args = parse_args()
print('Called with args:')
print(args)
if args.cfg_file is not None:
cfg_from_file(args.cfg_file)
cfg_set_path(args.exp_dir)
while not os.path.exists(args.thresh_file) and args.wait:
print('Wating for {} to exist...'.format(args.thresh_file))
time.sleep(10)
thresh = cfg_load_thresh(args.thresh_file)
cfg_set_mode('Test', thresh)
print('Using config:')
pprint.pprint(cfg)
while not os.path.exists(args.caffemodel) and args.wait:
print('Waiting for {} to exist...'.format(args.caffemodel))
time.sleep(10)
caffe.set_mode_gpu()
caffe.set_device(args.gpu_id)
# full AZ-net
net = caffe.Net(args.prototxt, args.caffemodel, caffe.TEST)
net.name = os.path.splitext(os.path.basename(args.caffemodel))[0]
# fc layers of AZ-Net
args = parser.parse_args()
return args
if __name__ == '__main__':
args = parse_args()
print('Called with args:')
print(args)
if args.cfg_file is not None:
cfg_from_file(args.cfg_file)
cfg_set_path(args.exp_dir)
cfg_set_mode('Train')
print('Using config:')
pprint.pprint(cfg)
if not args.randomize:
# fix the random seeds (numpy and caffe) for reproducibility
np.random.seed(cfg.RNG_SEED)
caffe.set_random_seed(cfg.RNG_SEED)
if args.normalize:
cfg.TRAIN.UN_NORMALIZE = True
else:
cfg.TRAIN.UN_NORMALIZE = False
# set up caffe
args = parse_args()
print('Called with args:')
print(args)
if args.cfg_file is not None:
cfg_from_file(args.cfg_file)
cfg_set_path(args.exp_dir)
while not os.path.exists(args.thresh_file) and args.wait:
print('Wating for {} to exist...'.format(args.thresh_file))
time.sleep(10)
thresh = cfg_load_thresh(args.thresh_file)
cfg_set_mode('Test', thresh)
print('Using config:')
pprint.pprint(cfg)
while not os.path.exists(args.caffemodel_az) and args.wait:
print('Waiting for {} to exist...'.format(args.caffemodel_az))
time.sleep(10)
while not os.path.exists(args.caffemodel_frcnn) and args.wait:
print('Waiting for {} to exist...'.format(args.caffemodel_frcnn))
time.sleep(10)
caffe.set_mode_gpu()
caffe.set_device(args.gpu_id)
