For some reason I always get this error, and I would really like some help on what it means and how to fix it.
Code: Select all
06/02/2020 20:07:11 MainProcess ThreadPoolExecutor-16_1 _base save DEBUG Saving model: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_decoder_B.h5'
06/02/2020 20:07:11 MainProcess ThreadPoolExecutor-16_0 _base save DEBUG Saving model: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_decoder_A.h5'
06/02/2020 20:07:11 MainProcess ThreadPoolExecutor-16_2 _base save DEBUG Saving model: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_encoder.h5'
06/02/2020 20:07:11 MainProcess ThreadPoolExecutor-16_3 serializer save DEBUG filename: C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_state.json, data type: <class 'dict'>
06/02/2020 20:07:11 MainProcess ThreadPoolExecutor-16_3 serializer _check_extension DEBUG Original filename: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_state.json', final filename: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_state.json'
06/02/2020 20:07:11 MainProcess ThreadPoolExecutor-16_3 serializer marshal DEBUG data type: <class 'dict'>
06/02/2020 20:07:11 MainProcess ThreadPoolExecutor-16_3 serializer marshal DEBUG returned data type: <class 'bytes'>
06/02/2020 20:07:11 MainProcess ThreadPoolExecutor-16_3 _base save DEBUG Saved State
06/02/2020 20:07:16 MainProcess _training_0 _base save_models INFO [Saved models] - Average since last save: face_loss_A: 0.21554, face_loss_B: 0.17824
06/02/2020 23:06:59 MainProcess _training_0 _base generate_preview DEBUG Generating preview
06/02/2020 23:06:59 MainProcess _training_0 _base largest_face_index DEBUG 0
06/02/2020 23:06:59 MainProcess _training_0 _base compile_sample DEBUG Compiling samples: (side: 'a', samples: 14)
06/02/2020 23:08:03 MainProcess _training_0 _base generate_preview DEBUG Generating preview
06/02/2020 23:08:03 MainProcess _training_0 _base largest_face_index DEBUG 0
06/02/2020 23:08:03 MainProcess _training_0 _base compile_sample DEBUG Compiling samples: (side: 'b', samples: 14)
06/02/2020 23:08:03 MainProcess _training_0 _base show_sample DEBUG Showing sample
06/02/2020 23:08:03 MainProcess _training_0 _base _get_predictions DEBUG Getting Predictions
06/02/2020 23:08:15 MainProcess _training_0 _base _get_predictions DEBUG Returning predictions: {'a_a': (14, 64, 64, 3), 'b_a': (14, 64, 64, 3), 'a_b': (14, 64, 64, 3), 'b_b': (14, 64, 64, 3)}
06/02/2020 23:08:15 MainProcess _training_0 _base _to_full_frame DEBUG side: 'a', number of sample arrays: 3, prediction.shapes: [(14, 64, 64, 3), (14, 64, 64, 3)])
06/02/2020 23:08:15 MainProcess _training_0 _base _frame_overlay DEBUG full_size: 256, target_size: 176, color: (0, 0, 255)
06/02/2020 23:08:15 MainProcess _training_0 _base _frame_overlay DEBUG Overlayed background. Shape: (14, 256, 256, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 176, 176, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 176, 176, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 176, 176, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 128, 128, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 128, 128, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 128, 128, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _get_headers DEBUG side: 'a', width: 128
06/02/2020 23:08:15 MainProcess _training_0 _base _get_headers DEBUG height: 32, total_width: 384
06/02/2020 23:08:15 MainProcess _training_0 _base _get_headers DEBUG texts: ['Original (A)', 'Original > Original', 'Original > Swap'], text_sizes: [(72, 9), (116, 9), (102, 9)], text_x: [28, 134, 269], text_y: 20
06/02/2020 23:08:15 MainProcess _training_0 _base _get_headers DEBUG header_box.shape: (32, 384, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _to_full_frame DEBUG side: 'b', number of sample arrays: 3, prediction.shapes: [(14, 64, 64, 3), (14, 64, 64, 3)])
06/02/2020 23:08:15 MainProcess _training_0 _base _frame_overlay DEBUG full_size: 256, target_size: 176, color: (0, 0, 255)
06/02/2020 23:08:15 MainProcess _training_0 _base _frame_overlay DEBUG Overlayed background. Shape: (14, 256, 256, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 176, 176, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 176, 176, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 176, 176, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 128, 128, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 128, 128, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
06/02/2020 23:08:15 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 128, 128, 3))
06/02/2020 23:08:15 MainProcess _training_0 _base _get_headers DEBUG side: 'b', width: 128
06/02/2020 23:08:15 MainProcess _training_0 _base _get_headers DEBUG height: 32, total_width: 384
