StoJo preset is crashing
Posted: Tue Nov 01, 2022 9:48 pm
For some reason i cant even start the training with the StoJo preset. It simply crashes.
Code: Select all
11/02/2022 03:03:33 MainProcess _training config _load_defaults_from_module DEBUG Importing defaults module: plugins.train.trainer.original_defaults
11/02/2022 03:03:33 MainProcess _training config add_section DEBUG Add section: (title: 'trainer.original', info: 'Original Trainer Options.\nWARNING: The defaults for augmentation will be fine for 99.9% of use cases. Only change them if you absolutely know what you are doing!')
11/02/2022 03:03:33 MainProcess _training config add_item DEBUG Add item: (section: 'trainer.original', title: 'preview_images', datatype: '<class 'int'>', default: '14', info: 'Number of sample faces to display for each side in the preview when training.', rounding: '2', min_max: (2, 16), choices: None, gui_radio: False, fixed: True, group: evaluation)
11/02/2022 03:03:33 MainProcess _training config add_item DEBUG Add item: (section: 'trainer.original', title: 'zoom_amount', datatype: '<class 'int'>', default: '5', info: 'Percentage amount to randomly zoom each training image in and out.', rounding: '1', min_max: (0, 25), choices: None, gui_radio: False, fixed: True, group: image augmentation)
11/02/2022 03:03:33 MainProcess _training config add_item DEBUG Add item: (section: 'trainer.original', title: 'rotation_range', datatype: '<class 'int'>', default: '10', info: 'Percentage amount to randomly rotate each training image.', rounding: '1', min_max: (0, 25), choices: None, gui_radio: False, fixed: True, group: image augmentation)
11/02/2022 03:03:33 MainProcess _training config add_item DEBUG Add item: (section: 'trainer.original', title: 'shift_range', datatype: '<class 'int'>', default: '5', info: 'Percentage amount to randomly shift each training image horizontally and vertically.', rounding: '1', min_max: (0, 25), choices: None, gui_radio: False, fixed: True, group: image augmentation)
11/02/2022 03:03:33 MainProcess _training config add_item DEBUG Add item: (section: 'trainer.original', title: 'flip_chance', datatype: '<class 'int'>', default: '50', info: 'Percentage chance to randomly flip each training image horizontally.\nNB: This is ignored if the 'no-flip' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: True, group: image augmentation)
11/02/2022 03:03:33 MainProcess _training config add_item DEBUG Add item: (section: 'trainer.original', title: 'color_lightness', datatype: '<class 'int'>', default: '30', info: 'Percentage amount to randomly alter the lightness of each training image.\nNB: This is ignored if the 'no-augment-color' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: True, group: color augmentation)
11/02/2022 03:03:33 MainProcess _training config add_item DEBUG Add item: (section: 'trainer.original', title: 'color_ab', datatype: '<class 'int'>', default: '8', info: 'Percentage amount to randomly alter the 'a' and 'b' colors of the L*a*b* color space of each training image.\nNB: This is ignored if the 'no-augment-color' optionis enabled', rounding: '1', min_max: (0, 50), choices: None, gui_radio: False, fixed: True, group: color augmentation)
11/02/2022 03:03:33 MainProcess _training config add_item DEBUG Add item: (section: 'trainer.original', title: 'color_clahe_chance', datatype: '<class 'int'>', default: '50', info: 'Percentage chance to perform Contrast Limited Adaptive Histogram Equalization on each training image.\nNB: This is ignored if the 'no-augment-color' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: False, group: color augmentation)
11/02/2022 03:03:33 MainProcess _training config add_item DEBUG Add item: (section: 'trainer.original', title: 'color_clahe_max_size', datatype: '<class 'int'>', default: '4', info: 'The grid size dictates how much Contrast Limited Adaptive Histogram Equalization is performed on any training image selected for clahe. Contrast will be applied randomly with a gridsize of 0 up to the maximum. This value is a multiplier calculated from the training image size.\nNB: This is ignored if the 'no-augment-color' option is enabled', rounding: '1', min_max: (1, 8), choices: None, gui_radio: False, fixed: True, group: color augmentation)
11/02/2022 03:03:33 MainProcess _training config _load_defaults_from_module DEBUG Added defaults: trainer.original
11/02/2022 03:03:33 MainProcess _training config handle_config DEBUG Handling config: (section: model.phaze_a, configfile: 'G:\faceswap\config\train.ini')
11/02/2022 03:03:33 MainProcess _training config check_exists DEBUG Config file exists: 'G:\faceswap\config\train.ini'
11/02/2022 03:03:33 MainProcess _training config load_config VERBOSE Loading config: 'G:\faceswap\config\train.ini'
11/02/2022 03:03:33 MainProcess _training config validate_config DEBUG Validating config
11/02/2022 03:03:33 MainProcess _training config check_config_change DEBUG Default config has not changed
11/02/2022 03:03:33 MainProcess _training config check_config_choices DEBUG Checking config choices
11/02/2022 03:03:33 MainProcess _training config _parse_list DEBUG Processed raw option 'keras_encoder' to list ['keras_encoder'] for section 'model.phaze_a', option 'freeze_layers'
11/02/2022 03:03:33 MainProcess _training config _parse_list DEBUG Processed raw option 'encoder' to list ['encoder'] for section 'model.phaze_a', option 'load_layers'
