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)