06/02/2020 23:08:15 MainProcess _training_0 _base _get_headers DEBUG texts: ['Swap (B)', 'Swap > Swap', 'Swap > Original'], text_sizes: [(59, 9), (87, 9), (102, 9)], text_x: [34, 148, 269], text_y: 20
06/02/2020 23:08:15 MainProcess _training_0 _base _get_headers DEBUG header_box.shape: (32, 384, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _duplicate_headers DEBUG side: a header.shape: (32, 384, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _duplicate_headers DEBUG side: b header.shape: (32, 384, 3)
06/02/2020 23:08:15 MainProcess _training_0 _base _stack_images DEBUG Stack images
06/02/2020 23:08:15 MainProcess _training_0 _base get_transpose_axes DEBUG Even number of images to stack
06/02/2020 23:08:15 MainProcess _training_0 _base _stack_images DEBUG Stacked images
06/02/2020 23:08:15 MainProcess _training_0 _base show_sample DEBUG Compiled sample
06/02/2020 23:08:16 MainProcess _training_0 _base save_models DEBUG Backing up and saving models
06/02/2020 23:08:16 MainProcess _training_0 _base get_save_averages DEBUG Getting save averages
06/02/2020 23:08:16 MainProcess _training_0 _base get_save_averages DEBUG Average losses since last save: {'a': 0.10190289102494716, 'b': 0.1120093747228384}
06/02/2020 23:08:16 MainProcess _training_0 _base check_loss_drop DEBUG Loss for 'a' has dropped
06/02/2020 23:08:16 MainProcess _training_0 _base check_loss_drop DEBUG Loss for 'b' has dropped
06/02/2020 23:08:16 MainProcess _training_0 _base should_backup DEBUG Lowest historical save iteration loss average: {'a': 0.21553638577461243, 'b': 0.1782432198524475}
06/02/2020 23:08:16 MainProcess _training_0 _base should_backup DEBUG Updating lowest save iteration average for 'a': 0.10190289102494716
06/02/2020 23:08:16 MainProcess _training_0 _base should_backup DEBUG Updating lowest save iteration average for 'b': 0.1120093747228384
06/02/2020 23:08:16 MainProcess _training_0 _base should_backup DEBUG Backing up: True
06/02/2020 23:08:16 MainProcess _training_0 _base save_models INFO Backing up models...
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_0 backup_restore backup_model VERBOSE Backing up: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_decoder_A.h5' to 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_decoder_A.h5.bk'
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_1 backup_restore backup_model VERBOSE Backing up: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_decoder_B.h5' to 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_decoder_B.h5.bk'
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_2 backup_restore backup_model VERBOSE Backing up: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_encoder.h5' to 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_encoder.h5.bk'
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_3 _base save DEBUG Saving State
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_3 backup_restore backup_model VERBOSE Backing up: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_state.json' to 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_state.json.bk'
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_1 _base save DEBUG Saving model: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_decoder_B.h5'
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_2 _base save DEBUG Saving model: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_encoder.h5'
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_0 _base save DEBUG Saving model: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_decoder_A.h5'
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_3 serializer save DEBUG filename: C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_state.json, data type: <class 'dict'>
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_3 serializer _check_extension DEBUG Original filename: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_state.json', final filename: 'C:\Users\HP Pavilion\Desktop\deepface\jeezz\original_state.json'
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_3 serializer marshal DEBUG data type: <class 'dict'>
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_3 serializer marshal DEBUG returned data type: <class 'bytes'>
06/02/2020 23:08:16 MainProcess ThreadPoolExecutor-219_3 _base save DEBUG Saved State
06/02/2020 23:08:34 MainProcess _training_0 _base save_models INFO [Saved models] - Average since last save: face_loss_A: 0.10190, face_loss_B: 0.11201
06/02/2020 23:52:27 MainProcess MainThread train _monitor DEBUG Thread error detected
06/02/2020 23:52:27 MainProcess _training_0 multithreading run DEBUG Error in thread (_training_0): Unable to allocate SVM memory
06/02/2020 23:52:27 MainProcess MainThread train _monitor DEBUG Closed Monitor
06/02/2020 23:52:27 MainProcess MainThread train _end_thread DEBUG Ending Training thread
06/02/2020 23:52:27 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting...