11/02/2022 03:03:33 MainProcess _training config check_config_choices DEBUG Checked config choices
11/02/2022 03:03:33 MainProcess _training config validate_config DEBUG Validated config
11/02/2022 03:03:33 MainProcess _training config handle_config DEBUG Handled config
11/02/2022 03:03:33 MainProcess _training config __init__ DEBUG Initialized: Config
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global', option: 'learning_rate')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'float'>, value: 5e-05)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global', option: 'epsilon_exponent')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'int'>, value: -16)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global', option: 'autoclip')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'bool'>, value: False)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global', option: 'allow_growth')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'bool'>, value: False)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global', option: 'mixed_precision')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'bool'>, value: True)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global', option: 'nan_protection')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'bool'>, value: True)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global', option: 'convert_batchsize')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'int'>, value: 16)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'loss_function')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'str'>, value: ms_ssim)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'loss_function_2')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'str'>, value: mae)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'loss_weight_2')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'int'>, value: 25)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'loss_function_3')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'str'>, value: ffl)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'loss_weight_3')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'int'>, value: 100)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'loss_function_4')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'str'>, value: None)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'loss_weight_4')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'int'>, value: 0)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'mask_loss_function')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'str'>, value: mae)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'eye_multiplier')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'int'>, value: 3)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'global.loss', option: 'mouth_multiplier')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'int'>, value: 2)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'model.phaze_a', option: 'fc_dropout')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'float'>, value: 0.0)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'model.phaze_a', option: 'fc_gblock_dropout')
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'float'>, value: 0.0)
11/02/2022 03:03:33 MainProcess _training config get DEBUG Getting config item: (section: 'model.phaze_a', option: 'freeze_layers')
11/02/2022 03:03:33 MainProcess _training config _parse_list DEBUG Processed raw option 'keras_encoder' to list ['keras_encoder'] for section 'model.phaze_a', option 'freeze_layers'
11/02/2022 03:03:33 MainProcess _training config get DEBUG Returning item: (type: <class 'list'>, value: ['keras_encoder'])
11/02/2022 03:03:33 MainProcess _training config changeable_items DEBUG Alterable for existing models: {'learning_rate': 5e-05, 'epsilon_exponent': -16, 'autoclip': False, 'allow_growth': False, 'mixed_precision': True, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'ms_ssim', 'loss_function_2': 'mae', 'loss_weight_2': 25, 'loss_function_3': 'ffl', 'loss_weight_3': 100, 'loss_function_4': None, 'loss_weight_4': 0, 'mask_loss_function': 'mae', 'eye_multiplier': 3, 'mouth_multiplier': 2, 'fc_dropout': 0.0, 'fc_gblock_dropout': 0.0, 'freeze_layers': ['keras_encoder']}
11/02/2022 03:03:33 MainProcess _training model __init__ DEBUG Initializing State: (model_dir: 'F:\Pinscreen_Data\HERE_Training_Data\FaceSwap_Avi_stojo', model_name: 'phaze_a', config_changeable_items: '{'learning_rate': 5e-05, 'epsilon_exponent': -16, 'autoclip': False, 'allow_growth': False, 'mixed_precision': True, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'ms_ssim', 'loss_function_2': 'mae', 'loss_weight_2': 25, 'loss_function_3': 'ffl', 'loss_weight_3': 100, 'loss_function_4': None, 'loss_weight_4': 0, 'mask_loss_function': 'mae', 'eye_multiplier': 3, 'mouth_multiplier': 2, 'fc_dropout': 0.0, 'fc_gblock_dropout': 0.0, 'freeze_layers': ['keras_encoder']}', no_logs: False
11/02/2022 03:03:33 MainProcess _training serializer get_serializer DEBUG <lib.serializer._JSONSerializer object at 0x000001FF0CE13760>
11/02/2022 03:03:33 MainProcess _training model _load DEBUG Loading State
11/02/2022 03:03:33 MainProcess _training model _load INFO No existing state file found. Generating.
