def main():
args = args_parser.parse_args()
if args.sub_command == 'onnx2tnn':
onnx_path = parse_path.parse_path(args.onnx_path)
output_dir = parse_path.parse_path(args.output_dir)
version = args.version
optimize = args.optimize
half = args.half
onnx_path = parse_path.parse_path(onnx_path)
output_dir = parse_path.parse_path(output_dir)
onnx2tnn.convert(onnx_path, output_dir, version, optimize, half)
elif args.sub_command == 'caffe2tnn':
proto_path = parse_path.parse_path(args.proto_path)
model_path = parse_path.parse_path(args.model_path)
output_dir = parse_path.parse_path(args.output_dir)
version = args.version
optimize = args.optimize
half = args.half
caffe2tnn.convert(proto_path, model_path, output_dir, version, optimize, half)
elif args.sub_command == 'tf2tnn':
tf_path = parse_path.parse_path(args.tf_path)
output_dir = parse_path.parse_path(args.output_dir)
input_names = args.input_names
output_names = args.output_names
version = args.version
optimize = args.optimize
half = args.half
tf2tnn.convert(tf_path, input_names, output_names, output_dir, version, optimize, half)
else:
print("Do not support convert!")
def convert(tf_path, input_names, output_names, output_dir, version, optimize, half, align=False, not_fold_const=False,
input_path=None, refer_path=None):
logging.info("Converter Tensorflow to TNN model\n")
checker.check_file_exist(tf_path)
model_name = os.path.basename(tf_path)
if output_dir is None or not os.path.isdir(output_dir):
output_dir = os.path.dirname(tf_path)
checker.check_file_exist(output_dir)
model_name = model_name[:-len(".pb")]
onnx_path = os.path.join(output_dir, model_name + ".onnx")
if tf2onnx(tf_path, input_names, output_names, onnx_path, not_fold_const) is False:
logging.error("Oh No, tf2onnx failed :(\n")
sys.exit(return_code.CONVERT_FAILED)
else:
logging.info("Convert TensorFlow to ONNX model succeed!\n")
if version is None:
version = "v1.0"
checker.check_file_exist(onnx_path)
onnx2tnn.convert(onnx_path, output_dir, version, optimize, half)
if align is True:
proto_suffix = '.tnnproto'
model_suffix = '.tnnmodel'
onnx_base_name = os.path.basename(onnx_path)
if optimize is True:
tnn_proto_name = onnx_base_name[:-len('.onnx')] + '.opt' + proto_suffix
tnn_model_name = onnx_base_name[:-len('.onnx')] + '.opt' + model_suffix
else:
tnn_proto_name = onnx_base_name[:-len('.onnx')] + proto_suffix
tnn_model_name = onnx_base_name[:-len('.onnx')] + model_suffix
tnn_proto_path = os.path.join(output_dir, tnn_proto_name)
tnn_model_path = os.path.join(output_dir, tnn_model_name)
align_model.align_model(onnx_path, tnn_proto_path, tnn_model_path, input_path, refer_path)
def convert(proto_path,
model_path,
output_dir,
version,
optimize,
half,
align=False,
input_path=None,
refer_path=None):
logging.info("Converter Caffe to ONNX Model\n")
checker.check_file_exist(proto_path)
checker.check_file_exist(model_path)
if output_dir is None:
output_dir = os.path.dirname(proto_path)
checker.check_file_exist(output_dir)
proto_name = os.path.basename(proto_path)
proto_name = proto_name[:-len(".prototxt")]
onnx_path = os.path.join(output_dir, proto_name + ".onnx")
if caffe2onnx(proto_path, model_path, onnx_path) is False:
logging.error("Oh No, caff2onnx failed :(\n")
sys.exit(return_code.CONVERT_FAILED)
else:
logging.info("Congratulations! caffe2onnx succeed!\n")
if version is None:
version = "v1.0"
is_ssd = checker.is_ssd_model(proto_path)
if is_ssd:
onnx2tnn.convert(onnx_path,
output_dir,
version,
False,
half,
is_ssd=True)
else:
onnx2tnn.convert(onnx_path, output_dir, version, optimize, half)
if is_ssd and ((input_path is None) or (refer_path is None)):
align = False
