Files
torzdf 837bc2d51d Faceswap 3 (#1516)
* 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
2025-12-21 02:45:11 +00:00

196 lines
7.0 KiB
Python

#!/usr/bin python3
""" Display Frame of the Faceswap GUI
This is the large right hand area of the GUI. At default, the Analysis tab is always displayed
here. Further optional tabs will also be displayed depending on the currently executing Faceswap
task. """
import logging
import gettext
import tkinter as tk
from tkinter import ttk
from lib.logger import parse_class_init
from lib.utils import get_module_objects
from .display_analysis import Analysis
from .display_command import GraphDisplay, PreviewExtract, PreviewTrain
from .utils import get_config
logger = logging.getLogger(__name__)
# LOCALES
_LANG = gettext.translation("gui.tooltips", localedir="locales", fallback=True)
_ = _LANG.gettext
class DisplayNotebook(ttk.Notebook): # pylint:disable=too-many-ancestors
""" The tkinter Notebook that holds the display items.
Parameters
----------
parent: :class:`tk.PanedWindow`
The paned window that holds the Display Notebook
"""
def __init__(self, parent):
logger.debug(parse_class_init(locals()))
super().__init__(parent)
parent.add(self)
tk_vars = get_config().tk_vars
self._wrapper_var = tk_vars.display
self._running_task = tk_vars.running_task
self._set_wrapper_var_trace()
self._add_static_tabs()
# pylint:disable=unnecessary-comprehension
self._static_tabs = [child for child in self.tabs()]
self.bind("<<NotebookTabChanged>>", self._on_tab_change)
logger.debug("Initialized %s", self.__class__.__name__)
@property
def running_task(self):
""" :class:`tkinter.BooleanVar`: The global tkinter variable that indicates whether a
Faceswap task is currently running or not. """
return self._running_task
def _set_wrapper_var_trace(self):
""" Sets the trigger to update the displayed notebook's pages when the global tkinter
variable `display` is updated in the :class:`~lib.gui.wrapper.ProcessWrapper`. """
logger.debug("Setting wrapper var trace")
self._wrapper_var.trace("w", self._update_displaybook)
def _add_static_tabs(self):
""" Add the tabs to the Display Notebook that are permanently displayed.
Currently this is just the `Analysis` tab.
"""
logger.debug("Adding static tabs")
for tab in ("job queue", "analysis"):
if tab == "job queue":
continue # Not yet implemented
if tab == "analysis":
helptext = {"stats":
_("Summary statistics for each training session")}
frame = Analysis(self, tab, helptext)
else:
frame = self._add_frame()
self.add(frame, text=tab.title())
def _add_frame(self):
""" Add a single frame for holding a static tab's contents.
Returns
-------
ttk.Frame
The frame, packed into position
"""
logger.debug("Adding frame")
frame = ttk.Frame(self)
frame.pack(side=tk.LEFT, fill=tk.BOTH, expand=True, padx=5, pady=5)
return frame
def _command_display(self, command):
""" Build the relevant command specific tabs based on the incoming Faceswap command.
Parameters
----------
command: str
The Faceswap command that is being executed
"""
build_tabs = getattr(self, f"_{command}_tabs")
build_tabs()
def _extract_tabs(self, command="extract"):
""" Build the display tabs that are used for Faceswap extract and convert tasks.
Notes
-----
The same display tabs are used for both convert and extract tasks.
command: [`"extract"`, `"convert"`], optional
The command that the display tabs are being built for. Default: `"extract"`
"""
logger.debug("Build extract tabs")
helptext = _("Preview updates every 5 seconds")
PreviewExtract(self, "preview", helptext, 5000, command)
logger.debug("Built extract tabs")
def _train_tabs(self):
""" Build the display tabs that are used for the Faceswap train task."""
logger.debug("Build train tabs")
for tab in ("graph", "preview"):
if tab == "graph":
helptext = _("Graph showing Loss vs Iterations")
GraphDisplay(self, "graph", helptext, 5000)
elif tab == "preview":
helptext = _("Training preview. Updated on every save iteration")
PreviewTrain(self, "preview", helptext, 1000)
logger.debug("Built train tabs")
def _convert_tabs(self):
""" Build the display tabs that are used for the Faceswap convert task.
Notes
-----
The tabs displayed are the same as used for extract, so :func:`_extract_tabs` is called.
"""
logger.debug("Build convert tabs")
self._extract_tabs(command="convert")
logger.debug("Built convert tabs")
def _remove_tabs(self):
""" Remove all optional displayed command specific tabs from the notebook. """
for child in self.tabs():
if child in self._static_tabs:
continue
logger.debug("removing child: %s", child)
child_name = child.split(".")[-1]
child_object = self.children.get(child_name) # returns the OptionalDisplayPage object
if not child_object:
continue
child_object.close() # Call the OptionalDisplayPage close() method
self.forget(child)
def _update_displaybook(self, *args): # pylint:disable=unused-argument
""" Callback to be executed when the global tkinter variable `display`
(:attr:`wrapper_var`) is updated when a Faceswap task is executed.
Currently only updates when a core faceswap task (extract, train or convert) is executed.
Parameters
----------
args: tuple
Required for tkinter callback events, but unused.
"""
command = self._wrapper_var.get()
self._remove_tabs()
if not command or command not in ("extract", "train", "convert"):
return
self._command_display(command)
def _on_tab_change(self, event): # pylint:disable=unused-argument
""" Event trigger for tab change events.
Calls the selected tabs :func:`on_tab_select` method, if it exists, otherwise returns.
Parameters
----------
event: tkinter callback event
Required, but unused
"""
selected = self.select().split(".")[-1]
logger.debug("Selected tab: %s", selected)
selected_object = self.children[selected]
if hasattr(selected_object, "on_tab_select"):
logger.debug("Calling on_tab_select for '%s'", selected_object)
selected_object.on_tab_select()
else:
logger.debug("Object does not have on_tab_select method. Returning: '%s'",
selected_object)
__all__ = get_module_objects(__name__)