11/02/2022 03:03:33 MainProcess _training model _new_session_id DEBUG 1
11/02/2022 03:03:33 MainProcess _training model _create_new_session DEBUG Creating new session. id: 1
11/02/2022 03:03:33 MainProcess _training model __init__ DEBUG Initialized State:
11/02/2022 03:03:33 MainProcess _training settings __init__ DEBUG Initializing Settings: (arguments: Namespace(func=<bound method ScriptExecutor.execute_script of <lib.cli.launcher.ScriptExecutor object at 0x000001FF7F8E8970>>, exclude_gpus=None, configfile=None, loglevel='INFO', logfile=None, redirect_gui=True, colab=False, input_a='F:\\Pinscreen_Data\\HERE_Training_Data\\A_256', input_b='F:\\Pinscreen_Data\\HERE_Training_Data\\B_256', model_dir='F:\\Pinscreen_Data\\HERE_Training_Data\\FaceSwap_Avi_stojo', load_weights=None, trainer='phaze-a', summary=False, freeze_weights=False, batch_size=8, iterations=1000000, distributed=False, distribution_strategy='default', save_interval=250, snapshot_interval=25000, timelapse_input_a=None, timelapse_input_b=None, timelapse_output=None, preview=False, write_image=False, no_logs=False, warp_to_landmarks=False, no_flip=False, no_augment_color=False, no_warp=False), mixed_precision: True, allow_growth: False, is_predict: False)
11/02/2022 03:03:33 MainProcess _training settings _set_tf_settings DEBUG Not setting any specific Tensorflow settings
11/02/2022 03:03:33 MainProcess _training settings _set_keras_mixed_precision DEBUG use_mixed_precision: True
11/02/2022 03:03:33 MainProcess _training device_compatibility_check _log_device_compatibility_check INFO Mixed precision compatibility check (mixed_float16): OK\nYour GPUs will likely run quickly with dtype policy mixed_float16 as they all have compute capability of at least 7.0
11/02/2022 03:03:33 MainProcess _training settings _set_keras_mixed_precision DEBUG Enabled mixed precision. (Compute dtype: float16, variable_dtype: float32)
11/02/2022 03:03:33 MainProcess _training settings __init__ INFO Enabling Mixed Precision Training.
11/02/2022 03:03:33 MainProcess _training settings _get_strategy DEBUG Using strategy: <tensorflow.python.distribute.distribute_lib._DefaultDistributionStrategy object at 0x000001FF0DDB2520>
11/02/2022 03:03:33 MainProcess _training settings __init__ DEBUG Initialized Settings
11/02/2022 03:03:33 MainProcess _training settings __init__ DEBUG Initializing Loss: (color_order: bgr)
11/02/2022 03:03:33 MainProcess _training settings _get_mask_channels DEBUG uses_masks: (True, True, True), mask_channels: [3, 4, 5]
11/02/2022 03:03:33 MainProcess _training settings __init__ DEBUG Initialized: Loss
11/02/2022 03:03:33 MainProcess _training model __init__ DEBUG Initialized ModelBase (Model)
11/02/2022 03:03:33 MainProcess _training phaze_a _select_freeze_layers DEBUG Substituting 'keras_encoder' for 'efficientnet_b4'
11/02/2022 03:03:33 MainProcess _training phaze_a _get_input_shape DEBUG Encoder input set to: (224, 224, 3)
11/02/2022 03:03:33 MainProcess _training phaze_a build DEBUG New model, inference or summary. Falling back to default build: (exists: False, inference: False, is_summary: False)
11/02/2022 03:03:33 MainProcess _training settings strategy_scope DEBUG Using strategy scope: <tensorflow.python.distribute.distribute_lib._DefaultDistributionContext object at 0x000001FF0CC258C0>
11/02/2022 03:03:33 MainProcess _training model _get_inputs DEBUG Getting inputs
11/02/2022 03:03:33 MainProcess _training model _get_inputs DEBUG inputs: [<KerasTensor: shape=(None, 224, 224, 3) dtype=float32 (created by layer 'face_in_a')>, <KerasTensor: shape=(None, 224, 224, 3) dtype=float32 (created by layer 'face_in_b')>]
11/02/2022 03:03:33 MainProcess _training phaze_a __call__ DEBUG Scaling to (0, 255) for 'efficientnet_b4'
11/02/2022 03:03:34 MainProcess _training multithreading run DEBUG Error in thread (_training): Exception encountered when calling layer "tf.math.truediv" (type TFOpLambda).\n\n`x` and `y` must have the same dtype, got tf.float16 != tf.float32.\n\nCall arguments received by layer "tf.math.truediv" (type TFOpLambda):\n • x=tf.Tensor(shape=(None, 224, 224, 3), dtype=float16)\n • y=tf.Tensor(shape=(3,), dtype=float32)\n • name=None
11/02/2022 03:03:35 MainProcess MainThread train _monitor DEBUG Thread error detected
11/02/2022 03:03:35 MainProcess MainThread train _monitor DEBUG Closed Monitor
11/02/2022 03:03:35 MainProcess MainThread train _end_thread DEBUG Ending Training thread
11/02/2022 03:03:35 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting...
