parser.add_argument('-i',action='store',dest='id_upper',type = int)
parser.add_argument('-c',action='store_true',help='train classifier')
parser.add_argument('-f',action='store',dest='file',type=str,help='parser a clothes image')
args = parser.parse_args()
if args.cmd == 'train':
if args.b:
if args.s:
train_bow_sift(args.id_upper)
elif args.p:
train_bow_pixel()
if args.c:
train_clf('pixel')
if args.cmd == 'test':
kmeans = KmeansModel()
kmeans.load('kmeans_pixel')
clf = RandomForest()
clf.load()
data = DataHandler()
data.load()
if args.file:
for res in clf.predict(kmeans,file):
print int(res),data.tell_label(int(res))
if args.cmd == 'data':
data = DataHandler()
data.parse_data('design.json')
data.save()
def test_something(self):
dh = DataHandler()
dh.parse_data("design.json")
