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