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OpenCV Error: Unspecified error (This Eigenfaces model is not computed yet. Did you call Eigenfaces::train?) in predict, file /home/pi/opencv_contrib-3.3.0/modules/face/src/eigen_faces.cpp, line 113 Traceback (most recent call last): File "box.py", line 42, in <module> label, confidence = model.predict(crop) cv2.error: /home/pi/opencv_contrib-3.3.0/modules/face/src/eigen_faces.cpp:113: error: (-2) This Eigenfaces model is not computed yet. Did you call Eigenfaces::train? in function predict

THE CODE IN WHICH THERE IS ERROR IS GIVEN BELOW import cv2

import config import face import hardware

if __name__ == '__main__': # Load training data into model print 'Loading training data...' model = cv2.face.EigenFaceRecognizer_create() model.read(config.TRAINING_FILE) print 'Training data loaded!' # Initialize camer and box. camera = config.get_camera() box = hardware.Box() # Move box to locked position. box.lock() print 'Running box...' print 'Press button to lock (if unlocked), or unlock if the correct face is detected.' print 'Press Ctrl-C to quit.' while True: print 'Button pressed, looking for face...' # Check for the positive face and unlock if found. image = camera.read() # Convert image to grayscale. image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) # Get coordinates of single face in captured image. result = face.detect_single(image) if result is None: print 'Could not detect single face! Check the image in capture.pgm' \ ' to see what was captured and try again with only one face visible.' continue x, y, w, h = result # Crop and resize image to face. crop = face.resize(face.crop(image, x, y, w, h))

            put=cv2.equalizeHist(crop)
            # Test face against model.
            label, confidence = model.predict(put)
            print 'Predicted {0} face with confidence {1} (lower is more confident).'.format(
                'POSITIVE' if label == config.POSITIVE_LABEL else 'NEGATIVE', 
                confidence)
            if label == config.POSITIVE_LABEL and confidence < config.POSITIVE_THRESHOLD:
                print 'Recognized face!'
                box.unlock()
            else:
                print 'Did not recognize face!'

OpenCV Error: Unspecified error (This Eigenfaces model is not computed yet. Did you call Eigenfaces::train?) in predict, file /home/pi/opencv_contrib-3.3.0/modules/face/src/eigen_faces.cpp, line 113 Traceback (most recent call last): File "box.py", line 42, in <module> label, confidence = model.predict(crop) cv2.error: /home/pi/opencv_contrib-3.3.0/modules/face/src/eigen_faces.cpp:113: error: (-2) This Eigenfaces model is not computed yet. Did you call Eigenfaces::train? in function predict

THE CODE IN WHICH THERE IS ERROR IS GIVEN BELOW BELOW

import cv2
 
cv2

import config
import face
import hardware
 
hardware


if __name__ == '__main__':
    # Load training data into model
    print 'Loading training data...'
    model = cv2.face.EigenFaceRecognizer_create()
    model.read(config.TRAINING_FILE)
    print 'Training data loaded!'
    # Initialize camer and box.
    camera = config.get_camera()
    box = hardware.Box()
    # Move box to locked position.
    box.lock()
    print 'Running box...'
    print 'Press button to lock (if unlocked), or unlock if the correct face is detected.'
    print 'Press Ctrl-C to quit.'
    while True:
                print 'Button pressed, looking for face...'
                # Check for the positive face and unlock if found.
                image = camera.read()
                # Convert image to grayscale.
                image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
                # Get coordinates of single face in captured image.
                result = face.detect_single(image)
                if result is None:
                    print 'Could not detect single face!  Check the image in capture.pgm' \
                          ' to see what was captured and try again with only one face visible.'
                    continue
                x, y, w, h = result
                # Crop and resize image to face.
                crop = face.resize(face.crop(image, x, y, w, h))
 
h))

                put=cv2.equalizeHist(crop)
             # Test face against model.
             label, confidence = model.predict(put)
             print 'Predicted {0} face with confidence {1} (lower is more confident).'.format(
                 'POSITIVE' if label == config.POSITIVE_LABEL else 'NEGATIVE', 
                 confidence)
             if label == config.POSITIVE_LABEL and confidence < config.POSITIVE_THRESHOLD:
                 print 'Recognized face!'
                 box.unlock()
             else:
                 print 'Did not recognize face!'