def process_arguments(self, arguments):
self.arguments = arguments
print("Input Directory: {}".format(self.arguments.input_dir))
print("Output Directory: {}".format(self.arguments.output_dir))
self.serializer = None
if self.arguments.serializer is None and self.arguments.alignments_path is not None:
ext = os.path.splitext(self.arguments.alignments_path)[-1]
self.serializer = Serializer.get_serializer_fromext(ext)
print(self.serializer, self.arguments.alignments_path)
else:
self.serializer = Serializer.get_serializer(self.arguments.serializer or "json")
print("Using {} serializer".format(self.serializer.ext))
print('Starting, this may take a while...')
self.output_dir = get_folder(self.arguments.output_dir)
try:
self.input_dir = get_image_paths(self.arguments.input_dir)
except:
print('Input directory not found. Please ensure it exists.')
exit(1)
self.filter = self.load_filter()
self.process()
self.finalize()
def load(self, swapped):
serializer = Serializer.get_serializer('json')
state_fn = ".".join([hdf['state'], serializer.ext])
try:
with open(str(self.model_dir / state_fn), 'rb') as fp:
state = serializer.unmarshal(fp.read().decode('utf-8'))
self._epoch_no = state['epoch_no']
except IOError as e:
print('Error loading training info:', e.strerror)
self._epoch_no = 0
except JSONDecodeError as e:
print('Error loading training info:', e.msg)
self._epoch_no = 0
(face_A,face_B) = (hdf['decoder_AH5'], hdf['decoder_BH5']) if not swapped else (hdf['decoder_BH5'], hdf['decoder_AH5'])
try:
self.encoder.load_weights(str(self.model_dir / hdf['encoderH5']))
self.decoder_A.load_weights(str(self.model_dir / face_A))
self.decoder_B.load_weights(str(self.model_dir / face_B))
print('loaded model weights')
return True
except Exception as e:
print('Failed loading existing training data.')
print(e)
return False
def load(self, swapped):
serializer = Serializer.get_serializer('json')
state_fn = ".".join([hdf['state'], serializer.ext])
try:
with open(str(self.model_dir / state_fn), 'rb') as fp:
state = serializer.unmarshal(fp.read().decode('utf-8'))
self._epoch_no = state['epoch_no']
except IOError as e:
print('Error loading training info:', e.strerror)
self._epoch_no = 0
except JSONDecodeError as e:
print('Error loading training info:', e.msg)
self._epoch_no = 0
(face_A, face_B) = (hdf['decoder_AH5'],
hdf['decoder_BH5']) if not swapped else (
hdf['decoder_BH5'], hdf['decoder_AH5'])
try:
self.encoder.load_weights(str(self.model_dir / hdf['encoderH5']))
self.decoder_A.load_weights(str(self.model_dir / face_A))
self.decoder_B.load_weights(str(self.model_dir / face_B))
print('loaded model weights')
return True
except Exception as e:
print('Failed loading existing training data.')
print(e)
return False
def process_arguments(self, arguments):
self.arguments = arguments
print("Input Directory: {}".format(self.arguments.input_dir))
print("Output Directory: {}".format(self.arguments.output_dir))
self.serializer = None
if self.arguments.serializer is None and self.arguments.alignments_path is not None:
ext = os.path.splitext(self.arguments.alignments_path)[-1]
self.serializer = Serializer.get_serializer_fromext(ext)
print(self.serializer, self.arguments.alignments_path)
else:
self.serializer = Serializer.get_serializer(self.arguments.serializer or "json")
print("Using {} serializer".format(self.serializer.ext))
print('Starting, this may take a while...')
self.output_dir = get_folder(self.arguments.output_dir)
try:
self.input_dir = get_image_paths(self.arguments.input_dir)
except:
print('Input directory not found. Please ensure it exists.')
