Itried uninstall CUDA , and faceswap , and reinstall faceswap only , still not work . ![Crying or Very Sad :cry:](./images/smilies/icon_cry.gif)
Code: Select all
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Applying mask from channel 3
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6E4CC70>, weight: 3.0, mask_channel: 4)
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Applying mask from channel 4
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDD190>, weight: 2.0, mask_channel: 5)
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Applying mask from channel 5
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDD5B0>, weight: 1.0, mask_channel: 3)
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Applying mask from channel 3
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDD940>, weight: 3.0, mask_channel: 4)
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Applying mask from channel 4
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDDE20>, weight: 2.0, mask_channel: 5)
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Applying mask from channel 5
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDD9D0>, weight: 1.0, mask_channel: 3)
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Applying mask from channel 3
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DF25E0>, weight: 3.0, mask_channel: 4)
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Applying mask from channel 4
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DF2AC0>, weight: 2.0, mask_channel: 5)
09/18/2022 20:08:02 MainProcess _training api converted_call DEBUG Applying mask from channel 5
09/18/2022 20:08:18 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6E34BE0>, weight: 1.0, mask_channel: 3)
09/18/2022 20:08:18 MainProcess _training api converted_call DEBUG Applying mask from channel 3
09/18/2022 20:08:18 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6E4C040>, weight: 3.0, mask_channel: 4)
09/18/2022 20:08:18 MainProcess _training api converted_call DEBUG Applying mask from channel 4
09/18/2022 20:08:18 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6E4C4F0>, weight: 2.0, mask_channel: 5)
09/18/2022 20:08:18 MainProcess _training api converted_call DEBUG Applying mask from channel 5
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AA6272AF40>, weight: 1.0, mask_channel: 3)
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Applying mask from channel 3
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6E4CC70>, weight: 3.0, mask_channel: 4)
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Applying mask from channel 4
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDD190>, weight: 2.0, mask_channel: 5)
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Applying mask from channel 5
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDD5B0>, weight: 1.0, mask_channel: 3)
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Applying mask from channel 3
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDD940>, weight: 3.0, mask_channel: 4)
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Applying mask from channel 4
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDDE20>, weight: 2.0, mask_channel: 5)
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Applying mask from channel 5
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DDD9D0>, weight: 1.0, mask_channel: 3)
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Applying mask from channel 3
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DF25E0>, weight: 3.0, mask_channel: 4)
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Applying mask from channel 4
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001AFC6DF2AC0>, weight: 2.0, mask_channel: 5)
09/18/2022 20:08:19 MainProcess _training api converted_call DEBUG Applying mask from channel 5
09/18/2022 20:09:38 MainProcess _training _base output_timelapse DEBUG Ouputting time-lapse
09/18/2022 20:09:38 MainProcess _training _base _setup DEBUG Setting up time-lapse
09/18/2022 20:09:38 MainProcess _training _base _setup DEBUG Time-lapse output set to 'D:\Temp\TimeLine'
09/18/2022 20:09:38 MainProcess _training utils get_image_paths DEBUG Scanned Folder contains 8017 files
09/18/2022 20:09:38 MainProcess _training utils get_image_paths DEBUG Returning 8017 images
09/18/2022 20:09:38 MainProcess _training utils get_image_paths DEBUG Scanned Folder contains 7202 files
09/18/2022 20:09:38 MainProcess _training utils get_image_paths DEBUG Returning 7202 images
09/18/2022 20:09:38 MainProcess _training _base set_timelapse_feed DEBUG Setting time-lapse feed: (input_images: '{'a': ['C:\\Faceswap\\044A\\02485.png', 'C:\\Faceswap\\044A\\02486.png', 'C:\\Faceswap\\044A\\02487.png', 'C:\\Faceswap\\044A\\02488.png', 'C:\\Faceswap\\044A\\02489.png', 'C:\\Faceswap\\044A\\02490.png', 'C:\\Faceswap\\044A\\02491.png', 'C:\\Faceswap\\044A\\02492.png', 'C:\\Faceswap\\044A\\02493.png', 'C:\\Faceswap\\044A\\02494.png', 'C:\\Faceswap\\044A\\02495.png', 'C:\\Faceswap\\044A\\02496.png', 'C:\\Faceswap\\044A\\02497.png', 'C:\\Faceswap\\044A\\02498.png', 'C:\\Faceswap\\044A\\02499.png', 'C:\\Faceswap\\044A\\02500.png', 'C:\\Faceswap\\044A\\02501.png', 'C:\\Faceswap\\044A\\02502.png', 'C:\\Faceswap\\044A\\02503.png', 'C:\\Faceswap\\044A\\02504.png', 'C:\\Faceswap\\044A\\02505.png', 'C:\\Faceswap\\044A\\02506.png', 'C:\\Faceswap\\044A\\02507.png', 'C:\\Faceswap\\044A\\02508.png', 'C:\\Faceswap\\044A\\02509.png', 'C:\\Faceswap\\044A\\02510.png', 'C:\\Faceswap\\044A\\02511.png', 'C:\\Faceswap\\044A\\02512.png',...............................
