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import numpy as np
import onnx
import torch
def convert_onnx(net, path_module, output, opset=11, simplify=False):
assert isinstance(net, torch.nn.Module)
img = np.random.randint(0, 255, size=(112, 112, 3), dtype=np.int32)
img = img.astype(np.float)
img = (img / 255. - 0.5) / 0.5 # torch style norm
img = img.transpose((2, 0, 1))
img = torch.from_numpy(img).unsqueeze(0).float()
weight = torch.load(path_module)
net.load_state_dict(weight)
net.eval()
torch.onnx.export(net, img, output, keep_initializers_as_inputs=False, verbose=False, opset_version=opset)
model = onnx.load(output)
graph = model.graph
graph.input[0].type.tensor_type.shape.dim[0].dim_param = 'None'
if simplify:
from onnxsim import simplify
model, check = simplify(model)
assert check, "Simplified ONNX model could not be validated"
onnx.save(model, output)
if __name__ == '__main__':
import os
import argparse
from backbones import get_model
parser = argparse.ArgumentParser(description='ArcFace PyTorch to onnx')
parser.add_argument('input', type=str, help='input backbone.pth file or path')
parser.add_argument('--output', type=str, default=None, help='output onnx path')
parser.add_argument('--network', type=str, default=None, help='backbone network')
parser.add_argument('--simplify', type=bool, default=False, help='onnx simplify')
args = parser.parse_args()
input_file = args.input
if os.path.isdir(input_file):
input_file = os.path.join(input_file, "backbone.pth")
assert os.path.exists(input_file)
model_name = os.path.basename(os.path.dirname(input_file)).lower()
params = model_name.split("_")
if len(params) >= 3 and params[1] in ('arcface', 'cosface'):
if args.network is None:
args.network = params[2]
assert args.network is not None
print(args)
backbone_onnx = get_model(args.network, dropout=0)
output_path = args.output
if output_path is None:
output_path = os.path.join(os.path.dirname(__file__), 'onnx')
if not os.path.exists(output_path):
os.makedirs(output_path)
assert os.path.isdir(output_path)
output_file = os.path.join(output_path, "%s.onnx" % model_name)
convert_onnx(backbone_onnx, input_file, output_file, simplify=args.simplify)
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