11/02/2022 03:03:35 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training'
11/02/2022 03:03:35 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training'
11/02/2022 03:03:35 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training'
Traceback (most recent call last):
File "G:\faceswap\lib\cli\launcher.py", line 217, in execute_script
process.process()
File "G:\faceswap\scripts\train.py", line 218, in process
self._end_thread(thread, err)
File "G:\faceswap\scripts\train.py", line 258, in _end_thread
thread.join()
File "G:\faceswap\lib\multithreading.py", line 217, in join
raise thread.err[1].with_traceback(thread.err[2])
File "G:\faceswap\lib\multithreading.py", line 96, in run
self._target(*self._args, **self._kwargs)
File "G:\faceswap\scripts\train.py", line 280, in _training
raise err
File "G:\faceswap\scripts\train.py", line 268, in _training
model = self._load_model()
File "G:\faceswap\scripts\train.py", line 296, in _load_model
model.build()
File "G:\faceswap\plugins\train\model\phaze_a.py", line 201, in build
super().build()
File "G:\faceswap\plugins\train\model\_base\model.py", line 315, in build
self._model = self.build_model(inputs)
File "G:\faceswap\plugins\train\model\phaze_a.py", line 358, in build_model
encoders = self._build_encoders(inputs)
File "G:\faceswap\plugins\train\model\phaze_a.py", line 382, in _build_encoders
encoder = Encoder(self.input_shape, self.config)()
File "G:\faceswap\plugins\train\model\phaze_a.py", line 737, in __call__
var_x = self._get_encoder_model()(var_x)
File "G:\faceswap\plugins\train\model\phaze_a.py", line 760, in _get_encoder_model
retval = getattr(kapp, model.keras_name)(**kwargs)
File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\keras\applications\efficientnet.py", line 652, in EfficientNetB4
return EfficientNet(
File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\keras\applications\efficientnet.py", line 334, in EfficientNet
x = x / tf.math.sqrt(IMAGENET_STDDEV_RGB)
File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\util\traceback_utils.py", line 153, in error_handler
raise e.with_traceback(filtered_tb) from None
File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\keras\layers\core\tf_op_layer.py", line 107, in handle
return TFOpLambda(op)(*args, **kwargs)
File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 67, in error_handler
raise e.with_traceback(filtered_tb) from None
TypeError: Exception encountered when calling layer "tf.math.truediv" (type TFOpLambda).
`x` and `y` must have the same dtype, got tf.float16 != tf.float32.
