"The function/feature is not implemented" error when running opencv example - python-3.x

Question

I get the error below when running the following code:
import cv2, sys, numpy, os
haar_file = 'haarcascade_frontalface_default.xml'
datasets = 'datasets'
print('Recognizing Face Please Be in sufficient Lights...')
(images, lables, names, id) = ([], [], {}, 0)
for (subdirs, dirs, files) in os.walk(datasets):
for subdir in dirs:
names[id] = subdir
subjectpath = os.path.join(datasets, subdir)
for filename in os.listdir(subjectpath):
path = subjectpath + '/' + filename
lable = id
images.append(cv2.imread(path))
lables.append(int(lable))
id += 1
(width, height) = (130, 100)
(images, lables) = [numpy.array(lis) for lis in [images, lables]]
model = cv2.face.LBPHFaceRecognizer_create()
model.train(images, lables) # error comes here
face_cascade = cv2.CascadeClassifier(haar_file)
webcam = cv2.VideoCapture(0)
while True:
(_, im) = webcam.read()
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(im, (x, y), (x + w, y + h), (255, 0, 0), 2)
face = gray[y:y + h, x:x + w]
face_resize = cv2.resize(face, (width, height))
prediction = model.predict(face_resize)
cv2.rectangle(im, (x, y), (x + w, y + h), (0, 255, 0), 3)
if prediction[1]<500:
cv2.putText(im, '% s' %
(names[prediction[0]]), (x-10, y-10),
cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0))
else:
cv2.putText(im, 'not recognized',
(x-10, y-10), cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0))
cv2.imshow('OpenCV', im)
key = cv2.waitKey(10)
if key == 27:
break
cv2.destroyAllWindows()
the error that pops up is:
Traceback (most recent call last):
File "Y:\vigyantram\AI-20200807T104521Z-001\AI\img processing1\face_recognize.py", line 19, in <module>
model.train(images, lables)
cv2.error: OpenCV(4.3.0) C:\projects\opencv-python\opencv_contrib\modules\face\src\lbph_faces.cpp:265: error: (-213:The function/feature is not implemented) Using Original Local Binary Patterns for feature extraction only works on single-channel images (given 16). Please pass the image data as a grayscale image! in function 'cv::face::elbp'?
Thank you in advance.

Answer 1

This may solve the problem. Use size(width and height) multiple of 8 or 16 if it doesn't work let me know u need to convert both test and train images to grey try that also it will work.
import cv2, sys, numpy, os
haar_file = 'haarcascade_frontalface_default.xml'
datasets = 'datasets'
print('Recognizing Face Please Be in sufficient Lights...')
(images, lables, names, id) = ([], [], {}, 0)
for (subdirs, dirs, files) in os.walk(datasets):
for subdir in dirs:
names[id] = subdir
subjectpath = os.path.join(datasets, subdir)
for filename in os.listdir(subjectpath):
path = subjectpath + '/' + filename
lable = id
images.append(cv2.imread(path))
lables.append(int(lable))
id += 1
(width, height) = (200, 200) #here 200 is multiple of 8
(images, lables) = [numpy.array(lis) for lis in [images, lables]]
model = cv2.face.LBPHFaceRecognizer_create()
model.train(images, lables) #error comes here
face_cascade = cv2.CascadeClassifier(haar_file)
webcam = cv2.VideoCapture(0)
while True:
(_, im) = webcam.read()
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(im, (x, y), (x + w, y + h), (255, 0, 0), 2)
face = gray[y:y + h, x:x + w]
face_resize = cv2.resize(face, (width, height))
prediction = model.predict(face_resize)
cv2.rectangle(im, (x, y), (x + w, y + h), (0, 255, 0), 3)
if prediction[1]<500:
cv2.putText(im, '% s' %
(names[prediction[0]]), (x-10, y-10),
cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0))
else:
cv2.putText(im, 'not recognized',
(x-10, y-10), cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0))
cv2.imshow('OpenCV', im)
key = cv2.waitKey(10)
if key == 27:
break
cv2.destroyAllWindows()

Answer 2

i got to know what to do.
images.append(cv2.imread(path,0))
The '0' had to be added.