import database from card import Card def listCards(fileName): db = database.loadDatabase(fileName) cards = database.loadAllCards(db=db) for card in cards: print(str(card)) if __name__ == "__main__": db = database.loadDatabase("box.db") print("You can list/add/modify/delete") command = input("What to do: ").lower() if command == "list": print("Listing...") listCards("box.db") elif command == "add": question = input("Question: ") answer = input("answer: ") colour = input("colour: ") image = input("image: ") card = Card(None, question, answer, colour, image, 1, 0) database.insertCard(db, card) elif command == "modify": cardId = input("Id of card to replace: ") card = database.loadCard(db, cardId) property_ = input("Property to modify: ").lower() value = input("New value: ") if property_ == "question":
def listCards(fileName): db = database.loadDatabase(fileName) cards = database.loadAllCards(db=db) for card in cards: print(str(card))
if args.output_file: output_file = args.output_file video_writer = cv2.VideoWriter(output_file, int(video.get(6)), video.get(5), (int(video.get(3)), int(video.get(4)))) if not video_writer.isOpened(): raise Exception("Cannot write to file %s" % output_file) write_output = True else: write_output = False detector_and_tracker = FaceDetectorAndTracker() descriptor = initDescriptor( descriptor_type, database_name, detector_and_tracker.alignment_with_face_detector.getReferenceShape()) database = loadDatabase(desc=descriptor_type, db=database_name) filters = [] if "jb" in descriptor_type: similarity = jointBayesianDistance else: similarity = np.inner cv2.namedWindow("Alignment demo") fps = video.get(5) print "Video running at %0.2f fps" % fps n = 0 face_detector_freq = int(fps / 2) shapes = []