I did everything like ( except I entered the alignments directory manualy, but then I got a crash report.
Here the crashreport i received.
Code: Select all
01/24/2021 01:59:03 MainProcess _run_0 training_data _expand_partials DEBUG Generating mask. side: 'b', filename: 'C:\Users\hanse\Desktop\df1\faceB\generated(3)(1)_000005_0.png'
01/24/2021 01:59:03 MainProcess _run_0 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000411_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_0 training_data _expand_partials DEBUG Generating mask. side: 'b', filename: 'C:\Users\hanse\Desktop\df1\faceB\generated(3)(1)_000085_0.png'
01/24/2021 01:59:03 MainProcess _run_0 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000399_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_0 training_data _expand_partials DEBUG Generating mask. side: 'b', filename: 'C:\Users\hanse\Desktop\df1\faceB\generated(3)(1)_000305_0.png'
01/24/2021 01:59:03 MainProcess _run_0 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000128_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_0 training_data _expand_partials DEBUG Generating mask. side: 'b', filename: 'C:\Users\hanse\Desktop\df1\faceB\generated(3)(1)_000026_0.png'
01/24/2021 01:59:03 MainProcess _run_0 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000173_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_0 training_data _expand_partials DEBUG Generating mask. side: 'b', filename: 'C:\Users\hanse\Desktop\df1\faceB\generated(3)(1)_000032_0.png'
01/24/2021 01:59:03 MainProcess _run_0 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000215_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_0 training_data _expand_partials DEBUG Generating mask. side: 'b', filename: 'C:\Users\hanse\Desktop\df1\faceB\generated(3)(1)_000015_0.png'
01/24/2021 01:59:03 MainProcess _run_0 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000404_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_0 training_data _expand_partials DEBUG Generating mask. side: 'b', filename: 'C:\Users\hanse\Desktop\df1\faceB\generated(3)(1)_000088_0.png'
01/24/2021 01:59:03 MainProcess _run_0 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000137_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_0 training_data _expand_partials DEBUG Generating mask. side: 'b', filename: 'C:\Users\hanse\Desktop\df1\faceB\generated(3)(1)_000035_0.png'
01/24/2021 01:59:03 MainProcess _run_0 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Mask already generated. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000189_0.png'
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000023_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000246_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Generating mask. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000089_0.png'
01/24/2021 01:59:03 MainProcess _run_1 aligned_face extract_face DEBUG _extract_face called without a loaded image. Returning empty face.
01/24/2021 01:59:03 MainProcess _run_1 training_data _expand_partials DEBUG Mask already generated. side: 'a', filename: 'C:\Users\hanse\Desktop\df1\faceA\jp tiktok_000071_0.png'
01/24/2021 01:59:03 MainProcess _training_0 ag_logging warn DEBUG AutoGraph could not transform <bound method Logger.isEnabledFor of <FaceswapLogger lib.model.losses_tf (DEBUG)>> and will run it as-is.\nPlease report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\nCause: module 'gast' has no attribute 'Index'\nTo silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
01/24/2021 01:59:03 MainProcess _training_0 ag_logging warn DEBUG AutoGraph could not transform <bound method Logger.findCaller of <FaceswapLogger lib.model.losses_tf (DEBUG)>> and will run it as-is.\nPlease report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\nCause: module 'gast' has no attribute 'Index'\nTo silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
01/24/2021 01:59:03 MainProcess _training_0 ag_logging warn DEBUG AutoGraph could not transform <bound method Logger.makeRecord of <FaceswapLogger lib.model.losses_tf (DEBUG)>> and will run it as-is.\nPlease report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\nCause: module 'gast' has no attribute 'Index'\nTo silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
01/24/2021 01:59:03 MainProcess _training_0 ag_logging warn DEBUG AutoGraph could not transform <bound method FaceswapFormatter.format of <lib.logger.FaceswapFormatter object at 0x000001856AC57F70>> and will run it as-is.\nPlease report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\nCause: module 'gast' has no attribute 'Index'\nTo silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
01/24/2021 01:59:03 MainProcess _training_0 api converted_call DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000018512090D30>, weight: 1.0, mask_channel: 3)
