print 'loading pretrained CNN...' feature_network = HumanConvNet(name='Person CNN', nout=2, numpy_rng=numpy_rng, theano_rng=theano_rng, batchsize=batchsize) feature_network.load('convnet_eth_inria_data/human_convnet_val_best.h5') feature_network.mode.set_value(np.uint8(1)) print "instantiating model..." model = RATM(name='RATM', imsize=imsize, patchsize=patchsize, nhid=nhid, numpy_rng=numpy_rng, eps=1e-4, hids_scale=1., feature_network=feature_network, input_feature_layer_name=input_feature_layer_name, metric_feature_layer_name=metric_feature_layer_name, nchannels=1, weight_decay=weight_decay) print "done (with instantiating model)" def visualize(fname): n = 5 idx = numpy_rng.permutation(len(val_data['inputs']))[:n] val_vids = val_data['inputs'][idx] val_bbs = val_data['targets'][idx] val_masks = val_data['masks'][idx]