error: (-215:Assertion failed) s >= 0 in function 'cv::setSize'

[ghost]

I am getting this error while training my classifier - face_recog.train(faces,np.array(faceID))

The full code is as follow:

[import cv2 import os import numpy as np %config IPCompleter.greedy=True

def facedetection(test_img):

gray_img = cv2.cvtColor(test_img,cv2.COLOR_BGR2GRAY)

face_cascade= cv2.CascadeClassifier("C:\\Users\\Abhijeet Debadwar\\AppData\\Local\\Programs\\Python\\Python38\\Lib\\site-packages\\cv2\\\data\\haarcascade_frontalface_default.xml")

faces = face_cascade.detectMultiScale(gray_img ,1.42,10)

return faces, gray_img

def labels_for_training_data(directory):

faces =[]
faceID= []

for maindirectory, subdirectory,filenames in os.walk(directory):
    
    for filename in filenames:
        
        if filename[0]==".":
            print("skipped")
            continue
            
        id = os.path.basename(maindirectory)
        
        img_path = os.path.join(maindirectory,filename)
        
        print("img_path ",img_path)
        print("image ID: ", id)
        
        test_img = cv2.imread(img_path)
        
        if test_img is None:
            print("IMAGE NOT LOADED PROPERLY")
            continue
                 
        faces_rect, gray_img = facedetection(test_img)
        
        if len(faces_rect)!=1:
            continue
            
        (x,y,w,h)= faces_rect[0]
        
        ROF_gray = gray_img[x:x+w,y:y+h]
        
        faces.append(ROF_gray)
        faceID.append(int(id))
        
        
return faces, faceID
        

def train_classifier(faces,faceID):

face_recog = cv2.face.LBPHFaceRecognizer_create()

face_recog.train(faces,np.array(faceID))

return face_recog

def draw_rect(test_img,faces):

(x,y,w,h) = faces

cv2.rectange(test_img,(x,y), (x+w,y+h),(255,0,0), 5)

def put_text(test_img,text,x,y):

cv2.putText(test_img,text, (x,y), cv2.FONT_HERSHEY_DUPLEX, 5, (0,255,0),5)

    

test_img = cv2.imread("D:\testimages\1\IMG_20190611_185155.jpg",1)

face_detected, gray_img = facedetection(test_img)

faces, faceID = labels_for_training_data("D:\testimages")

face_recog = train_classifier( faces, faceID)

name = { 1: "ABHIJEET", 0: "HERO"}

for face in face_detected:

(x,y,w,h)= face

roi_gray= gray_img[x:x+w,y:y+h]

label,confidencelevel = face_recog.predict(roi_gray)

print(" confidence ", confidencelevel)
print("label " , label)

draw_rect(test_img, face)

predicted_name = name[label]

put_text(test_img,predicted_name, x,y)


resized_img = cv2.resize(test_img, (500,500))

cv2.imshow("ABHIJEET S NICE", resized_img)

cv2.waitKey(0)

cv2.destroyAllWindows()                

[sanjuth]

Did u find a solution for this ?