Call arguments received by layer "tf.math.truediv" (type TFOpLambda):
• x=tf.Tensor(shape=(None, 224, 224, 3), dtype=float16)
• y=tf.Tensor(shape=(3,), dtype=float32)
• name=None
============ System Information ============
encoding: cp1252
git_branch: master
git_commits: d1a7f7a bugfix: Don't error if preview unsuccessfully read
gpu_cuda: No global version found. Check Conda packages for Conda Cuda
gpu_cudnn: No global version found. Check Conda packages for Conda cuDNN
gpu_devices: GPU_0: NVIDIA GeForce RTX 3090, GPU_1: NVIDIA GeForce RTX 3090
gpu_devices_active: GPU_0, GPU_1
gpu_driver: 522.30
gpu_vram: GPU_0: 24576MB, GPU_1: 24576MB
os_machine: AMD64
os_platform: Windows-10-10.0.22621-SP0
os_release: 10
py_command: G:\faceswap\faceswap.py train -A F:/Pinscreen_Data/HERE_Training_Data/A_256 -B F:/Pinscreen_Data/HERE_Training_Data/B_256 -m F:/Pinscreen_Data/HERE_Training_Data/FaceSwap_Avi_stojo -t phaze-a -bs 8 -it 1000000 -D default -s 250 -ss 25000 -L INFO -gui
py_conda_version: conda 22.9.0
py_implementation: CPython
py_version: 3.9.13
py_virtual_env: True
sys_cores: 32
sys_processor: AMD64 Family 25 Model 33 Stepping 0, AuthenticAMD
sys_ram: Total: 130993MB, Available: 107001MB, Used: 23992MB, Free: 107001MB
=============== Pip Packages ===============
absl-py @ file:///C:/b/abs_5babsu7y5x/croot/absl-py_1666362945682/work
astunparse==1.6.3
cachetools==5.2.0
certifi==2022.9.24
charset-normalizer==2.1.1
cloudpickle @ file:///tmp/build/80754af9/cloudpickle_1632508026186/work
colorama @ file:///C:/Windows/TEMP/abs_9439aeb1-0254-449a-96f7-33ab5eb17fc8apleb4yn/croots/recipe/colorama_1657009099097/work
cycler @ file:///tmp/build/80754af9/cycler_1637851556182/work
decorator @ file:///opt/conda/conda-bld/decorator_1643638310831/work
dm-tree==0.1.5
fastcluster @ file:///D:/bld/fastcluster_1649783471014/work
ffmpy==0.3.0
flatbuffers==1.12
fonttools==4.25.0
gast==0.4.0
google-auth==2.13.0
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.50.0
h5py==3.7.0
idna==3.4
imageio @ file:///C:/Windows/TEMP/abs_24c1b783-7540-4ca9-a1b1-0e8aa8e6ae64hb79ssux/croots/recipe/imageio_1658785038775/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1649960641006/work
importlib-metadata==5.0.0
joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1663332044897/work
keras==2.9.0
Keras-Preprocessing==1.1.2
kiwisolver @ file:///C:/ci/kiwisolver_1653292407425/work
libclang==14.0.6
Markdown==3.4.1
MarkupSafe==2.1.1
matplotlib @ file:///C:/ci/matplotlib-suite_1660169687702/work
mkl-fft==1.3.1
mkl-random @ file:///C:/ci/mkl_random_1626186184308/work
mkl-service==2.4.0
munkres==1.1.4
numexpr @ file:///C:/Windows/Temp/abs_e2036a32-9fe9-47f3-a04c-dbb1c232ba4b334exiur/croots/recipe/numexpr_1656940304835/work
numpy @ file:///C:/b/abs_53f_dbvhzc/croot/numpy_and_numpy_base_1665773185489/work
nvidia-ml-py==11.515.75
oauthlib==3.2.2
opencv-python==4.6.0.66
opt-einsum==3.3.0
packaging @ file:///tmp/build/80754af9/packaging_1637314298585/work
Pillow==9.2.0
ply==3.11
protobuf==3.19.6
psutil @ file:///C:/Windows/Temp/abs_b2c2fd7f-9fd5-4756-95ea-8aed74d0039flsd9qufz/croots/recipe/psutil_1656431277748/work
pyasn1==0.4.8
pyasn1-modules==0.2.8
pyparsing @ file:///C:/Users/BUILDE~1/AppData/Local/Temp/abs_7f_7lba6rl/croots/recipe/pyparsing_1661452540662/work
PyQt5==5.15.7
PyQt5-sip @ file:///C:/Windows/Temp/abs_d7gmd2jg8i/croots/recipe/pyqt-split_1659273064801/work/pyqt_sip