09/18/2022 20:09:38 MainProcess _training _base set_timelapse_feed DEBUG Setting preview feed: (side: 'a', images: 8017)
09/18/2022 20:09:38 MainProcess _training _base _load_generator DEBUG Loading generator, side: a, is_display: True, batch_size: 14
09/18/2022 20:09:38 MainProcess _training generator __init__ DEBUG Initializing PreviewDataGenerator: (model: phaze_a, side: a, images: 8017 , batch_size: 14, config: {'centering': 'face', 'coverage': 87.5, 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'epsilon_exponent': -5, 'autoclip': False, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': True, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'mae', 'loss_function_2': 'mse', 'loss_weight_2': 100, 'loss_function_3': None, 'loss_weight_3': 0, 'loss_function_4': None, 'loss_weight_4': 0, 'mask_loss_function': 'mse', 'eye_multiplier': 3, 'mouth_multiplier': 2, 'penalized_mask_loss': True, 'mask_type': 'unet-dfl', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'preview_images': 14, '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})
09/18/2022 20:09:38 MainProcess _training generator _get_output_sizes DEBUG side: a, model output shapes: [(None, 256, 256, 3), (None, 256, 256, 3)], output sizes: [256]
09/18/2022 20:09:38 MainProcess _training cache __init__ DEBUG Initializing: RingBuffer (batch_size: 14, image_shape: (288, 288, 6), buffer_size: 2, dtype: uint8
09/18/2022 20:09:38 MainProcess _training cache __init__ DEBUG Initialized: RingBuffer
09/18/2022 20:09:38 MainProcess _training generator __init__ DEBUG Initialized PreviewDataGenerator
09/18/2022 20:09:38 MainProcess _training generator minibatch_ab DEBUG do_shuffle: False
09/18/2022 20:09:38 MainProcess _training multithreading __init__ DEBUG Initializing BackgroundGenerator: (target: '_run_3', thread_count: 1)
09/18/2022 20:09:38 MainProcess _training multithreading __init__ DEBUG Initialized BackgroundGenerator: '_run_3'
09/18/2022 20:09:38 MainProcess _training multithreading start DEBUG Starting thread(s): '_run_3'
09/18/2022 20:09:38 MainProcess _training multithreading start DEBUG Starting thread 1 of 1: '_run_3'
09/18/2022 20:09:38 MainProcess _run_3 generator _minibatch DEBUG Loading minibatch generator: (image_count: 8017, do_shuffle: False)
09/18/2022 20:09:38 MainProcess _training multithreading start DEBUG Started all threads '_run_3': 1
09/18/2022 20:09:38 MainProcess _training _base set_timelapse_feed DEBUG Setting preview feed: (side: 'b', images: 7202)
09/18/2022 20:09:38 MainProcess _training _base _load_generator DEBUG Loading generator, side: b, is_display: True, batch_size: 14
09/18/2022 20:09:38 MainProcess _training generator __init__ DEBUG Initializing PreviewDataGenerator: (model: phaze_a, side: b, images: 7202 , batch_size: 14, config: {'centering': 'face', 'coverage': 87.5, 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'epsilon_exponent': -5, 'autoclip': False, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': True, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'mae', 'loss_function_2': 'mse', 'loss_weight_2': 100, 'loss_function_3': None, 'loss_weight_3': 0, 'loss_function_4': None, 'loss_weight_4': 0, 'mask_loss_function': 'mse', 'eye_multiplier': 3, 'mouth_multiplier': 2, 'penalized_mask_loss': True, 'mask_type': 'unet-dfl', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'preview_images': 14, '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})
09/18/2022 20:09:38 MainProcess _training generator _get_output_sizes DEBUG side: b, model output shapes: [(None, 256, 256, 3), (None, 256, 256, 3)], output sizes: [256]