01/24/2021 01:59:04 MainProcess _training_0 ag_logging warn DEBUG AutoGraph could not transform <bound method LossWrapper._apply_mask of <class 'lib.model.losses_tf.LossWrapper'>> and will run it as-is.\nPlease report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\nCause: module 'gast' has no attribute 'Index'\nTo silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
01/24/2021 01:59:04 MainProcess _training_0 ag_logging warn DEBUG AutoGraph could not transform <bound method DSSIMObjective.call of <lib.model.losses_tf.DSSIMObjective object at 0x0000018575AAA910>> and will run it as-is.\nPlease report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\nCause: module 'gast' has no attribute 'Index'\nTo silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001851208F820>, weight: 1.0, mask_channel: 3)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185120A21C0>, weight: 3.0, mask_channel: 4)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 4
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185120A2AF0>, weight: 1.0, mask_channel: 1)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 1
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101C3070>, weight: 2.0, mask_channel: 5)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 5
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101C3AC0>, weight: 1.0, mask_channel: 2)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 2
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101CF070>, weight: 1.0, mask_channel: 3)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101CFAC0>, weight: 1.0, mask_channel: 3)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101B0040>, weight: 3.0, mask_channel: 4)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 4
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101B0B20>, weight: 1.0, mask_channel: 1)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 1
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101920A0>, weight: 2.0, mask_channel: 5)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 5
01/24/2021 01:59:04 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000018510192AF0>, weight: 1.0, mask_channel: 2)
01/24/2021 01:59:04 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 2
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000018512090D30>, weight: 1.0, mask_channel: 3)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001851208F820>, weight: 1.0, mask_channel: 3)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185120A21C0>, weight: 3.0, mask_channel: 4)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 4
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185120A2AF0>, weight: 1.0, mask_channel: 1)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 1
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101C3070>, weight: 2.0, mask_channel: 5)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 5
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101C3AC0>, weight: 1.0, mask_channel: 2)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 2
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101CF070>, weight: 1.0, mask_channel: 3)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101CFAC0>, weight: 1.0, mask_channel: 3)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101B0040>, weight: 3.0, mask_channel: 4)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 4
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101B0B20>, weight: 1.0, mask_channel: 1)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 1
01/24/2021 01:59:06 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000185101920A0>, weight: 2.0, mask_channel: 5)
01/24/2021 01:59:06 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 5
01/24/2021 01:59:07 MainProcess _training_0 tmp4mdlxfxe if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000018510192AF0>, weight: 1.0, mask_channel: 2)
01/24/2021 01:59:07 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 2
01/24/2021 01:59:10 MainProcess _training_0 multithreading run DEBUG Error in thread (_training_0): 2 root error(s) found.\n (0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.\n [[node original/encoder/conv_128_0_conv2d/Conv2D (defined at Software\faceswap\plugins\train\trainer\_base.py:238) ]]\n [[Func/cond/then/_0/input/_32/_46]]\n (1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.\n [[node original/encoder/conv_128_0_conv2d/Conv2D (defined at Software\faceswap\plugins\train\trainer\_base.py:238) ]]\n0 successful operations.\n0 derived errors ignored. [Op:__inference_train_function_8926]\n\nFunction call stack:\ntrain_function -> train_function\n
01/24/2021 01:59:11 MainProcess MainThread train _monitor DEBUG Thread error detected
01/24/2021 01:59:11 MainProcess MainThread train _monitor DEBUG Closed Monitor
01/24/2021 01:59:11 MainProcess MainThread train _end_thread DEBUG Ending Training thread
01/24/2021 01:59:11 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting...