optimize = False
if align is True:
proto_suffix = '.tnnproto'
model_suffix = '.tnnmodel'
onnx_base_name = os.path.basename(onnx_path)
if optimize is True:
tnn_proto_name = onnx_base_name[:-len('.onnx'
)] + '.opt' + proto_suffix
tnn_model_name = onnx_base_name[:-len('.onnx'
)] + '.opt' + model_suffix
else:
tnn_proto_name = onnx_base_name[:-len('.onnx')] + proto_suffix
tnn_model_name = onnx_base_name[:-len('.onnx')] + model_suffix
tnn_proto_path = os.path.join(output_dir, tnn_proto_name)
tnn_model_path = os.path.join(output_dir, tnn_model_name)
align_model.align_model(onnx_path, tnn_proto_path, tnn_model_path,
input_path, refer_path)
def main():
args = args_parser.parse_args()
if args.sub_command == 'onnx2tnn':
onnx_path = parse_path.parse_path(args.onnx_path)
output_dir = parse_path.parse_path(args.output_dir)
input_names = args.input_names
version = args.version
optimize = args.optimize
half = args.half
align = args.align
input_file = args.input_file_path
ref_file = args.refer_file_path
onnx_path = parse_path.parse_path(onnx_path)
output_dir = parse_path.parse_path(output_dir)
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
onnx2tnn.convert(onnx_path, output_dir, version, optimize, half, align,
input_file, ref_file, input_names)
elif args.sub_command == 'caffe2tnn':
proto_path = parse_path.parse_path(args.proto_path)
model_path = parse_path.parse_path(args.model_path)
output_dir = parse_path.parse_path(args.output_dir)
version = args.version
optimize = args.optimize
half = args.half
align = args.align
input_file = args.input_file_path
ref_file = args.refer_file_path
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
caffe2tnn.convert(proto_path, model_path, output_dir, version,
optimize, half, align, input_file, ref_file)
elif args.sub_command == 'tf2tnn':
tf_path = parse_path.parse_path(args.tf_path)
output_dir = parse_path.parse_path(args.output_dir)
input_names = args.input_names
output_names = args.output_names
version = args.version
optimize = args.optimize
half = args.half
align = args.align
not_fold_const = args.not_fold_const
input_file = args.input_file_path
ref_file = args.refer_file_path
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
tf2tnn.convert(tf_path, input_names, output_names, output_dir, version,
optimize, half, align, not_fold_const, input_file,
ref_file)
else:
print("Do not support convert!")
def convert(tf_path, input_names, output_names, output_dir, version, optimize, half):
checker.check_file_exist(tf_path)
model_name = os.path.basename(tf_path)
if output_dir is None or not os.path.isdir(output_dir):
output_dir = os.path.dirname(tf_path)
checker.check_file_exist(output_dir)
model_name = model_name[:-len(".pb")]
onnx_path = os.path.join(output_dir, model_name + ".onnx")
if tf2onnx(tf_path, input_names, output_names, onnx_path) is False:
print("Oh No, tf2onnx failed")
else:
print("congratulations! tf2onnx succeed!")
if version is None:
version = "v1.0"
checker.check_file_exist(onnx_path)
onnx2tnn.convert(onnx_path, output_dir, version, optimize, half)
def convert(proto_path,
model_path,
output_dir,
version,
optimize,
half,
align=False,
input_path=None,
refer_path=None):
checker.check_file_exist(proto_path)
checker.check_file_exist(model_path)
if output_dir is None:
output_dir = os.path.dirname(proto_path)
checker.check_file_exist(output_dir)
proto_name = os.path.basename(proto_path)
proto_name = proto_name[:-len(".prototxt")]
onnx_path = os.path.join(output_dir, proto_name + ".onnx")
if caffe2onnx(proto_path, model_path, onnx_path) is False:
print("Oh No, caff2onnx failed")
else:
print("congratulations! caffe2onnx succeed!")
