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faceswap/lib/gui/menu.py
torzdf cd00859c40
model_refactor (#571) (#572)
* model_refactor (#571)

* original model to new structure

* IAE model to new structure

* OriginalHiRes to new structure

* Fix trainer for different resolutions

* Initial config implementation

* Configparse library added

* improved training data loader

* dfaker model working

* Add logging to training functions

* Non blocking input for cli training

* Add error handling to threads. Add non-mp queues to queue_handler

* Improved Model Building and NNMeta

* refactor lib/models

* training refactor. DFL H128 model Implementation

* Dfaker - use hashes

* Move timelapse. Remove perceptual loss arg

* Update INSTALL.md. Add logger formatting. Update Dfaker training

* DFL h128 partially ported

* Add mask to dfaker (#573)

* Remove old models. Add mask to dfaker

* dfl mask. Make masks selectable in config (#575)

* DFL H128 Mask. Mask type selectable in config.

* remove gan_v2_2

* Creating Input Size config for models

Creating Input Size config for models

Will be used downstream in converters.

Also name change of image_shape to input_shape to clarify ( for future models with potentially different output_shapes)

* Add mask loss options to config

* MTCNN options to config.ini. Remove GAN config. Update USAGE.md

* Add sliders for numerical values in GUI

* Add config plugins menu to gui. Validate config

* Only backup model if loss has dropped. Get training working again

* bugfixes

* Standardise loss printing

* GUI idle cpu fixes. Graph loss fix.

* mutli-gpu logging bugfix

* Merge branch 'staging' into train_refactor

* backup state file

* Crash protection: Only backup if both total losses have dropped

* Port OriginalHiRes_RC4 to train_refactor (OriginalHiRes)

* Load and save model structure with weights

* Slight code update

* Improve config loader. Add subpixel opt to all models. Config to state

* Show samples... wrong input

* Remove AE topology. Add input/output shapes to State

* Port original_villain (birb/VillainGuy) model to faceswap

* Add plugin info to GUI config pages

* Load input shape from state. IAE Config options.

* Fix transform_kwargs.
Coverage to ratio.
Bugfix mask detection

* Suppress keras userwarnings.
Automate zoom.
Coverage_ratio to model def.

* Consolidation of converters & refactor (#574)

* Consolidation of converters & refactor

Initial Upload of alpha

Items
- consolidate convert_mased & convert_adjust into one converter
-add average color adjust to convert_masked
-allow mask transition blur size to be a fixed integer of pixels and a fraction of the facial mask size
-allow erosion/dilation size to be a fixed integer of pixels and a fraction of the facial mask size
-eliminate redundant type conversions to avoid multiple round-off errors
-refactor loops for vectorization/speed
-reorganize for clarity & style changes

TODO
- bug/issues with warping the new face onto a transparent old image...use a cleanup mask for now
- issues with mask border giving black ring at zero erosion .. investigate
- remove GAN ??
- test enlargment factors of umeyama standard face .. match to coverage factor
- make enlargment factor a model parameter
- remove convert_adjusted and referencing code when finished

* Update Convert_Masked.py

default blur size of 2 to match original...
description of enlargement tests
breakout matrxi scaling into def

* Enlargment scale as a cli parameter

* Update cli.py

* dynamic interpolation algorithm

Compute x & y scale factors from the affine matrix on the fly by QR decomp.
Choose interpolation alogrithm for the affine warp based on an upsample or downsample for each image

* input size
input size from config

* fix issues with <1.0 erosion

* Update convert.py

* Update Convert_Adjust.py

more work on the way to merginf

* Clean up help note on sharpen

* cleanup seamless

* Delete Convert_Adjust.py

* Update umeyama.py

* Update training_data.py

* swapping

* segmentation stub

* changes to convert.str

* Update masked.py

* Backwards compatibility fix for models
Get converter running

* Convert:
Move masks to class.
bugfix blur_size
some linting

* mask fix

* convert fixes

- missing facehull_rect re-added
- coverage to %
- corrected coverage logic
- cleanup of gui option ordering

* Update cli.py

* default for blur

* Update masked.py

* added preliminary low_mem version of OriginalHighRes model plugin

* Code cleanup, minor fixes

* Update masked.py

* Update masked.py

* Add dfl mask to convert

* histogram fix & seamless location

* update

* revert

* bugfix: Load actual configuration in gui

* Standardize nn_blocks

* Update cli.py

* Minor code amends

* Fix Original HiRes model

* Add masks to preview output for mask trainers
refactor trainer.__base.py

* Masked trainers converter support

* convert bugfix

* Bugfix: Converter for masked (dfl/dfaker) trainers

* Additional Losses (#592)

* initial upload

* Delete blur.py

* default initializer = He instead of Glorot (#588)

* Allow kernel_initializer to be overridable

* Add ICNR Initializer option for upscale on all models.