09/18/2022 20:09:38 MainProcess _training cache __init__ DEBUG Initializing: RingBuffer (batch_size: 14, image_shape: (288, 288, 6), buffer_size: 2, dtype: uint8
09/18/2022 20:09:38 MainProcess _training cache __init__ DEBUG Initialized: RingBuffer
09/18/2022 20:09:38 MainProcess _training generator __init__ DEBUG Initialized PreviewDataGenerator
09/18/2022 20:09:38 MainProcess _training generator minibatch_ab DEBUG do_shuffle: False
09/18/2022 20:09:38 MainProcess _training multithreading __init__ DEBUG Initializing BackgroundGenerator: (target: '_run_4', thread_count: 1)
09/18/2022 20:09:38 MainProcess _training multithreading __init__ DEBUG Initialized BackgroundGenerator: '_run_4'
09/18/2022 20:09:38 MainProcess _training multithreading start DEBUG Starting thread(s): '_run_4'
09/18/2022 20:09:38 MainProcess _training multithreading start DEBUG Starting thread 1 of 1: '_run_4'
09/18/2022 20:09:38 MainProcess _run_4 generator _minibatch DEBUG Loading minibatch generator: (image_count: 7202, do_shuffle: False)
09/18/2022 20:09:38 MainProcess _training multithreading start DEBUG Started all threads '_run_4': 1
09/18/2022 20:09:38 MainProcess _training _base set_timelapse_feed DEBUG Set time-lapse feed: {'a': <generator object BackgroundGenerator.iterator at 0x000001AA5C112510>, 'b': <generator object BackgroundGenerator.iterator at 0x000001AFCD119A50>}
09/18/2022 20:09:38 MainProcess _training _base _setup DEBUG Set up time-lapse
09/18/2022 20:09:38 MainProcess _training _base output_timelapse DEBUG Getting time-lapse samples
09/18/2022 20:09:38 MainProcess _training _base generate_preview DEBUG Generating preview (is_timelapse: True)
09/18/2022 20:09:38 MainProcess _training _base generate_preview DEBUG Generated samples: is_timelapse: True, images: {'feed': {'a': (14, 288, 288, 3), 'b': (14, 288, 288, 3)}, 'samples': {'a': (14, 292, 292, 3), 'b': (14, 292, 292, 3)}, 'sides': {'a': (14, 288, 288, 1), 'b': (14, 288, 288, 1)}}
09/18/2022 20:09:38 MainProcess _training _base compile_sample DEBUG Compiling samples: (side: 'a', samples: 14)
09/18/2022 20:09:38 MainProcess _training _base compile_sample DEBUG Compiling samples: (side: 'b', samples: 14)
09/18/2022 20:09:38 MainProcess _training _base compile_sample DEBUG Compiled Samples: {'a': [(14, 288, 288, 3), (14, 292, 292, 3), (14, 288, 288, 1)], 'b': [(14, 288, 288, 3), (14, 292, 292, 3), (14, 288, 288, 1)]}
09/18/2022 20:09:38 MainProcess _training _base output_timelapse DEBUG Got time-lapse samples: {'a': 3, 'b': 3}
09/18/2022 20:09:38 MainProcess _training _base show_sample DEBUG Showing sample
09/18/2022 20:09:38 MainProcess _training _base _get_predictions DEBUG Getting Predictions
09/18/2022 20:09:48 MainProcess _training _base _get_predictions DEBUG Returning predictions: {'a_a': (14, 256, 256, 3), 'b_b': (14, 256, 256, 3), 'a_b': (14, 256, 256, 3), 'b_a': (14, 256, 256, 3)}
09/18/2022 20:09:48 MainProcess _training _base _to_full_frame DEBUG side: 'a', number of sample arrays: 3, prediction.shapes: [(14, 256, 256, 3), (14, 256, 256, 3)])
09/18/2022 20:09:48 MainProcess _training _base _process_full DEBUG full_size: 292, prediction_size: 256, color: (0.0, 0.0, 1.0)
09/18/2022 20:09:48 MainProcess _training _base _process_full DEBUG Overlayed background. Shape: (14, 292, 292, 3)
09/18/2022 20:09:48 MainProcess _training multithreading run DEBUG Error in thread (_training): OpenCV(4.6.0) D:\a\opencv-python\opencv-python\opencv\modules\core\src\arithm.cpp:650: error: (-209:Sizes of input arguments do not match) The operation is neither 'array op array' (where arrays have the same size and the same number of channels), nor 'array op scalar', nor 'scalar op array' in function 'cv::arithm_op'\n
