imagePaths=[os.path.join(path,f) for f in os.listdir(path)]
faceSamples=[]
Ids=[]
for imagePath in imagePaths:
pilImage=Image.open(imagePath).convert('L')
imageNp=np.array(pilImage,'uint8')
Id=int(os.path.split(imagePath)[-1].split(".")[1])
faces=detector.detectMultiScale(imageNp)
for (x,y,w,h) in faces:
faceSamples.append(imageNp[y:y+h,x:x+w])
Ids.append(Id)
return faceSamples,Ids
faces,Ids = getImagesAndLabels('dataSet')
s = recognizer.train(faces, np.array(Ids))
print("Successfully trained")
recognizer.write('trainer/trainer.yml')
and when i run it i get this error
Traceback (most recent call last):
File "D:\Face-react\Face Recogonition\Test 7\Face-Recognition-Attendance-System-master\attendance\training_dataSet.py", line 32, in
s = recognizer.train(faces, np.array(Ids))
cv2.error: OpenCV(4.2.0) C:\projects\opencv-python\opencv_contrib\modules\face\src\lbph_faces.cpp:362: error: (-210:Unsupported format or combination of formats) Empty training data was given. You'll need more than one sample to learn a model. in function 'cv::face::LBPH::train'
so this is the code..
import os,cv2; import numpy as np from PIL import Image;
recognizer = cv2.face.LBPHFaceRecognizer_create() detector= cv2.CascadeClassifier("haarcascade_frontalface_default.xml");
def getImagesAndLabels(path):
faces,Ids = getImagesAndLabels('dataSet') s = recognizer.train(faces, np.array(Ids)) print("Successfully trained") recognizer.write('trainer/trainer.yml')
and when i run it i get this error
Traceback (most recent call last):
File "D:\Face-react\Face Recogonition\Test 7\Face-Recognition-Attendance-System-master\attendance\training_dataSet.py", line 32, in
s = recognizer.train(faces, np.array(Ids))
cv2.error: OpenCV(4.2.0) C:\projects\opencv-python\opencv_contrib\modules\face\src\lbph_faces.cpp:362: error: (-210:Unsupported format or combination of formats) Empty training data was given. You'll need more than one sample to learn a model. in function 'cv::face::LBPH::train'