exit(1)
self.filter = self.load_filter()
self.process()
self.finalize()
def get_serializer(self):
""" Set the serializer to be used for loading and saving alignments """
if not self.args.serializer and self.args.alignments_path:
ext = os.path.splitext(self.args.alignments_path)[-1]
serializer = Serializer.get_serializer_fromext(ext)
print("Alignments Output: {}".format(self.args.alignments_path))
else:
serializer = Serializer.get_serializer(self.args.serializer or "json")
print("Using {} serializer".format(serializer.ext))
return serializer
def get_serializer(self):
""" Set the serializer to be used for loading and saving alignments """
if not self.args.serializer and self.args.alignments_path:
ext = os.path.splitext(self.args.alignments_path)[-1]
serializer = Serializer.get_serializer_from_ext(ext)
print("Alignments Output: {}".format(self.args.alignments_path))
else:
serializer = Serializer.get_serializer(self.args.serializer)
print("Using {} serializer".format(serializer.ext))
return serializer
def get_session_names(self):
""" Get the existing session names from state file """
serializer = Serializer.get_serializer("json")
state_file = os.path.join(self.model_dir,
"{}_state.{}".format(self.model_name, serializer.ext))
with open(state_file, "rb") as inp:
state = serializer.unmarshal(inp.read().decode("utf-8"))
session_names = ["session_{}".format(key)
for key in state["sessions"].keys()]
logger.debug("Session to restore: %s", session_names)
return session_names
def get_serializer(self):
""" Set the serializer to be used for loading and
saving alignments """
if (not hasattr(self.args, "serializer") or not self.args.serializer):
if self.args.alignments_path:
ext = os.path.splitext(self.args.alignments_path)[-1]
else:
ext = "json"
serializer = Serializer.get_serializer_from_ext(ext)
else:
serializer = Serializer.get_serializer(self.args.serializer)
print("Using {} serializer".format(serializer.ext))
return serializer
def __init__(self, model_dir, model_name, training_image_size):
self.serializer = Serializer.get_serializer("json")
filename = "{}_state.{}".format(model_name, self.serializer.ext)
self.filename = str(model_dir / filename)
self.name = model_name
self.iterations = 0
self.session_iterations = 0
self.training_size = training_image_size
self.sessions = dict()
self.lowest_avg_loss = dict()
self.inputs = dict()
self.config = dict()
self.load()
self.session_id = self.new_session_id()
self.create_new_session()
def __init__(self, in_queue, queue_size, arguments):
logger.debug("Initializing %s: (args: %s, queue_size: %s, in_queue: %s)",
self.__class__.__name__, arguments, queue_size, in_queue)
self.batchsize = min(queue_size, 16)
self.args = arguments
self.in_queue = in_queue
self.out_queue = queue_manager.get_queue("patch")
self.serializer = Serializer.get_serializer("json")
self.faces_count = 0
self.verify_output = False
self.model = self.load_model()
self.predictor = self.model.converter(self.args.swap_model)
self.queues = dict()
self.thread = MultiThread(self.predict_faces, thread_count=1)
self.thread.start()
logger.debug("Initialized %s: (out_queue: %s)", self.__class__.__name__, self.out_queue)
def __init__(self, in_queue, queue_size, arguments):
logger.debug("Initializing %s: (args: %s, queue_size: %s, in_queue: %s)",
self.__class__.__name__, arguments, queue_size, in_queue)
self.batchsize = self.get_batchsize(queue_size)
self.args = arguments
self.in_queue = in_queue
self.out_queue = queue_manager.get_queue("patch")
self.serializer = Serializer.get_serializer("json")
self.faces_count = 0
self.verify_output = False
self.model = self.load_model()
self.predictor = self.model.converter(self.args.swap_model)
self.queues = dict()
self.thread = MultiThread(self.predict_faces, thread_count=1)
self.thread.start()
