"The function/feature is not implemented" error when running opencv example

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.

Answer 3

I have the same error with the code bellow

cv2.error: OpenCV(4.5.4) D:\a\opencv-python\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'

import cv2
import os
import numpy as np

eigenface = cv2.face.EigenFaceRecognizer_create()

fisherface = cv2.face.FisherFaceRecognizer_create()
lbph = cv2.face.LBPHFaceRecognizer_create()

def getImagemComId():
    caminhos = [os.path.join('fotos', f) for f in os.listdir('fotos')]
    #print(caminhos)
    faces = []
    ids = []
    for caminhoImagem in caminhos:
        imagemFace = cv2.cvtColor(cv2.imread(caminhoImagem), cv2.COLOR_BGR2RGB)
        id = int(os.path.split(caminhoImagem)[-1].split('.')[1])
        #print(id)
        ids.append(id)
        faces.append(imagemFace)
        #cv2.imshow('face', imagemFace)
        #cv2.waitKey(10)
    return np.array(ids), faces

ids, faces = getImagemComId()
#print(faces)
print("Treinando...")

eigenface.train(faces, ids)
eigenface.write('classificadorEigen.yml')

fisherface.train(faces, ids)
fisherface.write('classificadorFisher.yml')

lbph.train(faces, ids)
lbph.write('classificadorLBPH.yml')

print("Treinamento realizado")