python-dateutil @ file:///tmp/build/80754af9/python-dateutil_1626374649649/work
pywin32==302
pywinpty @ file:///C:/ci_310/pywinpty_1644230983541/work/target/wheels/pywinpty-2.0.2-cp39-none-win_amd64.whl
requests==2.28.1
requests-oauthlib==1.3.1
rsa==4.9
scikit-learn @ file:///D:/bld/scikit-learn_1652976858669/work
scipy @ file:///C:/bld/scipy_1658811088396/work
sip @ file:///C:/Windows/Temp/abs_b8fxd17m2u/croots/recipe/sip_1659012372737/work
six @ file:///tmp/build/80754af9/six_1644875935023/work
tensorboard==2.9.1
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow-estimator==2.9.0
tensorflow-gpu==2.9.2
tensorflow-io-gcs-filesystem==0.27.0
tensorflow-probability @ file:///tmp/build/80754af9/tensorflow-probability_1633017132682/work
termcolor==2.0.1
threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1643647933166/work
toml @ file:///tmp/build/80754af9/toml_1616166611790/work
tornado @ file:///C:/ci/tornado_1662458743919/work
tqdm @ file:///C:/b/abs_0axbz66qik/croots/recipe/tqdm_1664392691071/work
typing_extensions @ file:///C:/Windows/TEMP/abs_dd2d0moa85/croots/recipe/typing_extensions_1659638831135/work
urllib3==1.26.12
Werkzeug==2.2.2
wincertstore==0.2
wrapt==1.14.1
zipp==3.10.0
============== Conda Packages ==============
# packages in environment at C:\Users\avira\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
absl-py 1.3.0 py39haa95532_0
astunparse 1.6.3 pypi_0 pypi
blas 1.0 mkl
brotli 1.0.9 h2bbff1b_7
brotli-bin 1.0.9 h2bbff1b_7
ca-certificates 2022.9.24 h5b45459_0 conda-forge
cachetools 5.2.0 pypi_0 pypi
certifi 2022.9.24 pyhd8ed1ab_0 conda-forge
charset-normalizer 2.1.1 pypi_0 pypi
cloudpickle 2.0.0 pyhd3eb1b0_0
colorama 0.4.5 py39haa95532_0
cudatoolkit 11.2.2 h933977f_10 conda-forge
cudnn 8.1.0.77 h3e0f4f4_0 conda-forge
cycler 0.11.0 pyhd3eb1b0_0
decorator 5.1.1 pyhd3eb1b0_0
dm-tree 0.1.5 py39hf11a4ad_0
fastcluster 1.2.6 py39h2e25243_1 conda-forge
ffmpeg 4.3.1 ha925a31_0 conda-forge
ffmpy 0.3.0 pypi_0 pypi
flatbuffers 1.12 pypi_0 pypi
fonttools 4.25.0 pyhd3eb1b0_0
freetype 2.12.1 ha860e81_0
gast 0.4.0 pypi_0 pypi
git 2.34.1 haa95532_0
glib 2.69.1 h5dc1a3c_1
google-auth 2.13.0 pypi_0 pypi
google-auth-oauthlib 0.4.6 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.50.0 pypi_0 pypi
gst-plugins-base 1.18.5 h9e645db_0
gstreamer 1.18.5 hd78058f_0
h5py 3.7.0 pypi_0 pypi
icu 58.2 ha925a31_3
idna 3.4 pypi_0 pypi
imageio 2.19.3 py39haa95532_0
imageio-ffmpeg 0.4.7 pyhd8ed1ab_0 conda-forge
importlib-metadata 5.0.0 pypi_0 pypi
intel-openmp 2021.4.0 haa95532_3556
joblib 1.2.0 pyhd8ed1ab_0 conda-forge
jpeg 9e h2bbff1b_0
keras 2.9.0 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
kiwisolver 1.4.2 py39hd77b12b_0
lerc 3.0 hd77b12b_0
libblas 3.9.0 1_h8933c1f_netlib conda-forge
libbrotlicommon 1.0.9 h2bbff1b_7
libbrotlidec 1.0.9 h2bbff1b_7
libbrotlienc 1.0.9 h2bbff1b_7
libcblas 3.9.0 5_hd5c7e75_netlib conda-forge
libclang 14.0.6 pypi_0 pypi
libdeflate 1.8 h2bbff1b_5
libffi 3.4.2 hd77b12b_4
libiconv 1.16 h2bbff1b_2
liblapack 3.9.0 5_hd5c7e75_netlib conda-forge
libogg 1.3.5 h2bbff1b_1
libpng 1.6.37 h2a8f88b_0
libtiff 4.4.0 h8a3f274_0
libvorbis 1.3.7 he774522_0
libwebp 1.2.4 h2bbff1b_0
libwebp-base 1.2.4 h2bbff1b_0
libxml2 2.9.14 h0ad7f3c_0
libxslt 1.1.35 h2bbff1b_0
lz4-c 1.9.3 h2bbff1b_1
m2w64-gcc-libgfortran 5.3.0 6 conda-forge
m2w64-gcc-libs 5.3.0 7 conda-forge
m2w64-gcc-libs-core 5.3.0 7 conda-forge
