plot_cnn_output(test_dyn_lips_preds,
os.path.join("models/saved", config["config_name"]),
"00_monkey_test_dyn_lips_feature_maps_output.gif",
verbose=True,
video=True)
plot_ft_map_pos(calculate_position(test_dyn_lips_preds[1:],
mode="weighted average",
return_mode="xy float"),
fig_name="00_monkey_test_dyn_lips_pos.png",
path=os.path.join("models/saved", config["config_name"]),
color_seq=color_seq)
# *********************** test 01 eyebrow model ******************
# plot it responses for eyebrow model
nb_model_eyebrow.plot_it_neurons(it_train_eyebrow,
title="01_it_train_eyebrow",
save_folder=os.path.join(
"models/saved", config["config_name"]))
nb_model_eyebrow.plot_it_neurons(it_test_eyebrow,
title="01_it_test_eyebrow",
save_folder=os.path.join(
"models/saved", config["config_name"]))
nb_model_eyebrow.plot_it_neurons(it_ref_test_eyebrow,
title="01_it_ref_test_eyebrow",
save_folder=os.path.join(
"models/saved", config["config_name"]))
# *********************** test 02 lips model ******************
# plot it responses for lips model
nb_model_lips.plot_it_neurons(it_train_lips,
title="02_it_train_lips",
save_folder=os.path.join("models/saved",
path=os.path.join("models/saved", config["config_name"]),
color_seq=color_seq)
# plot_cnn_output(test_dyn_lips_preds, os.path.join("models/saved", config["config_name"]),
# "00_monkey_test_dyn_lips_feature_maps_output.gif", verbose=True, video=True)
plot_ft_map_pos(calculate_position(test_dyn_lips_preds,
mode="weighted average",
return_mode="xy float"),
fig_name="00_monkey_test_dyn_lips_pos.png",
path=os.path.join("models/saved", config["config_name"]),
color_seq=color_seq)
# *********************** test 01 eyebrow model ******************
# plot it responses for eyebrow model
nb_model.plot_it_neurons(it_train,
title="01_it_train",
save_folder=os.path.join("models/saved",
config["config_name"]))
nb_model.plot_it_neurons(it_test,
title="01_it_test",
save_folder=os.path.join("models/saved",
config["config_name"]))
nb_model.plot_it_neurons(it_ref_test,
title="01_it_ref_test",
save_folder=os.path.join("models/saved",
config["config_name"]))
# plot it responses with reference
nb_model.plot_it_neurons_per_sequence(it_train,
title="02_it_train",
save_folder=os.path.join(
"models/saved",
title="01_train",
save_folder=os.path.join("models/saved", config['config_name']))
# --------------------------------------------------------------------------------------------------------------------
# apply face transfer using the monkey avatar
# load data
data = load_data(config, train=False)
# plot_sequence(np.array(data[0]).astype(np.uint8), video_name='02_test_sequence.mp4',
# path=os.path.join("models/saved", config['config_name']))
# --------------------------------------------------------------------------------------------------------------------
# predict model
face_neurons = model.predict(data)
# model.plot_it_neurons_per_sequence(face_neurons,
# title="02_test",
# save_folder=os.path.join("models/saved", config['config_name']))
model.plot_it_neurons(face_neurons,
title="02a_test",
save_folder=os.path.join("models/saved", config['config_name']))
# --------------------------------------------------------------------------------------------------------------------
# fit reference frames and predict model
face_neurons = model.fit(data, fit_dim_red=False,
fit_ref=True,
fit_tun=False)
model.plot_it_neurons_per_sequence(face_neurons,
title="03_test_wh_ref",
save_folder=os.path.join("models/saved", config['config_name']))