mirror of
https://github.com/deepfakes/faceswap
synced 2025-06-07 10:43:27 -04:00
* 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
105 lines
4 KiB
Python
105 lines
4 KiB
Python
#!/usr/bin/env python3
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""" Queue Manager for faceswap
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NB: Keep this in it's own module! If it gets loaded from
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a multiprocess on a Windows System it will break Faceswap"""
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import logging
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import multiprocessing as mp
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import sys
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import threading
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from queue import Queue, Empty as QueueEmpty # pylint: disable=unused-import; # noqa
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from time import sleep
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logger = logging.getLogger(__name__) # pylint: disable=invalid-name
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class QueueManager():
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""" Manage queues for availabilty across processes
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Don't import this class directly, instead
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import the variable: queue_manager """
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def __init__(self):
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logger.debug("Initializing %s", self.__class__.__name__)
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# Hacky fix to stop multiprocessing spawning managers in child processes
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if mp.current_process().name == "MainProcess":
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# Use a Multiprocessing manager in main process
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self.manager = mp.Manager()
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else:
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# Use a standard mp.queue in child process. NB: This will never be used
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# but spawned processes will load this module, so we need to dummy in a queue
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self.manager = mp
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self.shutdown = self.manager.Event()
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self.queues = dict()
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# Despite launching a subprocess, the scripts still want to access the same logging
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# queue as the GUI, so make sure the GUI gets it's own queue
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self._log_queue = self.manager.Queue() if "gui" not in sys.argv else mp.Queue()
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logger.debug("Initialized %s", self.__class__.__name__)
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def add_queue(self, name, maxsize=0, multiprocessing_queue=True):
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""" Add a queue to the manager
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Adds an event "shutdown" to the queue that can be used to indicate
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to a process that any activity on the queue should cease """
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logger.debug("QueueManager adding: (name: '%s', maxsize: %s)", name, maxsize)
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if name in self.queues.keys():
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raise ValueError("Queue '{}' already exists.".format(name))
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if multiprocessing_queue:
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queue = self.manager.Queue(maxsize=maxsize)
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else:
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queue = Queue(maxsize=maxsize)
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setattr(queue, "shutdown", self.shutdown)
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self.queues[name] = queue
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logger.debug("QueueManager added: (name: '%s')", name)
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def del_queue(self, name):
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""" remove a queue from the manager """
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logger.debug("QueueManager deleting: '%s'", name)
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del self.queues[name]
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logger.debug("QueueManager deleted: '%s'", name)
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def get_queue(self, name, maxsize=0):
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""" Return a queue from the manager
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If it doesn't exist, create it """
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logger.debug("QueueManager getting: '%s'", name)
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queue = self.queues.get(name, None)
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if not queue:
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self.add_queue(name, maxsize)
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queue = self.queues[name]
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logger.debug("QueueManager got: '%s'", name)
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return queue
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def terminate_queues(self):
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""" Set shutdown event, clear and send EOF to all queues
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To be called if there is an error """
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logger.debug("QueueManager terminating all queues")
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self.shutdown.set()
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for q_name, queue in self.queues.items():
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logger.debug("QueueManager terminating: '%s'", q_name)
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while not queue.empty():
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queue.get(True, 1)
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queue.put("EOF")
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logger.debug("QueueManager terminated all queues")
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def debug_monitor(self, update_secs=2):
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""" Debug tool for monitoring queues """
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thread = threading.Thread(target=self.debug_queue_sizes,
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args=(update_secs, ))
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thread.daemon = True
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thread.start()
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def debug_queue_sizes(self, update_secs):
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""" Output the queue sizes
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logged to INFO so it also displays in console
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"""
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while True:
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for name in sorted(self.queues.keys()):
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logger.info("%s: %s", name, self.queues[name].qsize())
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sleep(update_secs)
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queue_manager = QueueManager() # pylint: disable=invalid-name
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