01/24/2021 01:59:11 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training'
01/24/2021 01:59:11 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training_0'
01/24/2021 01:59:11 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training_0'
Traceback (most recent call last):
File "C:\Software\faceswap\lib\cli\launcher.py", line 182, in execute_script
process.process()
File "C:\Software\faceswap\scripts\train.py", line 170, in process
self._end_thread(thread, err)
File "C:\Software\faceswap\scripts\train.py", line 210, in _end_thread
thread.join()
File "C:\Software\faceswap\lib\multithreading.py", line 121, in join
raise thread.err[1].with_traceback(thread.err[2])
File "C:\Software\faceswap\lib\multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "C:\Software\faceswap\scripts\train.py", line 232, in _training
raise err
File "C:\Software\faceswap\scripts\train.py", line 222, in _training
self._run_training_cycle(model, trainer)
File "C:\Software\faceswap\scripts\train.py", line 302, in _run_training_cycle
trainer.train_one_step(viewer, timelapse)
File "C:\Software\faceswap\plugins\train\trainer\_base.py", line 238, in train_one_step
loss = self._model.model.train_on_batch(model_inputs, y=model_targets)
File "C:\Users\hanse\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\engine\training.py", line 1695, in train_on_batch
logs = train_function(iterator)
File "C:\Users\hanse\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\eager\def_function.py", line 780, in __call__
result = self._call(*args, **kwds)
File "C:\Users\hanse\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\eager\def_function.py", line 840, in _call
return self._stateless_fn(*args, **kwds)
File "C:\Users\hanse\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\eager\function.py", line 2829, in __call__
return graph_function._filtered_call(args, kwargs) # pylint: disable=protected-access
File "C:\Users\hanse\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\eager\function.py", line 1843, in _filtered_call
return self._call_flat(
File "C:\Users\hanse\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\eager\function.py", line 1923, in _call_flat
return self._build_call_outputs(self._inference_function.call(
File "C:\Users\hanse\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\eager\function.py", line 545, in call
outputs = execute.execute(
File "C:\Users\hanse\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\eager\execute.py", line 59, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node original/encoder/conv_128_0_conv2d/Conv2D (defined at Software\faceswap\plugins\train\trainer\_base.py:238) ]]
[[Func/cond/then/_0/input/_32/_46]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node original/encoder/conv_128_0_conv2d/Conv2D (defined at Software\faceswap\plugins\train\trainer\_base.py:238) ]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_function_8926]
Function call stack:
train_function -> train_function
============ System Information ============
encoding: cp1252
git_branch: Not Found
git_commits: Not Found
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: GeForce RTX 2070