if version is None:
version = "v1.0"
is_ssd = checker.is_ssd_model(proto_path)
if is_ssd:
onnx2tnn.convert(onnx_path, output_dir, version, False, half)
else:
onnx2tnn.convert(onnx_path, output_dir, version, optimize, half)
if align is True:
proto_suffix = '.tnnproto'
model_suffix = '.tnnmodel'
onnx_base_name = os.path.basename(onnx_path)
if optimize is True:
tnn_proto_name = onnx_base_name[:-len('.onnx'
)] + '.opt' + proto_suffix
tnn_model_name = onnx_base_name[:-len('.onnx'
)] + '.opt' + model_suffix
else:
tnn_proto_name = onnx_base_name[:-len('.onnx')] + proto_suffix
tnn_model_name = onnx_base_name[:-len('.onnx')] + model_suffix
tnn_proto_path = os.path.join(output_dir, tnn_proto_name)
tnn_model_path = os.path.join(output_dir, tnn_model_name)
align_model.align_model(onnx_path, tnn_proto_path, tnn_model_path,
input_path, refer_path)
def convert(tf_path,
input_names,
output_names,
output_dir,
version,
optimize,
half,
align=False,
not_fold_const=False,
input_path=None,
refer_path=None):
checker.check_file_exist(tf_path)
model_name = os.path.basename(tf_path)
if output_dir is None or not os.path.isdir(output_dir):
output_dir = os.path.dirname(tf_path)
checker.check_file_exist(output_dir)
model_name = model_name[:-len(".pb")]
onnx_path = os.path.join(output_dir, model_name + ".onnx")
if tf2onnx(tf_path, input_names, output_names, onnx_path,
not_fold_const) is False:
print("Oh No, tf2onnx failed")
else:
print("congratulations! tf2onnx succeed!")
if version is None:
version = "v1.0"
checker.check_file_exist(onnx_path)
onnx2tnn.convert(onnx_path, output_dir, version, optimize, half)
if align is True:
proto_suffix = '.tnnproto'
model_suffix = '.tnnmodel'
onnx_base_name = os.path.basename(onnx_path)
if optimize is True:
tnn_proto_name = onnx_base_name[:-len('.onnx'
)] + '.opt' + proto_suffix
tnn_model_name = onnx_base_name[:-len('.onnx'
)] + '.opt' + model_suffix
else:
tnn_proto_name = onnx_base_name[:-len('.onnx')] + proto_suffix
tnn_model_name = onnx_base_name[:-len('.onnx')] + model_suffix
tnn_proto_path = os.path.join(output_dir, tnn_proto_name)
tnn_model_path = os.path.join(output_dir, tnn_model_name)
align_model.align_model(onnx_path, tnn_proto_path, tnn_model_path,
input_path, refer_path)
def convert(proto_path, model_path, output_dir, version, optimize, half):
checker.check_file_exist(proto_path)
checker.check_file_exist(model_path)
if output_dir is None:
output_dir = os.path.dirname(proto_path)
checker.check_file_exist(output_dir)
proto_name = os.path.basename(proto_path)
proto_name = proto_name[:-len(".prototxt")]
onnx_path = os.path.join(output_dir, proto_name + ".onnx")
if caffe2onnx(proto_path, model_path, onnx_path) is False:
print("Oh No, caff2onnx failed")
else:
print("congratulations! caffe2onnx succeed!")
if version is None:
version = "v1.0"
is_ssd = checker.is_ssd_model(proto_path)
if is_ssd:
onnx2tnn.convert(onnx_path, output_dir, version, False, half)
else:
onnx2tnn.convert(onnx_path, output_dir, version, optimize, half)
def main():
parser = args_parser.parse_args()
args = parser.parse_args()
debug_mode: bool = args.debug
if debug_mode is True:
logging.basicConfig(level=logging.DEBUG, format='')
else:
logging.basicConfig(level=logging.INFO, format='')
logging.info("\n{} convert model, please wait a moment {}\n".format(
"-" * 10, "-" * 10))
if args.sub_command == 'onnx2tnn':
onnx_path = parse_path.parse_path(args.onnx_path)
output_dir = parse_path.parse_path(args.output_dir)
version = args.version
optimize = args.optimize
half = args.half
align = args.align
input_file = args.input_file_path
ref_file = args.refer_file_path
onnx_path = parse_path.parse_path(onnx_path)
output_dir = parse_path.parse_path(output_dir)
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
input_names = None
if args.input_names is not None:
input_names = ""
for item in args.input_names:
input_names += (item + " ")
try:
onnx2tnn.convert(onnx_path,
output_dir,
version,
optimize,
half,
align,
input_file,
ref_file,
input_names,
debug_mode=debug_mode)
except Exception as err:
logging.error("Conversion to tnn failed :(\n")
logging.error(err)