* Hopefully fixes RSoDs with original-highres model plugin

* remove debug line

* Original-HighRes model plugin Red Screen of Death fix, take #2

* Move global options to _base. Rename Villain model

* clipnorm and res block biases

* scale the end of res block

* res block

* dfaker pre-activation res

* OHRES pre-activation

* villain pre-activation

* tabs/space in nn_blocks

* fix for histogram with mask all set to zero

* fix to prevent two networks with same name

* GUI: Wider tooltips. Improve TQDM capture

* Fix regex bug

* Convert padding=48 to ratio of image size

* Add size option to alignments tool extract

* Pass through training image size to convert from model

* Convert: Pull training coverage from model

* convert: coverage, blur and erode to percent

* simplify matrix scaling

* ordering of sliders in train

* Add matrix scaling to utils. Use interpolation in lib.aligner transform

* masked.py Import get_matrix_scaling from utils

* fix circular import

* Update masked.py

* quick fix for matrix scaling

* testing thus for now

* tqdm regex capture bugfix

* Minor ammends

* blur size cleanup

* Remove coverage option from convert (Now cascades from model)

* Implement convert for all model types

* Add mask option and coverage option to all existing models

* bugfix for model loading on convert

* debug print removal

* Bugfix for masks in dfl_h128 and iae

* Update preview display. Add preview scaling to cli

* mask notes

* Delete training_data_v2.py

errant file

* training data variables

* Fix timelapse function

* Add new config items to state file for legacy purposes

* Slight GUI tweak

* Raise exception if problem with loaded model

* Add Tensorboard support (Logs stored in model directory)