gpu_devices_active: GPU_0
gpu_driver: 461.09
gpu_vram: GPU_0: 8192MB
os_machine: AMD64
os_platform: Windows-10-10.0.18362-SP0
os_release: 10
py_command: C:\Software\faceswap\faceswap.py train -A C:/Users/hanse/Desktop/df1/faceA -ala C:/Users/hanse/Desktop/df1/jp tiktok_alignments.fsa -B C:/Users/hanse/Desktop/df1/faceB -alb C:/Users/hanse/Desktop/df1/generated(3)(1)_alignments.fsa -m C:/Users/hanse/Desktop/df1/faceAB -t original -bs 12 -it 1000000 -s 250 -ss 25000 -tia C:/Users/hanse/Desktop/df1/faceA -tib C:/Users/hanse/Desktop/df1/faceB -to C:/Users/hanse/Desktop/df1/tl -ps 50 -L INFO -gui
py_conda_version: conda 4.9.2
py_implementation: CPython
py_version: 3.8.5
py_virtual_env: True
sys_cores: 6
sys_processor: Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
sys_ram: Total: 16319MB, Available: 7017MB, Used: 9301MB, Free: 7017MB
=============== Pip Packages ===============
absl-py @ file:///tmp/build/80754af9/absl-py_1607439979954/work
aiohttp @ file:///C:/ci/aiohttp_1607109697839/work
astunparse==1.6.3
async-timeout==3.0.1
attrs @ file:///tmp/build/80754af9/attrs_1604765588209/work
blinker==1.4
brotlipy==0.7.0
cachetools @ file:///tmp/build/80754af9/cachetools_1607706694405/work
certifi==2020.12.5
cffi @ file:///C:/ci/cffi_1606255208697/work
chardet @ file:///C:/ci/chardet_1605303225733/work
click @ file:///home/linux1/recipes/ci/click_1610990599742/work
cryptography==2.9.2
cycler==0.10.0
fastcluster==1.1.26
ffmpy==0.2.3
gast @ file:///tmp/build/80754af9/gast_1597433534803/work
google-auth @ file:///tmp/build/80754af9/google-auth_1607969906642/work
google-auth-oauthlib @ file:///tmp/build/80754af9/google-auth-oauthlib_1603929124518/work
google-pasta==0.2.0
grpcio @ file:///C:/ci/grpcio_1597406462198/work
h5py==2.10.0
idna @ file:///home/linux1/recipes/ci/idna_1610986105248/work
imageio @ file:///tmp/build/80754af9/imageio_1594161405741/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1609799311556/work
importlib-metadata @ file:///tmp/build/80754af9/importlib-metadata_1602276842396/work
joblib @ file:///tmp/build/80754af9/joblib_1607970656719/work
Keras-Applications @ file:///tmp/build/80754af9/keras-applications_1594366238411/work
Keras-Preprocessing==1.1.0
kiwisolver @ file:///C:/ci/kiwisolver_1604014703538/work
Markdown @ file:///C:/ci/markdown_1605111189761/work
matplotlib @ file:///C:/ci/matplotlib-base_1592837548929/work
mkl-fft==1.2.0
mkl-random==1.1.1
mkl-service==2.3.0
multidict @ file:///C:/ci/multidict_1600456481656/work
numpy @ file:///C:/ci/numpy_and_numpy_base_1603466732592/work
nvidia-ml-py3 @ git+https://github.com/deepfakes/nvidia-ml-py3.git@6fc29ac84b32bad877f078cb4a777c1548a00bf6
oauthlib==3.1.0
olefile==0.46
opencv-python==4.5.1.48
opt-einsum==3.1.0
pathlib==1.0.1
Pillow @ file:///C:/ci/pillow_1609786840597/work
protobuf==3.13.0
psutil @ file:///C:/ci/psutil_1598370330503/work
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycparser @ file:///tmp/build/80754af9/pycparser_1594388511720/work
PyJWT @ file:///C:/ci/pyjwt_1610893382614/work
pyOpenSSL @ file:///tmp/build/80754af9/pyopenssl_1608057966937/work
