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asked 2018-12-19 08:15:20 -0600

oja gravatar image

Hey guys I am doing a face recognition project using LBPHFaceRecognizer the problen is that for few images as test it is recognizing ad for few images it is giving this error: (-215:Assertion failed) s >= 0 in function 'cv::setSize'

I know the problem is with the picture but can't figure out what the problem is i tried reducing size for the image still doesn't work

Here is the complete code

import cv2
import os
import numpy as np


subjects=["","oja","mom"]
#img=cv2.imread('obama.jpg')
#function_1
def detect_face(img):
    gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    face_cascade=cv2.CascadeClassifier('A:/project_face_detection/face_detetion/opencv-files/lbpcascade_frontalface.xml')
    faces=face_cascade.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=5);
    if(len(faces)==0):
        return None,None
    (x,y,w,h)=faces[0]
    return gray[y:y+w,x:x+h],faces[0]

#function_2
def prepare_training_data(data_folder_path):
    dirs=os.listdir(data_folder_path)
    faces=[]
    labels=[]
    for dir_name in dirs:
        if not dir_name.startswith('s'):
            continue;
        label=int(dir_name.replace("s",""))
        subject_dir_path= data_folder_path +"/"+dir_name
        subject_images_names=os.listdir(subject_dir_path)   
        for image_name in subject_images_names:
            if image_name.startswith("."):
                continue;
            image_path=subject_dir_path + "/" + image_name 

            image=cv2.imread(image_path)


            cv2.imshow("training on image",cv2.resize(image,(400,500)))


            cv2.waitKey(100)
            face,rect=detect_face(image)
            if face is not None:
                faces.append(face)
                labels.append(label)
    cv2.destroyAllWindows()
    cv2.waitKey(1)
    cv2.destroyAllWindows()
    return faces,labels

print("preparing data")
faces,labels=prepare_training_data("training_data") 
print("total faces:",len(faces))
print("total labels:",len(labels))

face_recognizer = cv2.face.LBPHFaceRecognizer_create()
face_recognizer.train(faces, np.array(labels))            



#function_3
def draw_rectangle(img, rect):
    (x, y, w, h) = rect
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)

#function_4
def draw_text(img, text, x, y):
    cv2.putText(img, text, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 255, 0), 2)
#function_5
def predict(test_img):
    img = test_img.copy()
    face, rect = detect_face(img)
    label, confidence = face_recognizer.predict(face)
    label_text = subjects[label]
    draw_rectangle(img, rect)
    draw_text(img, label_text, rect[0], rect[1]-5)    
    return img


print("Predicting images...")

test_img1 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test3.1.jpg")
test_img2 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test2.1.jpg")

predicted_img1 = predict(test_img1)
predicted_img2 = predict(test_img2)
print("Prediction complete")

cv2.imshow(subjects[1], cv2.resize(predicted_img1, (250, 250)))
cv2.imshow(subjects[2], cv2.resize(predicted_img2, (250, 250)))
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.waitKey(1)
cv2.destroyAllWindows()

*when I try to predict for test3.1 image it works for test2.1 i get this error: (-215:Assertion failed) s >= 0 in function 'cv::setSize' *

test_img1 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test3.1.jpg")
    test_img2 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test2.1.jpg")

    predicted_img1 = predict(test_img1)
    predicted_img2 = predict(test_img2)

Thanks for looking into it I am relatively new to openCV so please don't step back from elaborating even the most basic stuff

Hey guys I am doing a face recognition project using LBPHFaceRecognizer the problen is that for few images as test it is recognizing ad for few images it is giving this error: (-215:Assertion failed) s >= 0 in function 'cv::setSize'

I know the problem is with the picture but can't figure out what the problem is i tried reducing size for the image still doesn't work

Here is the complete code

import cv2
import os
import numpy as np


subjects=["","oja","mom"]
#img=cv2.imread('obama.jpg')
#function_1
def detect_face(img):
    gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    face_cascade=cv2.CascadeClassifier('A:/project_face_detection/face_detetion/opencv-files/lbpcascade_frontalface.xml')
    faces=face_cascade.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=5);
    if(len(faces)==0):
        return None,None
    (x,y,w,h)=faces[0]
    return gray[y:y+w,x:x+h],faces[0]

#function_2
def prepare_training_data(data_folder_path):
    dirs=os.listdir(data_folder_path)
    faces=[]
    labels=[]
    for dir_name in dirs:
        if not dir_name.startswith('s'):
            continue;
        label=int(dir_name.replace("s",""))
        subject_dir_path= data_folder_path +"/"+dir_name
        subject_images_names=os.listdir(subject_dir_path)   
        for image_name in subject_images_names:
            if image_name.startswith("."):
                continue;
            image_path=subject_dir_path + "/" + image_name 

            image=cv2.imread(image_path)


            cv2.imshow("training on image",cv2.resize(image,(400,500)))


            cv2.waitKey(100)
            face,rect=detect_face(image)
            if face is not None:
                faces.append(face)
                labels.append(label)
    cv2.destroyAllWindows()
    cv2.waitKey(1)
    cv2.destroyAllWindows()
    return faces,labels

print("preparing data")
faces,labels=prepare_training_data("training_data") 
print("total faces:",len(faces))
print("total labels:",len(labels))

face_recognizer = cv2.face.LBPHFaceRecognizer_create()
face_recognizer.train(faces, np.array(labels))            