06/02/2020 23:52:27 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training'
06/02/2020 23:52:27 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training_0'
06/02/2020 23:52:27 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training_0'
Traceback (most recent call last):
File "C:\Users\HP Pavilion\faceswap\lib\cli\launcher.py", line 155, in execute_script
process.process()
File "C:\Users\HP Pavilion\faceswap\scripts\train.py", line 161, in process
self._end_thread(thread, err)
File "C:\Users\HP Pavilion\faceswap\scripts\train.py", line 201, in _end_thread
thread.join()
File "C:\Users\HP Pavilion\faceswap\lib\multithreading.py", line 121, in join
raise thread.err[1].with_traceback(thread.err[2])
File "C:\Users\HP Pavilion\faceswap\lib\multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "C:\Users\HP Pavilion\faceswap\scripts\train.py", line 226, in _training
raise err
File "C:\Users\HP Pavilion\faceswap\scripts\train.py", line 216, in _training
self._run_training_cycle(model, trainer)
File "C:\Users\HP Pavilion\faceswap\scripts\train.py", line 305, in _run_training_cycle
trainer.train_one_step(viewer, timelapse)
File "C:\Users\HP Pavilion\faceswap\plugins\train\trainer\_base.py", line 316, in train_one_step
raise err
File "C:\Users\HP Pavilion\faceswap\plugins\train\trainer\_base.py", line 283, in train_one_step
loss[side] = batcher.train_one_batch()
File "C:\Users\HP Pavilion\faceswap\plugins\train\trainer\_base.py", line 424, in train_one_batch
loss = self._model.predictors[self._side].train_on_batch(model_inputs, model_targets)
File "C:\Users\HP Pavilion\MiniConda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 1217, in train_on_batch
outputs = self.train_function(ins)
File "C:\Users\HP Pavilion\MiniConda3\envs\faceswap\lib\site-packages\plaidml\keras\backend.py", line 175, in __call__
self._invoker.invoke()
File "C:\Users\HP Pavilion\MiniConda3\envs\faceswap\lib\site-packages\plaidml\__init__.py", line 1455, in invoke
return Invocation(self._ctx, self)
File "C:\Users\HP Pavilion\MiniConda3\envs\faceswap\lib\site-packages\plaidml\__init__.py", line 1464, in __init__
self._as_parameter_ = _lib().plaidml_schedule_invocation(ctx, invoker)
File "C:\Users\HP Pavilion\MiniConda3\envs\faceswap\lib\site-packages\plaidml\__init__.py", line 777, in _check_err
self.raise_last_status()
File "C:\Users\HP Pavilion\MiniConda3\envs\faceswap\lib\site-packages\plaidml\library.py", line 131, in raise_last_status
raise self.last_status()
plaidml.exceptions.ResourceExhausted: Unable to allocate SVM memory
============ System Information ============
encoding: cp1252
git_branch: master
git_commits: ac40b0f Remove subpixel upscaling option (#1024)
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: Advanced Micro Devices, Inc. - Stoney (experimental)
gpu_devices_active: GPU_0
gpu_driver: ['3075.12']
gpu_vram: GPU_0: 1378MB
os_machine: AMD64
os_platform: Windows-10-10.0.18362-SP0
os_release: 10
py_command: C:\Users\HP Pavilion\faceswap\faceswap.py train -A C:/Users/HP Pavilion/Desktop/deepface/orig -ala C:/Users/HP Pavilion/Desktop/data_dst/alignments.fsa -B C:/Users/HP Pavilion/Desktop/deepface/otp -alb C:/Users/HP Pavilion/Desktop/data_src/alignments.fsa -m C:/Users/HP Pavilion/Desktop/deepface/jeezz -t original -bs 64 -it 100000 -s 100 -ss 25000 -ps 50 -nac -L INFO -gui
py_conda_version: conda 4.8.3
py_implementation: CPython
py_version: 3.7.7
py_virtual_env: True
sys_cores: 2