* ICNR fix

* loss bugfix

* convert bugfix

* Move ini files to config folder. Make TensorBoard optional

* Fix training data for unbalanced inputs/outputs

* Fix config "none" test

* Keep helptext in .ini files when saving config from GUI

* Remove frame_dims from alignments

* Add no-flip and warp-to-landmarks cli options

* Revert OHR to RC4_fix version

* Fix lowmem mode on OHR model

* padding to variable

* Save models in parallel threads

* Speed-up of res_block stability

* Automated Reflection Padding

* Reflect Padding as a training option

Includes auto-calculation of proper padding shapes, input_shapes, output_shapes

Flag included in config now

* rest of reflect padding

* Move TB logging to cli. Session info to state file

* Add session iterations to state file

* Add recent files to menu. GUI code tidy up

* [GUI] Fix recent file list update issue

* Add correct loss names to TensorBoard logs

* Update live graph to use TensorBoard and remove animation

* Fix analysis tab. GUI optimizations

* Analysis Graph popup to Tensorboard Logs

* [GUI] Bug fix for graphing for models with hypens in name

* [GUI] Correctly split loss to tabs during training

* [GUI] Add loss type selection to analysis graph

* Fix store command name in recent files. Switch to correct tab on open

* [GUI] Disable training graph when 'no-logs' is selected

* Fix graphing race condition

* rename original_hires model to unbalanced
2019-02-09 18:35:12 +00:00

134 lines
5.4 KiB
Python

#!/usr/bin python3
""" The Menu Bars for faceswap GUI """
import logging
import os
import sys
import tkinter as tk
from importlib import import_module
from lib.Serializer import JSONSerializer
from .utils import get_config
from .popup_configure import popup_config
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
class MainMenuBar(tk.Menu):
""" GUI Main Menu Bar """
def __init__(self, master=None):
logger.debug("Initializing %s", self.__class__.__name__)
super().__init__(master)
self.root = master
self.config = get_config()
self.file_menu = tk.Menu(self, tearoff=0)
self.recent_menu = tk.Menu(self.file_menu, tearoff=0, postcommand=self.refresh_recent_menu)
self.edit_menu = tk.Menu(self, tearoff=0)
self.build_file_menu()
self.build_edit_menu()
logger.debug("Initialized %s", self.__class__.__name__)
def build_file_menu(self):
""" Add the file menu to the menu bar """
logger.debug("Building File menu")
self.file_menu.add_command(
label="Load full config...", underline=0, command=self.config.load)
self.file_menu.add_command(
label="Save full config...", underline=0, command=self.config.save)
self.file_menu.add_separator()
self.file_menu.add_cascade(label="Open recent", underline=6, menu=self.recent_menu)
self.file_menu.add_separator()
self.file_menu.add_command(
label="Reset all to default", underline=0, command=self.config.cli_opts.reset)
self.file_menu.add_command(
label="Clear all", underline=0, command=self.config.cli_opts.clear)
self.file_menu.add_separator()
self.file_menu.add_command(label="Quit", underline=0, command=self.root.close_app)
self.add_cascade(label="File", menu=self.file_menu, underline=0)
logger.debug("Built File menu")
def build_recent_menu(self):
""" Load recent files into menu bar """
logger.debug("Building Recent Files menu")
serializer = JSONSerializer
menu_file = os.path.join(self.config.pathcache, ".recent.json")
if not os.path.isfile(menu_file):
self.clear_recent_files(serializer, menu_file)
with open(menu_file, "rb") as inp:
recent_files = serializer.unmarshal(inp.read().decode("utf-8"))
logger.debug("Loaded recent files: %s", recent_files)
for recent_item in recent_files:
filename, command = recent_item
logger.debug("processing: ('%s', %s)", filename, command)
if not os.path.isfile(filename):
logger.debug("File does not exist")
continue
lbl_command = command if command else "All"
self.recent_menu.add_command(
label="{} ({})".format(filename, lbl_command.title()),
command=lambda fnm=filename, cmd=command: self.config.load(cmd, fnm))
self.recent_menu.add_separator()
self.recent_menu.add_command(
label="Clear recent files",
underline=0,
command=lambda srl=serializer, mnu=menu_file: self.clear_recent_files(srl, mnu))
logger.debug("Built Recent Files menu")
@staticmethod
def clear_recent_files(serializer, menu_file):
""" Creates or clears recent file list """
logger.debug("clearing recent files list: '%s'", menu_file)
recent_files = serializer.marshal(list())
with open(menu_file, "wb") as out:
out.write(recent_files.encode("utf-8"))
def refresh_recent_menu(self):
""" Refresh recent menu on save/load of files """
self.recent_menu.delete(0, "end")
self.build_recent_menu()
def build_edit_menu(self):
""" Add the edit menu to the menu bar """
logger.debug("Building Edit menu")
edit_menu = tk.Menu(self, tearoff=0)
configs = self.scan_for_configs()
for name in sorted(list(configs.keys())):
label = "Configure {} Plugins...".format(name.title())
config = configs[name]
edit_menu.add_command(
label=label,
underline=10,
command=lambda conf=(name, config), root=self.root: popup_config(conf, root))
self.add_cascade(label="Edit", menu=edit_menu, underline=0)
logger.debug("Built Edit menu")
def scan_for_configs(self):
""" Scan for config.ini file locations """
root_path = os.path.abspath(os.path.dirname(sys.argv[0]))
plugins_path = os.path.join(root_path, "plugins")
logger.debug("Scanning path: '%s'", plugins_path)
configs = dict()
for dirpath, _, filenames in os.walk(plugins_path):
if "_config.py" in filenames:
plugin_type = os.path.split(dirpath)[-1]
config = self.load_config(plugin_type)
configs[plugin_type] = config
logger.debug("Configs loaded: %s", sorted(list(configs.keys())))
return configs
@staticmethod
def load_config(plugin_type):
""" Load the config to generate config file if it doesn't exist and get filename """
# Load config to generate default if doesn't exist
mod = ".".join(("plugins", plugin_type, "_config"))
module = import_module(mod)
config = module.Config(None)
logger.debug("Found '%s' config at '%s'", plugin_type, config.configfile)
return config