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
177 lines
5.8 KiB
Python
177 lines
5.8 KiB
Python
#!/usr/bin/python
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""" Logging Setup """
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import collections
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import logging
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from logging.handlers import QueueHandler, QueueListener, RotatingFileHandler
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import os
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import re
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import sys
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import traceback
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from datetime import datetime
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from time import sleep
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from lib.queue_manager import queue_manager
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from lib.sysinfo import sysinfo
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LOG_QUEUE = queue_manager._log_queue # pylint: disable=protected-access
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class MultiProcessingLogger(logging.Logger):
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""" Create custom logger with custom levels """
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def __init__(self, name):
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for new_level in (("VERBOSE", 15), ("TRACE", 5)):
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level_name, level_num = new_level
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if hasattr(logging, level_name):
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continue
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logging.addLevelName(level_num, level_name)
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setattr(logging, level_name, level_num)
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super().__init__(name)
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def verbose(self, msg, *args, **kwargs):
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"""
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Log 'msg % args' with severity 'VERBOSE'.
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"""
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if self.isEnabledFor(15):
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self._log(15, msg, args, **kwargs)
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def trace(self, msg, *args, **kwargs):
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"""
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Log 'msg % args' with severity 'VERBOSE'.
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"""
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if self.isEnabledFor(5):
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self._log(5, msg, args, **kwargs)
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class FaceswapFormatter(logging.Formatter):
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""" Override formatter to strip newlines and multiple spaces from logger
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Messages that begin with "R|" should be handled as is
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"""
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def format(self, record):
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if record.msg.startswith("R|"):
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record.msg = record.msg[2:]
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record.strip_spaces = False
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elif record.strip_spaces:
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record.msg = re.sub(" +", " ", record.msg.replace("\n", "\\n").replace("\r", "\\r"))
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return super().format(record)
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class RollingBuffer(collections.deque):
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"""File-like that keeps a certain number of lines of text in memory."""
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def write(self, buffer):
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""" Write line to buffer """
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for line in buffer.rstrip().splitlines():
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self.append(line + "\n")
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def set_root_logger(loglevel=logging.INFO, queue=LOG_QUEUE):
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""" Setup the root logger.
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Loaded in main process and into any spawned processes
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Automatically added in multithreading.py"""
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rootlogger = logging.getLogger()
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q_handler = QueueHandler(queue)
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rootlogger.addHandler(q_handler)
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rootlogger.setLevel(loglevel)
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def log_setup(loglevel, logfile, command):
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""" initial log set up. """
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numeric_loglevel = get_loglevel(loglevel)
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root_loglevel = min(logging.DEBUG, numeric_loglevel)
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set_root_logger(loglevel=root_loglevel)
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log_format = FaceswapFormatter("%(asctime)s %(processName)-15s %(threadName)-15s "
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"%(module)-15s %(funcName)-25s %(levelname)-8s %(message)s",
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datefmt="%m/%d/%Y %H:%M:%S")
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f_handler = file_handler(numeric_loglevel, logfile, log_format, command)
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s_handler = stream_handler(numeric_loglevel)
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c_handler = crash_handler(log_format)
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q_listener = QueueListener(LOG_QUEUE, f_handler, s_handler, c_handler,
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respect_handler_level=True)
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q_listener.start()
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logging.info("Log level set to: %s", loglevel.upper())
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def file_handler(loglevel, logfile, log_format, command):
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""" Add a logging rotating file handler """
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if logfile is not None:
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filename = logfile
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else:
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filename = os.path.join(os.path.dirname(os.path.realpath(sys.argv[0])), "faceswap")
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# Windows has issues sharing the log file with subprocesses, so log GUI separately
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filename += "_gui.log" if command == "gui" else ".log"
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should_rotate = os.path.isfile(filename)
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log_file = RotatingFileHandler(filename, backupCount=1)
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if should_rotate:
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log_file.doRollover()
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log_file.setFormatter(log_format)
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log_file.setLevel(loglevel)
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return log_file
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def stream_handler(loglevel):
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""" Add a logging cli handler """
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# Don't set stdout to lower than verbose
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loglevel = max(loglevel, 15)
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log_format = FaceswapFormatter("%(asctime)s %(levelname)-8s %(message)s",
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datefmt="%m/%d/%Y %H:%M:%S")
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log_console = logging.StreamHandler(sys.stdout)
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log_console.setFormatter(log_format)
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log_console.setLevel(loglevel)
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return log_console
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def crash_handler(log_format):
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""" Add a handler that sores the last 50 debug lines to `debug_buffer`
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for use in crash reports """
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log_crash = logging.StreamHandler(debug_buffer)
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log_crash.setFormatter(log_format)
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log_crash.setLevel(logging.DEBUG)
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return log_crash
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def get_loglevel(loglevel):
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""" Check valid log level supplied and return numeric log level """
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numeric_level = getattr(logging, loglevel.upper(), None)
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if not isinstance(numeric_level, int):
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raise ValueError("Invalid log level: %s" % loglevel)
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return numeric_level
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def crash_log():
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""" Write debug_buffer to a crash log on crash """
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path = os.getcwd()
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filename = os.path.join(path, datetime.now().strftime("crash_report.%Y.%m.%d.%H%M%S%f.log"))
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# Wait until all log items have been processed
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while not LOG_QUEUE.empty():
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sleep(1)
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freeze_log = list(debug_buffer)
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with open(filename, "w") as outfile:
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outfile.writelines(freeze_log)
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traceback.print_exc(file=outfile)
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outfile.write(sysinfo.full_info())
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return filename
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# Add a flag to logging.LogRecord to not strip formatting from particular records
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old_factory = logging.getLogRecordFactory()
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def faceswap_logrecord(*args, **kwargs):
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record = old_factory(*args, **kwargs)
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record.strip_spaces = True
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return record
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logging.setLogRecordFactory(faceswap_logrecord)
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# Set logger class to custom logger
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logging.setLoggerClass(MultiProcessingLogger)
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# Stores the last 50 debug messages
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debug_buffer = RollingBuffer(maxlen=50) # pylint: disable=invalid-name
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