mirror of
https://github.com/facefusion/facefusion-labs.git
synced 2026-05-22 23:59:40 +02:00
Henry Ruhs
2e6394565a
* add sync batchnorm * replace random.choice with hash * fifty percent reduction * fix discriminator input * restore dataset.py * Remove duplicates * add discriminator_ratio to config * fix onnx export bug: replace round() with int() * Fix embedding naming * Introduce ModelWithConfigCheckpoint callback (#86) * Fix dist ini * Style: Refactor typing and improve code clarity in training.py (#88) * Add type casting for trainer params * Add type casting for trainer params * Add type casting for trainer params * Remove inplace activations for torch.compile compatibility (#89) * Fix README * improvise with norm layers & weighted average * add skip layer * use gelu instead of leaky_relu * cleanup * cleanup * Update dependencies * Different defaults and enable validation * Different defaults and enable validation * Revert to higher batch size * Just use copy over copy2 --------- Co-authored-by: harisreedhar <h4harisreedhar.s.s@gmail.com> Co-authored-by: NeuroDonu <112660822+NeuroDonu@users.noreply.github.com> Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>
105 lines
1.4 KiB
Markdown
105 lines
1.4 KiB
Markdown
CrossFace
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=========
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> Seamless face embedding across various models.
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Preview
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-------
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Installation
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------------
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```
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pip install -r requirements.txt
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```
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Setup
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-----
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This `config.ini` utilizes the MegaFace dataset to train the CrossFace model for SimSwap.
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```
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[training.dataset]
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file_pattern = .datasets/megaface/**/*.jpg
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```
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```
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[training.loader]
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batch_size = 128
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num_workers = 8
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split_ratio = 0.95
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```
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```
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[training.model]
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source_path = .models/arcface_w600k_r50.pt
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target_path = .models/arcface_simswap.pt
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```
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```
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[training.trainer]
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max_epochs = 4096
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strategy = auto
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precision = 16-mixed
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```
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```
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[training.optimizer]
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learning_rate = 0.001
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```
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```
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[training.logger]
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logger_path = .logs
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logger_name = crossface_simswap
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```
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```
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[training.output]
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directory_path = .outputs
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file_pattern = crossface_simswap_{epoch}_{step}
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resume_path = .outputs/last.ckpt
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```
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```
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[exporting]
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directory_path = .exports
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source_path = .outputs/last.ckpt
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target_path = .exports/crossface_simswap.onnx
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ir_version = 10
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opset_version = 15
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```
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Training
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--------
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Train the model.
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```
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python train.py
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```
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Launch the TensorBoard to monitor the training.
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```
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tensorboard --logdir .logs
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```
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Exporting
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---------
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Export the model to ONNX.
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```
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python export.py
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```
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