def preprocess_from_weights(path_topology,
path_weights,
path_output_dir,
output_node_names=None):
"""""Preprocess a model built by Keras (from topology+weights)
:param path_topology:
:param path_weights:
:param path_output_dir:
:param output_node_names:
:return:
"""
if not valid_file(path_topology):
show_invalid_message('model topology file', path_topology)
return
if not valid_file(path_weights):
show_invalid_message('model weights file', path_weights)
return
model = load_from_saved_weights(path_topology, path_weights)
enc_model = generate_encapsulate_model(
model, split_layer_name_list(output_node_names))
# Generate temp Keras enc_model for further processing
save_enc_model(path_output_dir, enc_model)
convert_tfjs(path_output_dir)
clean_temp_file(path_output_dir)
def show_summary_weights(path_topology, path_weights):
"""Present model summary by model topology and weights
Load the model from topology and weights, then present model summary
:param path_topology: path to model topology file
:param path_weights: path to model weights file
:return: should not return anything
"""
if not valid_file(path_topology):
show_invalid_message('model topology file', path_topology)
return
if not valid_file(path_weights):
show_invalid_message('model weights file', path_weights)
return
print("show summary of keras saved topology + weights...")
model = load_from_saved_weights(path_topology, path_weights)
model.summary()
def show_keras_model_summary(path_model):
"""Present model summary by single model file
Load the model from a single model file, then present model summary
:param path_model: path to the single model file
:return: should not return anything
"""
if not valid_file(path_model):
show_invalid_message('input file', path_model)
return
print("show summary of keras saved model...")
model = load_from_saved_model(path_model)
model.summary()
def process_tfjs_model(path_input, path_output, output_names=None):
os.makedirs(path_output, exist_ok=True)
if not valid_file(path_input):
show_invalid_message('input model file', path_input)
return
if output_names is None:
subprocess.check_call(["node", MAIN_JS_PATH, path_input, path_output])
else:
output_names = "--output_layer_names=" + output_names
subprocess.check_call(
["node", MAIN_JS_PATH, output_names, path_input, path_output])
print("Mission Complete!!!")
def preprocess_from_model(path_model, path_output_dir, output_node_names=None):
"""Preprocess a model built by Keras (from single .h5 file)
:param path_model:
:param path_output_dir:
:param output_node_names:
:return: should not return anything
"""
if not valid_file(path_model):
show_invalid_message('input file', path_model)
return
model = load_from_saved_model(path_model)
enc_model = generate_encapsulate_model(model, split_layer_name_list(output_node_names))
# Generate temp Keras enc_model for further processing
save_enc_model(path_output_dir, enc_model)
convert_tfjs(path_output_dir)
clean_temp_file(path_output_dir)
def show_tfjs_model_summary(path_input):
if not valid_file(path_input):
show_invalid_message('input model file', path_input)
return
subprocess.check_call(["node", MAIN_JS_PATH, "--summary", path_input])