m2w64-gmp 6.1.0 2 conda-forge
m2w64-libwinpthread-git 5.0.0.4634.697f757 2 conda-forge
markdown 3.4.1 pypi_0 pypi
markupsafe 2.1.1 pypi_0 pypi
matplotlib 3.5.2 py39haa95532_0
matplotlib-base 3.5.2 py39hd77b12b_0
mkl 2021.4.0 haa95532_640
mkl-service 2.4.0 py39h2bbff1b_0
mkl_fft 1.3.1 py39h277e83a_0
mkl_random 1.2.2 py39hf11a4ad_0
msys2-conda-epoch 20160418 1 conda-forge
munkres 1.1.4 py_0
numexpr 2.8.3 py39hb80d3ca_0
numpy 1.23.3 py39h3b20f71_0
numpy-base 1.23.3 py39h4da318b_0
nvidia-ml-py 11.515.75 pypi_0 pypi
oauthlib 3.2.2 pypi_0 pypi
opencv-python 4.6.0.66 pypi_0 pypi
openssl 1.1.1q h8ffe710_0 conda-forge
opt-einsum 3.3.0 pypi_0 pypi
packaging 21.3 pyhd3eb1b0_0
pcre 8.45 hd77b12b_0
pillow 9.2.0 py39hdc2b20a_1
pip 22.2.2 py39haa95532_0
ply 3.11 py39haa95532_0
protobuf 3.19.6 pypi_0 pypi
psutil 5.9.0 py39h2bbff1b_0
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pyparsing 3.0.9 py39haa95532_0
pyqt 5.15.7 py39hd77b12b_0
pyqt5-sip 12.11.0 py39hd77b12b_0
python 3.9.13 h6244533_2
python-dateutil 2.8.2 pyhd3eb1b0_0
python_abi 3.9 2_cp39 conda-forge
pywin32 302 py39h2bbff1b_2
pywinpty 2.0.2 py39h5da7b33_0
qt-main 5.15.2 he8e5bd7_7
qt-webengine 5.15.9 hb9a9bb5_4
qtwebkit 5.212 h3ad3cdb_4
requests 2.28.1 pypi_0 pypi
requests-oauthlib 1.3.1 pypi_0 pypi
rsa 4.9 pypi_0 pypi
scikit-learn 1.1.1 py39he931e04_0 conda-forge
scipy 1.8.1 py39h5567194_2 conda-forge
setuptools 63.4.1 py39haa95532_0
sip 6.6.2 py39hd77b12b_0
six 1.16.0 pyhd3eb1b0_1
sqlite 3.39.3 h2bbff1b_0
tensorboard 2.9.1 pypi_0 pypi
tensorboard-data-server 0.6.1 pypi_0 pypi
tensorboard-plugin-wit 1.8.1 pypi_0 pypi
tensorflow-estimator 2.9.0 pypi_0 pypi
tensorflow-gpu 2.9.2 pypi_0 pypi
tensorflow-io-gcs-filesystem 0.27.0 pypi_0 pypi
tensorflow-probability 0.14.0 pyhd3eb1b0_0
termcolor 2.0.1 pypi_0 pypi
threadpoolctl 3.1.0 pyh8a188c0_0 conda-forge
tk 8.6.12 h2bbff1b_0
toml 0.10.2 pyhd3eb1b0_0
tornado 6.2 py39h2bbff1b_0
tqdm 4.64.1 py39haa95532_0
typing-extensions 4.3.0 py39haa95532_0
typing_extensions 4.3.0 py39haa95532_0
tzdata 2022e h04d1e81_0
urllib3 1.26.12 pypi_0 pypi
vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 2.2.2 pypi_0 pypi
wheel 0.37.1 pyhd3eb1b0_0
wincertstore 0.2 py39haa95532_2
winpty 0.4.3 4
wrapt 1.14.1 pypi_0 pypi
xz 5.2.6 h8cc25b3_0
zipp 3.10.0 pypi_0 pypi
zlib 1.2.13 h8cc25b3_0
zstd 1.5.2 h19a0ad4_0
================= Configs ==================
--------- .faceswap ---------
backend: nvidia
--------- convert.ini ---------
[color.color_transfer]
clip: True
preserve_paper: True
[color.manual_balance]
colorspace: HSV
balance_1: 0.0
balance_2: 0.0
balance_3: 0.0
contrast: 0.0
brightness: 0.0
[color.match_hist]
threshold: 99.0
[mask.mask_blend]
type: normalized
kernel_size: 3
passes: 4
threshold: 4
erosion: 0.0
erosion_top: 0.0
erosion_bottom: 0.0
erosion_left: 0.0
erosion_right: 0.0
[scaling.sharpen]
method: none
amount: 150
radius: 0.3
threshold: 5.0
[writer.ffmpeg]
container: mp4
codec: libx264
crf: 23
preset: medium
tune: none
profile: auto
level: auto
skip_mux: False
[writer.gif]
fps: 25
loop: 0
palettesize: 256
subrectangles: False
[writer.opencv]
format: png
draw_transparent: False
separate_mask: False
jpg_quality: 75
png_compress_level: 3
[writer.pillow]
format: png
draw_transparent: False
separate_mask: False
optimize: False
gif_interlace: True
jpg_quality: 75
png_compress_level: 3
tif_compression: tiff_deflate
--------- extract.ini ---------
