data_tags = OrderedDict( target=arr((n_frames, ), "int32"), video=arr((n_frames, ) + im_shp + (n_channels, ), "float32"), ) if n_channels == 1: data_tags["video"] = arr((n_frames, ) + im_shp, "float32") data_loader = Loader(preprocessors=[ LabelsCon(), VideoLoadPrep(n_frames=n_frames, rand_middle_frame=False, rgb=n_channels > 1), Augment3D(output_shape=(n_frames, ) + im_shp, output_scale=(1, 1, 1), mode="nearest", interp_order=0, augm_params={ "translation": [0, 4, 4], "rotation": [2, 0, 0], "shear": [0, 0, 0], "scale": [1, 1.1, 1.1], }), ClassPerFrame(n_frames=n_frames), ], inputs=data_tags) # TRAINING ############ learning_rate = 3e-5 * batch_size learning_rate_decay = 3e-5
augm_params={ "translation": [0, 16, 16], "rotation": [8, 0, 0], "shear": [0, 0, 0], "scale": [1, 1.5, 1.5], "reflection": [0, 0, .5] # Bernoulli p } print "augm_params", augm_params data_loader = Loader( data_path=paths.CON_PREP2, preprocessors=[ LabelsCon(), VideoLoadPrep(n_frames=n_frames, rand_middle_frame=True, rgb=n_channels>1, use_bcolz=True, tolerance=0, rgbbias=-127), Augment3D(output_shape=(n_frames,)+im_shp, output_scale=(1,1,1), mode="constant", dbias=-127, interp_order=1, augm_params=augm_params), ClassPerFrame(n_frames=n_frames), ], inputs = data_tags ) # TRAINING ############ learning_rate = 3e-5 * batch_size learning_rate_decay = 3e-5 validate_every_n_samples = 20*1024 validate_every_n_chunks = int(np.ceil(validate_every_n_samples/float(chunk_size)))
augm_params = { "translation": [0, 16, 16], "rotation": [4, 0, 0], "shear": [0, 0, 0], "scale": [1, 1.2, 1.2], "reflection": [0, 0, .5] # Bernoulli p } print "augm_params", augm_params data_loader = Loader(preprocessors=[ LabelsCon(), VideoLoadPrep(n_frames=n_frames, rand_middle_frame=False, rgb=n_channels > 1, tolerance=4), Augment3D(output_shape=(n_frames, ) + im_shp, output_scale=(1, 1, 1), mode="nearest", interp_order=0, augm_params=augm_params), ClassPerFrame(n_frames=n_frames), ], inputs=data_tags) # TRAINING ############ learning_rate = 3e-5 * batch_size learning_rate_decay = 3e-5 validate_every_n_samples = 20 * 1024 validate_every_n_chunks = int(