue
cv2.rectangle(frame21, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame21, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame21)
resizedframe21 = rescale_frame(frame21, percent=75)
cv2.imshow('frame2', resizedframe21)
frame21 = frame22
ret2, frame22 = cap2.read()
diff3 = cv2.absdiff(frame31, frame32)
gray3 = cv2.cvtColor(diff3, cv2.COLOR_BGR2GRAY)
blur3 = cv2.GaussianBlur(gray3, (5, 5), 0)
_, tresh3 = cv2.threshold(blur3, 40, 255, cv2.THRESH_BINARY)
dilated3 = cv2.dilate(tresh3, None, iterations=3)
contours3, _ = cv2.findContours(dilated3, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours3:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 800:
continue
cv2.rectangle(frame31, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame31, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = "RASP" + str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame31)
resizedframe31 = rescale_frame(frame31, percent=75)
cv2.imshow('frame3', resizedframe31)
frame31 = frame32
ret3, frame32 = cap3.read()
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
Thanks Kartik and thekangaroo for your answers.
I managed to run my three cameras at the same time using threads. I am just opening them and showing a resized stream.
There is another issue as one cameras, and then a second, stops after a random time between 5 to 20 seconds. The stream stops and then the windows closes without any messages.
It seems to me that it is due to lagging getting the image from the cameras... any ideas to avoid that with openCV ?
Thanks again for your helpful answers.
Below is the code I use :
import cv2
import threading
import time
class camThread(threading.Thread):
def __init__(self, previewName, camID):
threading.Thread.__init__(self)
self.previewName = previewName
self.camID = camID
def run(self):
print("Starting " + self.previewName)
camPreview(self.previewName, self.camID)
def rescale_frame(frame, percent=75):
width = int(frame.shape[1] * percent / 100)
height = int(frame.shape[0] * percent / 100)
dim = (width, height)
return cv2.resize(frame, dim, interpolation=cv2.INTER_AREA)
def camPreview(previewName, camID):
cv2.namedWindow(previewName)
cam = cv2.VideoCapture(camID)
if cam.isOpened(): # try to get the first frame
rval, frame = cam.read()
else:
time.sleep(10)
rval, frame = cam.read()
percent = 50
width = int(frame.shape[1] * percent / 100)
height = int(frame.shape[0] * percent / 100)
dim = (width, height)
while rval:
# cv2.imshow(previewName, frame)
cv2.imshow(previewName, cv2.resize(frame, dim, interpolation=cv2.INTER_AREA))
time.sleep(0.5)
rval, frame = cam.read()
key = cv2.waitKey(20)
print(previewName + str(cam.isOpened()))
# Create two threads as follows
thread1 = camThread("CLIO", 'rtsp://xxxx')
thread2 = camThread("JARDIN", 'rtsp://xxxx')
thread3 = camThread("RASPCAM", 'http://xxxx')
thread1.start()
thread2.start()
thread3.start()
I am trying to detect a face using OpenCV. I have a file recognizer.py as follows:
import cv2
faceDetect = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
cam = cv2.VideoCapture(0)
rec = cv2.face.createLBPHFaceRecognizer()
rec.load('recognizer/trainningData.yml')
id = 0
font = cv2.FONT_HERSHEY_SIMPLEX
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:
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 2)
id, conf = rec.predict(gray[y:y + h, x:x + w])
cv2.putText(img, str(id), (x, y + h), font, 255, (255, 0, 0))
cv2.imshow("Face", img)
if cv2.waitKey(1) == ord('q'):
break
cam.release()
cv2.destroyAllWindows()
When I am trying to run this code, the program is running successfully and opening a camera window.
But whenever, I am trying to show my face in front of the camera, the program is terminating with exit code 1 and showing the following error:
Traceback (most recent call last):
File "/home/prateek/recognizer.py", line 15, in <module>
id, conf = rec.predict(gray[y:y + h, x:x + w])
TypeError: 'int' object is not iterable
Process finished with exit code 1
Means, I am getting the error on line 15 which is as follows:
id, conf = rec.predict(gray[y:y + h, x:x + w])
I don't know how to resolve this problem. I am using Python3 and OpenCV3.3.
Finally, I have got the solution. The problem with was version of opencv. This code is for opencv2.4 and I was trying to run it on opencv3.
Well, The final code for opencv3 is as following:
import cv2
faceDetect = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
cam = cv2.VideoCapture(0)
rec = cv2.face.createLBPHFaceRecognizer()
rec.load('recognizer/trainningData.yml')
id = 0
font = cv2.FONT_HERSHEY_SIMPLEX
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:
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 2)
id= rec.predict(gray[y:y + h, x:x + w])
cv2.putText(img, str(id), (x, y + h), font, 255, (255, 0, 0))
cv2.imshow("Face", img)
if cv2.waitKey(1) == ord('q'):
break
cam.release()
cv2.destroyAllWindows()
There is no need to mention the variable conf.
rec.predict(gray[y:y + h, x:x + w]) is returning the id of the person from the database.