pyparsing @ file:///home/linux1/recipes/ci/pyparsing_1610983426697/work
pyreadline==2.1
PySocks @ file:///C:/ci/pysocks_1605287845585/work
python-dateutil==2.8.1
pywin32==227
requests @ file:///tmp/build/80754af9/requests_1608241421344/work
requests-oauthlib==1.3.0
rsa @ file:///tmp/build/80754af9/rsa_1610483308194/work
scikit-learn @ file:///C:/ci/scikit-learn_1598377018496/work
scipy @ file:///C:/ci/scipy_1604596260408/work
sip==4.19.13
six @ file:///C:/ci/six_1605187374963/work
tensorboard @ file:///home/builder/ktietz/conda/conda-bld/tensorboard_1604313476433/work/tmp_pip_dir
tensorboard-plugin-wit==1.6.0
tensorflow==2.3.0
tensorflow-estimator @ file:///tmp/build/80754af9/tensorflow-estimator_1599136169057/work/whl_temp/tensorflow_estimator-2.3.0-py2.py3-none-any.whl
termcolor==1.1.0
threadpoolctl @ file:///tmp/tmp9twdgx9k/threadpoolctl-2.1.0-py3-none-any.whl
tornado @ file:///C:/ci/tornado_1606942392901/work
tqdm @ file:///tmp/build/80754af9/tqdm_1609788246169/work
typing-extensions @ file:///tmp/build/80754af9/typing_extensions_1598376058250/work
urllib3 @ file:///tmp/build/80754af9/urllib3_1606938623459/work
Werkzeug==1.0.1
win-inet-pton @ file:///C:/ci/win_inet_pton_1605306167264/work
wincertstore==0.2
wrapt==1.12.1
yarl @ file:///C:/ci/yarl_1598045274898/work
zipp @ file:///tmp/build/80754af9/zipp_1604001098328/work
============== Conda Packages ==============
# packages in environment at C:\Users\hanse\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
_tflow_select 2.3.0 gpu
absl-py 0.11.0 pyhd3eb1b0_1
aiohttp 3.7.3 py38h2bbff1b_1
astunparse 1.6.3 py_0
async-timeout 3.0.1 py38_0
attrs 20.3.0 pyhd3eb1b0_0
blas 1.0 mkl
blinker 1.4 py38_0
brotlipy 0.7.0 py38h2bbff1b_1003
ca-certificates 2021.1.19 haa95532_0
cachetools 4.2.0 pyhd3eb1b0_0
certifi 2020.12.5 py38haa95532_0
cffi 1.14.4 py38hcd4344a_0
chardet 3.0.4 py38haa95532_1003
click 7.1.2 pyhd3eb1b0_0
cryptography 2.9.2 py38h7a1dbc1_0
cudatoolkit 10.1.243 h74a9793_0
cudnn 7.6.5 cuda10.1_0
cycler 0.10.0 py38_0
fastcluster 1.1.26 py38h251f6bf_2 conda-forge
ffmpeg 4.3.1 ha925a31_0 conda-forge
ffmpy 0.2.3 pypi_0 pypi
freetype 2.10.4 hd328e21_0
gast 0.4.0 py_0
git 2.23.0 h6bb4b03_0
google-auth 1.24.0 pyhd3eb1b0_0
google-auth-oauthlib 0.4.2 pyhd3eb1b0_2
google-pasta 0.2.0 py_0
grpcio 1.31.0 py38he7da953_0
h5py 2.10.0 py38h5e291fa_0
hdf5 1.10.4 h7ebc959_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 2.10 pyhd3eb1b0_0
imageio 2.9.0 py_0
imageio-ffmpeg 0.4.3 pyhd8ed1ab_0 conda-forge
importlib-metadata 2.0.0 py_1
intel-openmp 2020.2 254
joblib 1.0.0 pyhd3eb1b0_0
jpeg 9b hb83a4c4_2
keras-applications 1.0.8 py_1
keras-preprocessing 1.1.0 py_1
kiwisolver 1.3.0 py38hd77b12b_0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.13.0.1 h200bbdf_0
libtiff 4.1.0 h56a325e_1
lz4-c 1.9.3 h2bbff1b_0
markdown 3.3.3 py38haa95532_0
matplotlib 3.2.2 0
matplotlib-base 3.2.2 py38h64f37c6_0
mkl 2020.2 256
mkl-service 2.3.0 py38h196d8e1_0
mkl_fft 1.2.0 py38h45dec08_0
mkl_random 1.1.1 py38h47e9c7a_0
multidict 4.7.6 py38he774522_1
numpy 1.19.2 py38hadc3359_0
numpy-base 1.19.2 py38ha3acd2a_0
nvidia-ml-py3 7.352.1 pypi_0 pypi
oauthlib 3.1.0 py_0
olefile 0.46 py_0
