mirror of
https://github.com/deepfakes/faceswap.git
synced 2026-10-29 06:03:41 +08:00
torzdf
837bc2d51d
* 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
90 lines
2.8 KiB
Python
Executable File
90 lines
2.8 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
""" The default options for the faceswap Realface Model plugin.
|
|
|
|
Defaults files should be named `<plugin_name>_defaults.py`
|
|
|
|
Any qualifying items placed into this file will automatically get added to the relevant config
|
|
.ini files within the faceswap/config folder and added to the relevant GUI settings page.
|
|
|
|
The following variable should be defined:
|
|
|
|
Parameters
|
|
----------
|
|
HELPTEXT: str
|
|
A string describing what this plugin does
|
|
|
|
Further plugin configuration options are assigned using:
|
|
>>> <config_item> = ConfigItem(...)
|
|
|
|
where <config_item> is the name of the configuration option to be added (lower-case, alpha-numeric
|
|
+ underscore only) and ConfigItem(...) is the [`~lib.config.objects.ConfigItem`] data for the
|
|
option.
|
|
|
|
See the docstring/ReadtheDocs documentation required parameters for the ConfigItem object.
|
|
Items will be grouped together as per their `group` parameter, but otherwise will be processed in
|
|
the order that they are added to this module.
|
|
from lib.config import ConfigItem
|
|
"""
|
|
# pylint:disable=duplicate-code
|
|
from lib.config import ConfigItem
|
|
|
|
|
|
HELPTEXT = (
|
|
"An extra detailed variant of Original model.\n"
|
|
"Incorporates ideas from Bryanlyon and inspiration from the Villain model.\n"
|
|
"Requires about 6GB-8GB of VRAM (batchsize 8-16).\n"
|
|
)
|
|
|
|
|
|
input_size = ConfigItem(
|
|
datatype=int,
|
|
default=64,
|
|
group="size",
|
|
info="Resolution (in pixels) of the input image to train on.\n"
|
|
"BE AWARE Larger resolution will dramatically increase VRAM requirements.\n"
|
|
"Higher resolutions may increase prediction accuracy, but does not effect the "
|
|
"resulting output size.\nMust be between 64 and 128 and be divisible by 16.",
|
|
rounding=16,
|
|
min_max=(64, 128),
|
|
fixed=True)
|
|
|
|
output_size = ConfigItem(
|
|
datatype=int,
|
|
default=128,
|
|
group="size",
|
|
info="Output image resolution (in pixels).\nBe aware that larger resolution will "
|
|
"increase VRAM requirements.\nNB: Must be between 64 and 256 and be divisible "
|
|
"by 16.",
|
|
rounding=16,
|
|
min_max=(64, 256),
|
|
fixed=True)
|
|
|
|
dense_nodes = ConfigItem(
|
|
datatype=int,
|
|
default=1536,
|
|
group="network",
|
|
info="Number of nodes for decoder. Might affect your model's ability to learn in "
|
|
"general.\nNote that: Lower values will affect the ability to predict "
|
|
"details.",
|
|
rounding=64,
|
|
min_max=(768, 2048),
|
|
fixed=True)
|
|
|
|
complexity_encoder = ConfigItem(
|
|
datatype=int,
|
|
default=128,
|
|
group="network",
|
|
info="Encoder Convolution Layer Complexity. sensible ranges: 128 to 150.",
|
|
rounding=4,
|
|
min_max=(96, 160),
|
|
fixed=True)
|
|
|
|
complexity_decoder = ConfigItem(
|
|
datatype=int,
|
|
default=512,
|
|
group="network",
|
|
info="Decoder Complexity.",
|
|
rounding=4,
|
|
min_max=(512, 544),
|
|
fixed=True)
|