#function_3
def draw_rectangle(img, rect):
    (x, y, w, h) = rect
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)

#function_4
def draw_text(img, text, x, y):
    cv2.putText(img, text, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 255, 0), 2)
#function_5
def predict(test_img):
    img = test_img.copy()
    face, rect = detect_face(img)
    label, confidence = face_recognizer.predict(face)
    label_text = subjects[label]
    draw_rectangle(img, rect)
    draw_text(img, label_text, rect[0], rect[1]-5)    
    return img


print("Predicting images...")

test_img1 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test3.1.jpg")
test_img2 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test2.1.jpg")

predicted_img1 = predict(test_img1)
predicted_img2 = predict(test_img2)
print("Prediction complete")

cv2.imshow(subjects[1], cv2.resize(predicted_img1, (250, 250)))
cv2.imshow(subjects[2], cv2.resize(predicted_img2, (250, 250)))
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.waitKey(1)
cv2.destroyAllWindows()

*when I try to predict for test3.1 image it works for test2.1 i get this error: (-215:Assertion failed) s >= 0 in function 'cv::setSize' *

test_img1 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test3.1.jpg")
    test_img2 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test2.1.jpg")

    predicted_img1 = predict(test_img1)
    predicted_img2 = predict(test_img2)

Thanks for looking into it I am relatively new to openCV so please don't step back from elaborating even the most basic stuff

click to hide/show revision 3
retagged

updated 2020-11-14 05:43:26 -0600

sturkmen gravatar image

Hey guys I am doing a face recognition project using LBPHFaceRecognizer the problen is that for few images as test it is recognizing ad for few images it is giving this error: (-215:Assertion failed) s >= 0 in function 'cv::setSize'

I know the problem is with the picture but can't figure out what the problem is i tried reducing size for the image still doesn't work

Here is the complete code

import cv2
import os
import numpy as np


subjects=["","oja","mom"]
#img=cv2.imread('obama.jpg')
#function_1
def detect_face(img):
    gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    face_cascade=cv2.CascadeClassifier('A:/project_face_detection/face_detetion/opencv-files/lbpcascade_frontalface.xml')
    faces=face_cascade.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=5);
    if(len(faces)==0):
        return None,None
    (x,y,w,h)=faces[0]
    return gray[y:y+w,x:x+h],faces[0]

#function_2
def prepare_training_data(data_folder_path):
    dirs=os.listdir(data_folder_path)
    faces=[]
    labels=[]
    for dir_name in dirs:
        if not dir_name.startswith('s'):
            continue;
        label=int(dir_name.replace("s",""))
        subject_dir_path= data_folder_path +"/"+dir_name
        subject_images_names=os.listdir(subject_dir_path)   
        for image_name in subject_images_names:
            if image_name.startswith("."):
                continue;
            image_path=subject_dir_path + "/" + image_name 

            image=cv2.imread(image_path)


            cv2.imshow("training on image",cv2.resize(image,(400,500)))


            cv2.waitKey(100)
            face,rect=detect_face(image)
            if face is not None:
                faces.append(face)
                labels.append(label)
    cv2.destroyAllWindows()
    cv2.waitKey(1)
    cv2.destroyAllWindows()
    return faces,labels

print("preparing data")
faces,labels=prepare_training_data("training_data") 
print("total faces:",len(faces))
print("total labels:",len(labels))

face_recognizer = cv2.face.LBPHFaceRecognizer_create()
face_recognizer.train(faces, np.array(labels))            



#function_3
def draw_rectangle(img, rect):
    (x, y, w, h) = rect
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)

#function_4
def draw_text(img, text, x, y):
    cv2.putText(img, text, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 255, 0), 2)
#function_5
def predict(test_img):
    img = test_img.copy()
    face, rect = detect_face(img)
    label, confidence = face_recognizer.predict(face)
    label_text = subjects[label]
    draw_rectangle(img, rect)
    draw_text(img, label_text, rect[0], rect[1]-5)    
    return img


print("Predicting images...")

test_img1 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test3.1.jpg")
test_img2 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test2.1.jpg")

predicted_img1 = predict(test_img1)
predicted_img2 = predict(test_img2)
print("Prediction complete")

cv2.imshow(subjects[1], cv2.resize(predicted_img1, (250, 250)))
cv2.imshow(subjects[2], cv2.resize(predicted_img2, (250, 250)))
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.waitKey(1)
cv2.destroyAllWindows()

*when I try to predict for test3.1 image it works for test2.1 i get this error: (-215:Assertion failed) s >= 0 in function 'cv::setSize' *

test_img1 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test3.1.jpg")
    test_img2 = cv2.imread("A:/project_face_detection/face_detetion/test_data/test2.1.jpg")

    predicted_img1 = predict(test_img1)
    predicted_img2 = predict(test_img2)

Thanks for looking into it I am relatively new to openCV so please don't step back from elaborating even the most basic stuff

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