[global]
allow_growth: False
aligner_min_scale: 0.07
aligner_max_scale: 2.0
aligner_distance: 22.5
aligner_roll: 45.0
save_filtered: False
[align.fan]
batch-size: 12
[detect.cv2_dnn]
confidence: 50
[detect.mtcnn]
minsize: 20
scalefactor: 0.709
batch-size: 8
cpu: True
threshold_1: 0.6
threshold_2: 0.7
threshold_3: 0.7
[detect.s3fd]
confidence: 70
batch-size: 4
[mask.bisenet_fp]
batch-size: 8
cpu: False
weights: faceswap
include_ears: True
include_hair: False
include_glasses: True
[mask.custom]
batch-size: 8
centering: face
fill: False
[mask.unet_dfl]
batch-size: 8
[mask.vgg_clear]
batch-size: 6
[mask.vgg_obstructed]
batch-size: 2
[recognition.vgg_face2]
batch-size: 16
cpu: False
--------- train.ini ---------
[global]
centering: head
coverage: 100.0
icnr_init: False
conv_aware_init: False
optimizer: adabelief
learning_rate: 5e-05
epsilon_exponent: -16
autoclip: False
reflect_padding: False
allow_growth: False
mixed_precision: True
nan_protection: True
convert_batchsize: 16
[global.loss]
loss_function: ms_ssim
loss_function_2: mae
loss_weight_2: 25
loss_function_3: ffl
loss_weight_3: 100
loss_function_4: None
loss_weight_4: 0
mask_loss_function: mae
eye_multiplier: 3
mouth_multiplier: 2
penalized_mask_loss: True
mask_type: bisenet-fp_face
mask_blur_kernel: 3
mask_threshold: 4
learn_mask: False
[model.dfaker]
output_size: 128
[model.dfl_h128]
lowmem: False
[model.dfl_sae]
input_size: 128
architecture: df
autoencoder_dims: 0
encoder_dims: 42
decoder_dims: 21
multiscale_decoder: False
[model.dlight]
features: best
details: good
output_size: 256
[model.original]
lowmem: False
[model.phaze_a]
output_size: 256
shared_fc: none
enable_gblock: True
split_fc: True
split_gblock: False
split_decoders: False
enc_architecture: efficientnet_b4
enc_scaling: 60
enc_load_weights: True
bottleneck_type: dense
bottleneck_norm: none
bottleneck_size: 512
bottleneck_in_encoder: True
fc_depth: 1
fc_min_filters: 1280
fc_max_filters: 1280
fc_dimensions: 8
fc_filter_slope: -0.5
fc_dropout: 0.0
fc_upsampler: upsample2d
fc_upsamples: 1
fc_upsample_filters: 1280
fc_gblock_depth: 3
fc_gblock_min_nodes: 512
fc_gblock_max_nodes: 512
fc_gblock_filter_slope: -0.5
fc_gblock_dropout: 0.0
dec_upscale_method: resize_images
dec_upscales_in_fc: 0
dec_norm: none
dec_min_filters: 160
dec_max_filters: 640
dec_slope_mode: full
dec_filter_slope: -0.33
dec_res_blocks: 1
dec_output_kernel: 3
dec_gaussian: True
dec_skip_last_residual: False
freeze_layers: keras_encoder
load_layers: encoder
fs_original_depth: 4
fs_original_min_filters: 128
fs_original_max_filters: 1024
fs_original_use_alt: False
mobilenet_width: 1.0
mobilenet_depth: 1
mobilenet_dropout: 0.001
mobilenet_minimalistic: False
[model.realface]
input_size: 64
output_size: 128
dense_nodes: 1536
complexity_encoder: 128
complexity_decoder: 512
[model.unbalanced]
input_size: 128
lowmem: False
nodes: 1024
complexity_encoder: 128
complexity_decoder_a: 384
complexity_decoder_b: 512
[model.villain]
lowmem: False
[trainer.original]
preview_images: 4
zoom_amount: 5
rotation_range: 10
shift_range: 5
flip_chance: 50
color_lightness: 30
color_ab: 8
color_clahe_chance: 50
color_clahe_max_size: 4
--------- gui.ini ---------
[global]
fullscreen: False
tab: extract
options_panel_width: 30
console_panel_height: 20
icon_size: 14
font: default
font_size: 9
autosave_last_session: prompt
timeout: 120
auto_load_model_stats: True