def __init__(self,
face_classifier_filepath=None,
eye_classifier_filepath=None,
parent=None):
super().__init__(parent)
if face_classifier_filepath is None:
face_classifier_filepath = get_haarcascade_filepath()
if eye_classifier_filepath is None:
eye_classifier_filepath = get_haarcascade_filepath('eyes')
self.fisher_faces = cv2.faces.createFisherFaceRecognizer()
# Need an integer as the key, and image as the
self._images = {}
self._eye_classifier = cv2.CascadeClassifier(eye_classifier_filepath)
def main():
# We need to make the QApplication before our QMainWindow
# We also need to pass in our system argument values (sys.argv)
app = QtWidgets.QApplication(sys.argv)
main_window = QtWidgets.QMainWindow()
# QMainWindow requires a central widget.
haar_file = get_haarcascade_filepath()
central_widget = FaceSignalWidget(haar_file)
main_window.setCentralWidget(central_widget)
# Show our main window
main_window.show()
# Start the event loop processing
app.exec()
def __init__(self, parent=None):
super().__init__(parent)
haar_filepath = get_haarcascade_filepath()
self.face_detect_widget = FaceDetectionWidget(haar_filepath)
self.video_recording = RecordVideo()
record_button = QtWidgets.QPushButton('Run')
layout = Qtwidgets.QVBoxLayout()
layout.addWidget(self.face_detect_widget)
layout.addWidget(record_button)
self.setLayout(layout)
# Connect our signal `clicked` to our method `start_recording`
record_button.clicked.connect(self.video_recording.start_recording)
# alias out the method call `image_data_slot` to make the code
# line shorter
image_data_slot = self.face_detect_widget.image_data_slot
# connect our signal `image_data` to our method `image_data_slot`
self.video_recording.image_data.connect(image_data_slot)