09/18/2022 20:09:48 MainProcess MainThread train _monitor DEBUG Thread error detected
09/18/2022 20:09:48 MainProcess MainThread train _monitor DEBUG Closed Monitor
09/18/2022 20:09:48 MainProcess MainThread train _end_thread DEBUG Ending Training thread
09/18/2022 20:09:48 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting...
09/18/2022 20:09:48 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training'
09/18/2022 20:09:48 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training'
09/18/2022 20:09:48 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training'
Traceback (most recent call last):
File "C:\Users\adama\faceswap\lib\cli\launcher.py", line 201, in execute_script
process.process()
File "C:\Users\adama\faceswap\scripts\train.py", line 217, in process
self._end_thread(thread, err)
File "C:\Users\adama\faceswap\scripts\train.py", line 257, in _end_thread
thread.join()
File "C:\Users\adama\faceswap\lib\multithreading.py", line 217, in join
raise thread.err[1].with_traceback(thread.err[2])
File "C:\Users\adama\faceswap\lib\multithreading.py", line 96, in run
self._target(*self._args, **self._kwargs)
File "C:\Users\adama\faceswap\scripts\train.py", line 279, in _training
raise err
File "C:\Users\adama\faceswap\scripts\train.py", line 269, in _training
self._run_training_cycle(model, trainer)
File "C:\Users\adama\faceswap\scripts\train.py", line 357, in _run_training_cycle
trainer.train_one_step(viewer, timelapse)
File "C:\Users\adama\faceswap\plugins\train\trainer\_base.py", line 246, in train_one_step
self._update_viewers(viewer, timelapse_kwargs)
File "C:\Users\adama\faceswap\plugins\train\trainer\_base.py", line 354, in _update_viewers
self._timelapse.output_timelapse(timelapse_kwargs)
File "C:\Users\adama\faceswap\plugins\train\trainer\_base.py", line 1074, in output_timelapse
image = self._samples.show_sample()
File "C:\Users\adama\faceswap\plugins\train\trainer\_base.py", line 647, in show_sample
return self._compile_preview(preds)
File "C:\Users\adama\faceswap\plugins\train\trainer\_base.py", line 743, in _compile_preview
display = self._to_full_frame(side, samples, preds)
File "C:\Users\adama\faceswap\plugins\train\trainer\_base.py", line 798, in _to_full_frame
images = self._compile_masked(images, samples[-1])
File "C:\Users\adama\faceswap\plugins\train\trainer\_base.py", line 884, in _compile_masked
retval = [np.array([cv2.addWeighted(img, 1.0, mask, 0.3, 0)
File "C:\Users\adama\faceswap\plugins\train\trainer\_base.py", line 884, in <listcomp>
retval = [np.array([cv2.addWeighted(img, 1.0, mask, 0.3, 0)
File "C:\Users\adama\faceswap\plugins\train\trainer\_base.py", line 884, in <listcomp>
retval = [np.array([cv2.addWeighted(img, 1.0, mask, 0.3, 0)
cv2.error: OpenCV(4.6.0) D:\a\opencv-python\opencv-python\opencv\modules\core\src\arithm.cpp:650: error: (-209:Sizes of input arguments do not match) The operation is neither 'array op array' (where arrays have the same size and the same number of channels), nor 'array op scalar', nor 'scalar op array' in function 'cv::arithm_op'
============ System Information ============
encoding: cp950
git_branch: master
git_commits: 2d312a9 Minor updates and fixups - Mask Tool - Typing + BiSeNet mask update fix - Alignments Tool - Auto search for alignments file
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_devices_active: GPU_0
gpu_driver: 516.94
gpu_vram: GPU_0: 24576MB
os_machine: AMD64
os_platform: Windows-10-10.0.19044-SP0
os_release: 10
