def __init__(self,
settings,
net,
batched_data_mean,
labels=None,
label_layers=[],
channel_swap_to_rgb=None):
self.settings = settings
self.net = net
self.batched_data_mean = batched_data_mean
self.labels = labels if labels else [
'labels not provided' for ii in range(1000)
]
self.label_layers = label_layers if label_layers else list()
self.siamese_helper = SiameseHelper(self.settings.layers_list)
if channel_swap_to_rgb:
self.channel_swap_to_rgb = array(channel_swap_to_rgb)
else:
if settings._calculated_is_gray_model:
self.channel_swap_to_rgb = arange(1)
else:
self.channel_swap_to_rgb = arange(3) # Don't change order
# since we have a batch of same data mean images, we can just take the first
if batched_data_mean is not None:
self._data_mean_rgb_img = self.batched_data_mean[
0, self.channel_swap_to_rgb].transpose(
(1, 2, 0)) # Store as (227,227,3) in RGB order.
else:
self._data_mean_rgb_img = None
def __init__(self, net, settings, bindings, live_vis):
self.lock = Lock() # State is accessed in multiple threads
self.settings = settings
self.bindings = bindings
self.net = net
self.live_vis = live_vis
self.fill_layers_list(net)
self.siamese_helper = SiameseHelper(settings.layers_list)
self._populate_net_blob_info(net)
self.layer_boost_indiv_choices = self.settings.caffevis_boost_indiv_choices # 0-1, 0 is noop
self.layer_boost_gamma_choices = self.settings.caffevis_boost_gamma_choices # 0-inf, 1 is noop
self.caffe_net_state = 'free' # 'free', 'proc', or 'draw'
self.extra_msg = ''
self.back_stale = True # back becomes stale whenever the last back diffs were not computed using the current backprop unit and method (bprop or deconv)
self.next_frame = None
self.next_label = None
self.next_filename = None
self.last_frame = None
self.jpgvis_to_load_key = None
self.last_key_at = 0
self.quit = False
self._reset_user_state()
def main():
parser = argparse.ArgumentParser(description='Loads a pickled NetMaxTracker and outputs one or more of {the patches of the image, a deconv patch, a backprop patch} associated with the maxes.')
parser.add_argument('--N', type = int, default = 9, help = 'Note and save top N activations.')
parser.add_argument('--gpu', action = 'store_true', default=settings.caffevis_mode_gpu, help = 'Use gpu.')
parser.add_argument('--do-maxes', action = 'store_true', default=settings.max_tracker_do_maxes, help = 'Output max patches.')
parser.add_argument('--do-deconv', action = 'store_true', default=settings.max_tracker_do_deconv, help = 'Output deconv patches.')
parser.add_argument('--do-deconv-norm', action = 'store_true', default=settings.max_tracker_do_deconv_norm, help = 'Output deconv-norm patches.')
parser.add_argument('--do-backprop', action = 'store_true', default=settings.max_tracker_do_backprop, help = 'Output backprop patches.')
parser.add_argument('--do-backprop-norm', action = 'store_true', default=settings.max_tracker_do_backprop_norm, help = 'Output backprop-norm patches.')
parser.add_argument('--do-info', action = 'store_true', default=settings.max_tracker_do_info, help = 'Output info file containing max filenames and labels.')
parser.add_argument('--idx-begin', type = int, default = None, help = 'Start at this unit (default: all units).')
parser.add_argument('--idx-end', type = int, default = None, help = 'End at this unit (default: all units).')
parser.add_argument('--nmt_pkl', type = str, default = os.path.join(settings.caffevis_outputs_dir, 'find_max_acts_output.pickled'), help = 'Which pickled NetMaxTracker to load.')
parser.add_argument('--net_prototxt', type = str, default = settings.caffevis_deploy_prototxt, help = 'network prototxt to load')
parser.add_argument('--net_weights', type = str, default = settings.caffevis_network_weights, help = 'network weights to load')
parser.add_argument('--datadir', type = str, default = settings.static_files_dir, help = 'directory to look for files in')
parser.add_argument('--filelist', type = str, default = settings.static_files_input_file, help = 'List of image files to consider, one per line. Must be the same filelist used to produce the NetMaxTracker!')
parser.add_argument('--outdir', type = str, default = settings.caffevis_outputs_dir, help = 'Which output directory to use. Files are output into outdir/layer/unit_%%04d/{maxes,deconv,backprop}_%%03d.png')
parser.add_argument('--search-min', action='store_true', default=False, help='Should we also search for minimal activations?')
args = parser.parse_args()
settings.caffevis_deploy_prototxt = args.net_prototxt
settings.caffevis_network_weights = args.net_weights
net, data_mean = load_network(settings)
# validate batch size
if settings.is_siamese and settings._calculated_siamese_network_format == 'siamese_batch_pair':
# currently, no batch support for siamese_batch_pair networks
# it can be added by simply handle the batch indexes properly, but it should be thoroughly tested
assert (settings.max_tracker_batch_size == 1)
# set network batch size
current_input_shape = net.blobs[net.inputs[0]].shape
current_input_shape[0] = settings.max_tracker_batch_size
net.blobs[net.inputs[0]].reshape(*current_input_shape)
net.reshape()
assert args.do_maxes or args.do_deconv or args.do_deconv_norm or args.do_backprop or args.do_backprop_norm or args.do_info, 'Specify at least one do_* option to output.'
siamese_helper = SiameseHelper(settings.layers_list)
nmt = load_max_tracker_from_file(args.nmt_pkl)
for layer_name in settings.layers_to_output_in_offline_scripts:
print 'Started work on layer %s' % (layer_name)
normalized_layer_name = siamese_helper.normalize_layer_name_for_max_tracker(layer_name)
mt = nmt.max_trackers[normalized_layer_name]
if args.idx_begin is None:
idx_begin = 0
if args.idx_end is None:
idx_end = mt.max_vals.shape[0]
with WithTimer('Saved %d images per unit for %s units %d:%d.' % (args.N, normalized_layer_name, idx_begin, idx_end)):
output_max_patches(settings, mt, net, normalized_layer_name, idx_begin, idx_end,
args.N, args.datadir, args.filelist, args.outdir, False,
(args.do_maxes, args.do_deconv, args.do_deconv_norm, args.do_backprop, args.do_backprop_norm, args.do_info))
if args.search_min:
output_max_patches(settings, mt, net, normalized_layer_name, idx_begin, idx_end,
args.N, args.datadir, args.filelist, args.outdir, True,
(args.do_maxes, args.do_deconv, args.do_deconv_norm, args.do_backprop, args.do_backprop_norm, args.do_info))