logger.debug("Initialized %s: (out_queue: %s)", self.__class__.__name__, self.out_queue)
def get_serializer(self, filename, serializer):
""" Set the serializer to be used for loading and
saving alignments
If a filename with a valid extension is passed in
this will be used as the serializer, otherwise the
specified serializer will be used """
extension = os.path.splitext(filename)[1]
if extension in (".json", ".p", ".yaml", ".yml"):
retval = Serializer.get_serializer_from_ext(extension)
elif serializer not in ("json", "pickle", "yaml"):
raise ValueError("Error: {} is not a valid serializer. Use "
"'json', 'pickle' or 'yaml'")
else:
retval = Serializer.get_serializer(serializer)
if self.verbose:
print("Using {} serializer for alignments".format(retval.ext))
return retval
def __init__(self, model_dir, model_name, no_logs, training_image_size):
logger.debug("Initializing %s: (model_dir: '%s', model_name: '%s', no_logs: %s, "
"training_image_size: '%s'", self.__class__.__name__, model_dir,
model_name, no_logs, training_image_size)
self.serializer = Serializer.get_serializer("json")
filename = "{}_state.{}".format(model_name, self.serializer.ext)
self.filename = str(model_dir / filename)
self.name = model_name
self.iterations = 0
self.session_iterations = 0
self.training_size = training_image_size
self.sessions = dict()
self.lowest_avg_loss = dict()
self.inputs = dict()
self.config = dict()
self.load()
self.session_id = self.new_session_id()
self.create_new_session(no_logs)
logger.debug("Initialized %s:", self.__class__.__name__)
def save_weights(self):
model_dir = str(self.model_dir)
for model in hdf.values():
backup_file(model_dir, model)
self.encoder.save_weights(str(self.model_dir / hdf['encoderH5']))
self.decoder_A.save_weights(str(self.model_dir / hdf['decoder_AH5']))
self.decoder_B.save_weights(str(self.model_dir / hdf['decoder_BH5']))
print('saved model weights')
serializer = Serializer.get_serializer('json')
state_fn = ".".join([hdf['state'], serializer.ext])
state_dir = str(self.model_dir / state_fn)
try:
with open(state_dir, 'wb') as fp:
state_json = serializer.marshal({'epoch_no': self.epoch_no})
fp.write(state_json.encode('utf-8'))
except IOError as e:
print(e.strerror)
def __init__(self, model_dir, model_name, config_changeable_items,
no_logs, pingpong, training_image_size):
logger.debug("Initializing %s: (model_dir: '%s', model_name: '%s', "
"config_changeable_items: '%s', no_logs: %s, pingpong: %s, "
"training_image_size: '%s'", self.__class__.__name__, model_dir, model_name,
config_changeable_items, no_logs, pingpong, training_image_size)
self.serializer = Serializer.get_serializer("json")
filename = "{}_state.{}".format(model_name, self.serializer.ext)
self.filename = str(model_dir / filename)
self.name = model_name
self.iterations = 0
self.session_iterations = 0
self.training_size = training_image_size
self.sessions = dict()
self.lowest_avg_loss = dict()
self.inputs = dict()
self.config = dict()
self.load(config_changeable_items)
self.session_id = self.new_session_id()
self.create_new_session(no_logs, pingpong)
logger.debug("Initialized %s:", self.__class__.__name__)
def get_serializer(filename, serializer):
""" Set the serializer to be used for loading and
saving alignments
If a filename with a valid extension is passed in
this will be used as the serializer, otherwise the
specified serializer will be used """
logger.debug("Getting serializer: (filename: '%s', serializer: '%s')",
filename, serializer)
extension = os.path.splitext(filename)[1]
if extension in (".json", ".p", ".yaml", ".yml"):
logger.debug("Serializer set from file extension: '%s'", extension)
retval = Serializer.get_serializer_from_ext(extension)
elif serializer not in ("json", "pickle", "yaml"):
raise ValueError("Error: {} is not a valid serializer. Use "
"'json', 'pickle' or 'yaml'")
