mirror of
https://github.com/facefusion/facefusion-labs.git
synced 2026-05-22 23:59:40 +02:00
henryruhs
31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
import os
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from configparser import ConfigParser
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import torch
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from .training import FaceSwapperTrainer
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CONFIG_PARSER = ConfigParser()
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CONFIG_PARSER.read('config.ini')
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def export() -> None:
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config =\
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{
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'directory_path': CONFIG_PARSER.get('exporting', 'directory_path'),
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'source_path': CONFIG_PARSER.get('exporting', 'source_path'),
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'target_path': CONFIG_PARSER.get('exporting', 'target_path'),
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'target_size': CONFIG_PARSER.getint('exporting', 'target_size'),
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'ir_version': CONFIG_PARSER.getint('exporting', 'ir_version'),
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'opset_version': CONFIG_PARSER.getint('exporting', 'opset_version')
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}
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os.makedirs(config.get('directory_path'), exist_ok = True)
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model = FaceSwapperTrainer.load_from_checkpoint(config.get('source_path'), map_location = 'cpu')
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model.eval()
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model.ir_version = torch.tensor(config.get('ir_version'))
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source_tensor = torch.randn(1, 512)
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target_tensor = torch.randn(1, 3, config.get('target_size'), config.get('target_size'))
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torch.onnx.export(model, (source_tensor, target_tensor), config.get('target_path'), input_names = [ 'source', 'target' ], output_names = [ 'output' ], opset_version = config.get('opset_version'))
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