* FaceSwap 3 (#1515)
* Update extract pipeline
* Update requirements + setup for nvidia
* Remove allow-growth option
* tf.keras to keras updates
* lib.model.losses - Port + fix all loss functions for Keras3
* lib.model - port initializers, layers. normalization to Keras3
* lib.model.autoclip to Keras 3
* Update mixed precision layer storage
* model file to .keras format
* Restructure nn_blocks to initialize layers in __init__
* Tensorboard
- Trainer: Add Torch compatible Tensorboard callbacks
- GUI event reader remove TF dependency
* Loss logging
- Flush TB logs on save
- Replace TB live iterator for GUI
* Backup models on total loss drop rather than per side
* Update all models to Keras3 Compat
* Remove lib.model.session
* Update clip ViT to Keras 3
* plugins.extract.mask.unet-dfl - Fix for Keras3/Torch backend
* Port AdaBelief to Keras 3
* setup.py:
- Add --dev flag for dev tool install
* Fix Keras 3 syntax
* Fix LR Finder for Keras 3
* Fix mixed precision switching for Keras 3
* Add more optimizers + open up config setting
* train: Remove updating FS1 weights to FS2 models
* Alignments: Remove support for legacy .json files
* tools.model:
- Remove TF Saved Format saving
- Fix Backup/Restore + Nan-Scan
* Fix inference model creation for Keras 3
* Preview tool: Fix for Keras3
* setup.py: Configure keras backend
* train: Migration of FS2 models to FS3
* Training: Default coverage to 100%
* Remove DirectML backend
* Update setup for MacOS
* GUI: Force line reading to UTF-8
* Remove redundant Tensorflow references
* Remove redundant code
* Legacy model loading: Fix TFLamdaOp scalar ops and DepthwiseConv2D
* Add vertical offset option for training
* Github actions: Add more python versions
* Add python version to workflow names
* Github workflow: Exclude Python 3.12 for macOS
* Implement custom training loop
* Fs3 - Add RTX5xxx and ROCm 6.1-6.4 support (#1511)
* setup.py: Add Cuda/ROCm version select options
* bump minimum python version to 3.11
* Switch from setup.cgf to pyproject.toml
* Documentation: Update all docs to use automodapi
* Allow sysinfo to run with missing packages + correctly install tk under Linux
* Bugfix: dot naming convention in clip models
* lib.config: Centralise globally rather than passing as object
- Add torch DataParallel for multi-gpu training
- GUI: Group switches together when generating cli args
- CLI: Remove deprecated multi-character argparse args
- Refactor:
- Centralise tensorboard reading/writing + unit tests
- Create trainer plugin interfaces + add original + distributed
* Update installers
- Manual Tool:
- Hide annotations for faces not meeting criteria
- Update landmarks on face add/del
- Clearer landmark annotations
- Handle non-numerics in frame number box
- Training
- Fix mis-aligned preview images
- Allows mixing legacy + new alignments for A and B
- Catch non-training images in training folder
- Catch inconsistently sized training images
- Standardize coverage ratio calculation
- lib.image - Add option to get image shape along with hash
Dfaker model:
- Add 256px mode
- train/_config.py: PEP8 Fixes. Slight description change on coverage
- models/_base.py:
- Remove unused variables from Loss()
- Delete legacy config items from state file
- Save state file on Legacy update
- PEP8
- Remove _defaults.py for models with no config options
* documentation, pep8, style, clarity updates
* Update cli.py
* Update _config.py
remove extra mask and coverage
mask type as dropdown
* Update training_data.py
move coverage / LR to global
cut down on loss description
style change
losses working in PR
* simpler logging
* legacy update
Bugfix: Fully disable keypress monitor for GUI
Bugfix: Preview - Handle missing alignments file
Config changes:
- Separate plugin defaults into their own files
- Move mask_type to global training config
- Add ability to pass in custom config files
torzdf