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I'm getting the following error while using OpenCV

My code is as below:

It helps in identifying the faces

import cv2, sys, numpy, os size = 4 haar_file = 'haarcascade_frontalface_default.xml' datasets = 'datasets'

Part 1: Create fisherRecognizer

print('Recognizing Face Please Be in sufficient Lights...')

Create a list of images and a list of corresponding names

(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, 0)) lables.append(int(lable)) id += 1 (width, height) = (130, 100)

Create a Numpy array from the two lists above

(images, lables) = [numpy.array(lis) for lis in [images, lables]] print('Images', images) print('Lables', lables)

OpenCV trains a model from the images

NOTE FOR OpenCV2: remove '.face'

model = cv2.face.LBPHFaceRecognizer_create() model.train(images, lables)

Part 2: Use fisherRecognizer on camera stream

face_cascade = cv2.CascadeClassifier(haar_file) print('Initiating image capture now...') 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)) # Try to recognize the face 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 - %.0f' %(names[prediction[0]], prediction[1]), (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) 
if cv2.waitKey(10) & 0xff == ord('q'):
    break

cv2.waitKey(0)

Release the capture once all the processing is done.

cv2.destroyAllWindows() webcam.release()

The error that I get while running the program in Jupyter notebook is as follows:

error Traceback (most recent call last) <ipython-input-7-eab39be2c873> in <module> 32 print('Images', images) 33 print('Lables', lables) ---> 34 model.train(images, lables) 35 36 # Part 2: Use fisherRecognizer on camera stream

error: OpenCV(4.4.0) C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build-wwma2wne\opencv\modules\core\src\matrix.cpp:235: error: (-215:Assertion failed) s >= 0 in function 'cv::setSize'

I'm getting the following error while using OpenCV

My code is as below:

# It helps in identifying the faces
faces import cv2, sys, numpy, os size = 4 haar_file = 'haarcascade_frontalface_default.xml' datasets = 'datasets' 'datasets' # Part 1: Create fisherRecognizer fisherRecognizer print('Recognizing Face Please Be in sufficient Lights...') # Create a list of images and a list of corresponding names names (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, 0)) lables.append(int(lable)) id += 1 (width, height) = (130, 100) # Create a Numpy array from the two lists above above (images, lables) = [numpy.array(lis) for lis in [images, lables]] print('Images', images) print('Lables', lables) lables) # OpenCV trains a model from the images images # NOTE FOR OpenCV2: remove '.face' '.face' model = cv2.face.LBPHFaceRecognizer_create() model.train(images, lables) lables) # Part 2: Use fisherRecognizer on camera stream stream face_cascade = cv2.CascadeClassifier(haar_file) print('Initiating image capture now...') 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)) # Try to recognize the face 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 - %.0f' %(names[prediction[0]], prediction[1]), (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) if cv2.waitKey(10) & 0xff == ord('q'): break cv2.waitKey(0) cv2.waitKey(0) # Release the capture once all the processing is done. done. cv2.destroyAllWindows() webcam.release()

webcam.release()

The error that I get while running the program in Jupyter notebook is as follows:

--------------------------------------------------------------------------- error Traceback (most recent call last) <ipython-input-7-eab39be2c873> in <module> 32 print('Images', images) 33 print('Lables', lables) ---> 34 model.train(images, lables) 35 36 # Part 2: Use fisherRecognizer on camera stream stream error: OpenCV(4.4.0) C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build-wwma2wne\opencv\modules\core\src\matrix.cpp:235: error: (-215:Assertion failed) s >= 0 in function 'cv::setSize''cv::setSize'