opencv-python 4.5.1.48 pypi_0 pypi
openssl 1.1.1i h2bbff1b_0
opt_einsum 3.1.0 py_0
pathlib 1.0.1 py_1
pillow 8.1.0 py38h4fa10fc_0
pip 20.3.3 py38haa95532_0
protobuf 3.13.0.1 py38ha925a31_1
psutil 5.7.2 py38he774522_0
pyasn1 0.4.8 py_0
pyasn1-modules 0.2.8 py_0
pycparser 2.20 py_2
pyjwt 2.0.1 py38haa95532_0
pyopenssl 20.0.1 pyhd3eb1b0_1
pyparsing 2.4.7 pyhd3eb1b0_0
pyqt 5.9.2 py38ha925a31_4
pyreadline 2.1 py38_1
pysocks 1.7.1 py38haa95532_0
python 3.8.5 h5fd99cc_1
python-dateutil 2.8.1 py_0
python_abi 3.8 1_cp38 conda-forge
pywin32 227 py38he774522_1
qt 5.9.7 vc14h73c81de_0
requests 2.25.1 pyhd3eb1b0_0
requests-oauthlib 1.3.0 py_0
rsa 4.7 pyhd3eb1b0_1
scikit-learn 0.23.2 py38h47e9c7a_0
scipy 1.5.2 py38h14eb087_0
setuptools 51.3.3 py38haa95532_4
sip 4.19.13 py38ha925a31_0
six 1.15.0 py38haa95532_0
sqlite 3.33.0 h2a8f88b_0
tensorboard 2.3.0 pyh4dce500_0
tensorboard-plugin-wit 1.6.0 py_0
tensorflow 2.3.0 mkl_py38h1fcfbd6_0
tensorflow-base 2.3.0 gpu_py38h7339f5a_0
tensorflow-estimator 2.3.0 pyheb71bc4_0
tensorflow-gpu 2.3.0 he13fc11_0
termcolor 1.1.0 py38_1
threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.10 he774522_0
tornado 6.1 py38h2bbff1b_0
tqdm 4.55.1 pyhd3eb1b0_0
typing-extensions 3.7.4.3 0
typing_extensions 3.7.4.3 py_0
urllib3 1.26.2 pyhd3eb1b0_0
vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 1.0.1 py_0
wheel 0.36.2 pyhd3eb1b0_0
win_inet_pton 1.1.0 py38haa95532_0
wincertstore 0.2 py38_0
wrapt 1.12.1 py38he774522_1
xz 5.2.5 h62dcd97_0
yarl 1.5.1 py38he774522_0
zipp 3.4.0 pyhd3eb1b0_0
zlib 1.2.11 h62dcd97_4
zstd 1.4.5 h04227a9_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.box_blend]
type: gaussian
distance: 11.0
radius: 5.0
passes: 1
[mask.mask_blend]
type: normalized
kernel_size: 3
passes: 4
threshold: 4
erosion: 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
jpg_quality: 75
png_compress_level: 3
[writer.pillow]
format: png
draw_transparent: False
optimize: False
gif_interlace: True
jpg_quality: 75
png_compress_level: 3
tif_compression: tiff_deflate
--------- extract.ini ---------
[global]
allow_growth: True
[align.fan]
batch-size: 12
[detect.cv2_dnn]
confidence: 50
[detect.mtcnn]
minsize: 20
threshold_1: 0.6
threshold_2: 0.7
threshold_3: 0.7
scalefactor: 0.709
batch-size: 8
[detect.s3fd]
confidence: 70
batch-size: 1
[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: 68.75
icnr_init: False
conv_aware_init: False
optimizer: adam
learning_rate: 5e-05
reflect_padding: False
allow_growth: False
mixed_precision: False
convert_batchsize: 16
[global.loss]
loss_function: ssim
mask_loss_function: mse
l2_reg_term: 100
eye_multiplier: 3
mouth_multiplier: 2
penalized_mask_loss: True
mask_type: extended
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
clipnorm: True
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.realface]
input_size: 64
output_size: 128
dense_nodes: 1536
complexity_encoder: 128
complexity_decoder: 512
[model.unbalanced]
input_size: 128
lowmem: False
clipnorm: True
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
disable_warp: False
color_lightness: 30
color_ab: 8
color_clahe_chance: 50
color_clahe_max_size: 4