else:
logger.debug("Serializer set from argument: '%s'", serializer)
retval = Serializer.get_serializer(serializer)
logger.verbose("Using '%s' serializer for alignments", retval.ext)
return retval
def save_weights(self):
model_dir = str(self.model_dir)
for model in hdf.values():
backup_file(model_dir, model)
self.encoder.save_weights(str(self.model_dir / hdf['encoderH5']))
self.decoder_A.save_weights(str(self.model_dir / hdf['decoder_AH5']))
self.decoder_B.save_weights(str(self.model_dir / hdf['decoder_BH5']))
print('saved model weights')
serializer = Serializer.get_serializer('json')
state_fn = ".".join([hdf['state'], serializer.ext])
state_dir = str(self.model_dir / state_fn)
try:
with open(state_dir, 'wb') as fp:
state_json = serializer.marshal({
'epoch_no' : self.epoch_no
})
fp.write(state_json.encode('utf-8'))
except IOError as e:
print(e.strerror)
def get_serializer(filename, serializer):
""" Set the serializer to be used for loading and
saving alignments
If a filename with a valid extension is passed in
this will be used as the serializer, otherwise the
specified serializer will be used """
logger.debug("Getting serializer: (filename: '%s', serializer: '%s')",
filename, serializer)
extension = os.path.splitext(filename)[1]
if extension in (".json", ".p", ".yaml", ".yml"):
logger.debug("Serializer set from file extension: '%s'", extension)
retval = Serializer.get_serializer_from_ext(extension)
elif serializer not in ("json", "pickle", "yaml"):
raise ValueError("Error: {} is not a valid serializer. Use "
"'json', 'pickle' or 'yaml'")
else:
logger.debug("Serializer set from argument: '%s'", serializer)
retval = Serializer.get_serializer(serializer)
logger.verbose("Using '%s' serializer for alignments", retval.ext)
return retval
def process_arguments(self, arguments):
self.arguments = arguments
print("Input Directory: {}".format(self.arguments.input_dir))
print("Output Directory: {}".format(self.arguments.output_dir))
print("Filter: {}".format(self.arguments.filter))
self.serializer = None
if self.arguments.serializer is None and self.arguments.alignments_path is not None:
ext = os.path.splitext(self.arguments.alignments_path)[-1]
self.serializer = Serializer.get_serializer_fromext(ext)
print(self.serializer, self.arguments.alignments_path)
else:
self.serializer = Serializer.get_serializer(
self.arguments.serializer or "json")
print("Using {} serializer".format(self.serializer.ext))
try:
if self.arguments.rotate_images is not None and self.arguments.rotate_images != "off":
if self.arguments.rotate_images == "on":
self.rotation_angles = range(90, 360, 90)
else:
rotation_angles = [
int(angle)
for angle in self.arguments.rotate_images.split(",")
]
if len(rotation_angles) == 1:
rotation_step_size = rotation_angles[0]
self.rotation_angles = range(rotation_step_size, 360,
rotation_step_size)
elif len(rotation_angles) > 1:
self.rotation_angles = rotation_angles
except AttributeError:
pass
print('Starting, this may take a while...')
try:
if self.arguments.skip_existing:
self.already_processed = get_image_paths(
self.arguments.output_dir)
except AttributeError:
pass
self.output_dir = get_folder(self.arguments.output_dir)
try:
try:
if self.arguments.skip_existing:
self.input_dir = get_image_paths(self.arguments.input_dir,
self.already_processed)
print('Excluding %s files' % len(self.already_processed))
else:
self.input_dir = get_image_paths(self.arguments.input_dir)
except AttributeError:
self.input_dir = get_image_paths(self.arguments.input_dir)
except:
print('Input directory not found. Please ensure it exists.')
exit(1)
self.filter = self.load_filter()
self.process()
self.finalize()
def set_destination_serializer(self):
""" set the destination serializer """
self.serializer = Serializer.get_serializer(self.destination_format)