py_command: C:\Users\adama\faceswap\faceswap.py train -A C:/Faceswap/044A -B C:/Faceswap/Face Li Finall -2 -m D:/Temp/Model/Ayu + Li -t phaze-a -bs 8 -it 2000000 -D default -s 250 -ss 25000 -tia C:/Faceswap/044A -tib C:/Faceswap/Face Li Finall -2 -to D:/Temp/TimeLine -L INFO -gui
py_conda_version: conda 4.14.0
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: 65460MB, Available: 48054MB, Used: 17405MB, Free: 48054MB
=============== Pip Packages ===============
absl-py==1.2.0
astunparse==1.6.3
cachetools==5.2.0
certifi==2022.9.14
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==2.11.0
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.49.0
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==4.12.0
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:/Windows/Temp/abs_2a1e1vbeag/croots/recipe/numpy_and_numpy_base_1659432712056/work
nvidia-ml-py==11.515.75
oauthlib==3.2.1
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==3.19.5
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_1659726281030/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:/ci/tqdm_1650636210717/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==3.8.1
============== Conda Packages ==============
# packages in environment at C:\Users\adama\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
absl-py 1.2.0 pypi_0 pypi
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 2022.9.14 h5b45459_0 conda-forge
cachetools 5.2.0 pypi_0 pypi
certifi 2022.9.14 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 2.10.4 hd328e21_0
gast 0.4.0 pypi_0 pypi
git 2.34.1 haa95532_0
glib 2.69.1 h5dc1a3c_1
google-auth 2.11.0 pypi_0 pypi
google-auth-oauthlib 0.4.6 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.49.0 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 4.12.0 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 1.2.2 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 1.23.1 py39h7a0a035_0
numpy-base 1.23.1 py39hca35cd5_0
nvidia-ml-py 11.515.75 pypi_0 pypi
oauthlib 3.2.1 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 22.1.2 py39haa95532_0
ply 3.11 py39haa95532_0
protobuf 3.19.5 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_1
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 1.1.2 py39hfd4428b_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 3.39.2 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 4.64.0 py39haa95532_0
typing-extensions 4.3.0 py39haa95532_0
typing_extensions 4.3.0 py39haa95532_0
tzdata 2022c 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 5.2.5 h8cc25b3_1
zipp 3.8.1 pypi_0 pypi
zlib 1.2.12 h8cc25b3_3
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
[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: False
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
--------- 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
--------- train.ini ---------
[global]
centering: face
coverage: 87.5
icnr_init: False
conv_aware_init: False
optimizer: adam
learning_rate: 5e-05
epsilon_exponent: -5
autoclip: False
reflect_padding: False
allow_growth: False
mixed_precision: True
nan_protection: True
convert_batchsize: 16
[global.loss]
loss_function: mae
loss_function_2: mse
loss_weight_2: 100
loss_function_3: None
loss_weight_3: 0
loss_function_4: None
loss_weight_4: 0
mask_loss_function: mse
eye_multiplier: 3
mouth_multiplier: 2
penalized_mask_loss: True
mask_type: unet-dfl
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_v2_l
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: 192
dec_max_filters: 960
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: 14
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