elif args.sub_command == 'caffe2tnn':
proto_path = parse_path.parse_path(args.proto_path)
model_path = parse_path.parse_path(args.model_path)
output_dir = parse_path.parse_path(args.output_dir)
version = args.version
optimize = args.optimize
half = args.half
align = args.align
input_file = args.input_file_path
ref_file = args.refer_file_path
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
try:
caffe2tnn.convert(proto_path,
model_path,
output_dir,
version,
optimize,
half,
align,
input_file,
ref_file,
debug_mode=debug_mode)
except Exception as err:
logging.error("Conversion to tnn failed :(\n")
logging.error(err)
elif args.sub_command == 'tf2tnn':
tf_path = parse_path.parse_path(args.tf_path)
output_dir = parse_path.parse_path(args.output_dir)
input_names = args.input_names
output_names = args.output_names
version = args.version
optimize = args.optimize
half = args.half
align = args.align
not_fold_const = args.not_fold_const
input_file = args.input_file_path
ref_file = args.refer_file_path
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
try:
tf2tnn.convert(tf_path,
input_names,
output_names,
output_dir,
version,
optimize,
half,
align,
not_fold_const,
input_file,
ref_file,
debug_mode=debug_mode)
except Exception as err:
logging.error("\nConversion to tnn failed :(\n")
logging.error(err)
elif args.sub_command == 'tflite2tnn':
tf_path = parse_path.parse_path(args.tf_path)
output_dir = parse_path.parse_path(args.output_dir)
version = args.version
align = args.align
input_file = args.input_file_path
ref_file = args.refer_file_path
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
try:
tflite2tnn.convert(tf_path,
output_dir,
version,
align,
input_file,
ref_file,
debug_mode=debug_mode)
except Exception as err:
logging.error("\n Conversion to tnn failed :(\n")
logging.error(err)
elif args.sub_command is None:
parser.print_help()
else:
logging.info("Do not support convert!")
def main():
parser = args_parser.parse_args()
args = parser.parse_args()
logging.info("\n{} convert model, please wait a moment {}\n".format(
"-" * 10, "-" * 10))
if args.sub_command == 'onnx2tnn':
onnx_path = parse_path.parse_path(args.onnx_path)
output_dir = parse_path.parse_path(args.output_dir)
input_names = args.input_names
version = args.version
optimize = args.optimize
half = args.half
align = args.align
input_file = args.input_file_path
ref_file = args.refer_file_path
onnx_path = parse_path.parse_path(onnx_path)
output_dir = parse_path.parse_path(output_dir)
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
try:
onnx2tnn.convert(onnx_path, output_dir, version, optimize, half,
align, input_file, ref_file, input_names)
except Exception as err:
logging.error("Conversion to tnn failed :(\n")
elif args.sub_command == 'caffe2tnn':
proto_path = parse_path.parse_path(args.proto_path)
model_path = parse_path.parse_path(args.model_path)
output_dir = parse_path.parse_path(args.output_dir)
version = args.version
optimize = args.optimize
half = args.half
align = args.align
input_file = args.input_file_path
ref_file = args.refer_file_path
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
try:
caffe2tnn.convert(proto_path, model_path, output_dir, version,
optimize, half, align, input_file, ref_file)
except Exception as err:
logging.error("Conversion to tnn failed :(\n")
elif args.sub_command == 'tf2tnn':
tf_path = parse_path.parse_path(args.tf_path)
output_dir = parse_path.parse_path(args.output_dir)
input_names = args.input_names
output_names = args.output_names
version = args.version
optimize = args.optimize
half = args.half
align = args.align
not_fold_const = args.not_fold_const
input_file = args.input_file_path
ref_file = args.refer_file_path
input_file = parse_path.parse_path(input_file)
ref_file = parse_path.parse_path(ref_file)
try:
tf2tnn.convert(tf_path, input_names, output_names, output_dir,
version, optimize, half, align, not_fold_const,
input_file, ref_file)
except Exception as err:
logging.error("\nConversion to tnn failed :(\n")
elif args.sub_command is None:
parser.print_help()
else:
logging.info("Do not support convert!")