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 = []