sys_processor: AMD64 Family 21 Model 112 Stepping 0, AuthenticAMD
sys_ram: Total: 3974MB, Available: 463MB, Used: 3511MB, Free: 463MB
=============== Pip Packages ===============
============== Conda Packages ==============
# packages in environment at C:\Users\HP Pavilion\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
_tflow_select 2.2.0 eigen
absl-py 0.9.0 py37_0
astor 0.8.0 py37_0
blas 1.0 mkl
blinker 1.4 py37_0
ca-certificates 2020.1.1 0
cachetools 3.1.1 py_0
certifi 2020.4.5.1 py37_0
cffi 1.14.0 py37h7a1dbc1_0
chardet 3.0.4 py37_1003
click 7.1.2 py_0
cloudpickle 1.4.1 py_0
cryptography 2.9.2 py37h7a1dbc1_0
cycler 0.10.0 py37_0
cytoolz 0.10.1 py37he774522_0
dask-core 2.17.0 py_0
decorator 4.4.2 py_0
enum34 1.1.10 pypi_0 pypi
fastcluster 1.1.26 py37he350917_0 conda-forge
ffmpeg 4.2.3 ha925a31_0 conda-forge
ffmpy 0.2.2 pypi_0 pypi
freetype 2.9.1 ha9979f8_1
gast 0.2.2 py37_0
git 2.23.0 h6bb4b03_0
google-auth 1.14.1 py_0
google-auth-oauthlib 0.4.1 py_2
google-pasta 0.2.0 py_0
grpcio 1.27.2 py37h351948d_0
h5py 2.9.0 py37h5e291fa_0
hdf5 1.10.4 h7ebc959_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 2.9 py_1
imageio 2.6.1 py37_0
imageio-ffmpeg 0.4.2 py_0 conda-forge
intel-openmp 2020.1 216
joblib 0.15.1 py_0
jpeg 9b hb83a4c4_2
keras 2.2.4 0
keras-applications 1.0.8 py_0
keras-base 2.2.4 py37_0
keras-preprocessing 1.1.0 py_1
kiwisolver 1.2.0 py37h74a9793_0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.11.4 h7bd577a_0
libtiff 4.1.0 h56a325e_0
markdown 3.1.1 py37_0
matplotlib 3.1.1 py37hc8f65d3_0
matplotlib-base 3.1.3 py37h64f37c6_0
mkl 2020.1 216
mkl-service 2.3.0 py37hb782905_0
mkl_fft 1.0.15 py37h14836fe_0
mkl_random 1.1.1 py37h47e9c7a_0
networkx 2.4 py_0
numpy 1.17.4 py37h4320e6b_0
numpy-base 1.17.4 py37hc3f5095_0
nvidia-ml-py3 7.352.1 pypi_0 pypi
oauthlib 3.1.0 py_0
olefile 0.46 py37_0
opencv-python 4.1.2.30 pypi_0 pypi
openssl 1.1.1g he774522_0
opt_einsum 3.1.0 py_0
pathlib 1.0.1 py37_1
pillow 6.2.1 py37hdc69c19_0
pip 20.0.2 py37_3
plaidml 0.6.4 pypi_0 pypi
plaidml-keras 0.6.4 pypi_0 pypi
protobuf 3.11.4 py37h33f27b4_0
psutil 5.7.0 py37he774522_0
pyasn1 0.4.8 py_0
pyasn1-modules 0.2.7 py_0
pycparser 2.20 py_0
pyjwt 1.7.1 py37_0
pyopenssl 19.1.0 py37_0
pyparsing 2.4.7 py_0
pyqt 5.9.2 py37h6538335_2
pyreadline 2.1 py37_1
pysocks 1.7.1 py37_0
python 3.7.7 h81c818b_4
python-dateutil 2.8.1 py_0
python_abi 3.7 1_cp37m conda-forge
pytz 2020.1 py_0
pywavelets 1.1.1 py37he774522_0
pywin32 227 py37he774522_1
pyyaml 5.3.1 py37he774522_0
qt 5.9.7 vc14h73c81de_0
requests 2.23.0 py37_0
requests-oauthlib 1.3.0 py_0
rsa 4.0 py_0
scikit-image 0.16.2 py37h47e9c7a_0
scikit-learn 0.22.1 py37h6288b17_0
scipy 1.4.1 py37h9439919_0
setuptools 46.4.0 py37_0
sip 4.19.8 py37h6538335_0
six 1.14.0 py37_0
sqlite 3.31.1 h2a8f88b_1
tensorboard 2.2.1 pyh532a8cf_0
tensorboard-plugin-wit 1.6.0 py_0
tensorflow 1.15.0 eigen_py37h9f89a44_0
tensorflow-base 1.15.0 eigen_py37h07d2309_0
tensorflow-estimator 1.15.1 pyh2649769_0
termcolor 1.1.0 py37_1
tk 8.6.8 hfa6e2cd_0
toolz 0.10.0 py_0
toposort 1.5 py_3 conda-forge
tornado 6.0.4 py37he774522_1
tqdm 4.46.0 py_0
urllib3 1.25.8 py37_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_2
werkzeug 0.16.1 py_0
wheel 0.34.2 py37_0
win_inet_pton 1.1.0 py37_0
wincertstore 0.2 py37_0
wrapt 1.12.1 py37he774522_1
xz 5.2.5 h62dcd97_0
yaml 0.1.7 hc54c509_2
zlib 1.2.11 h62dcd97_4
zstd 1.3.7 h508b16e_0
=============== State File =================
{
"name": "original",
"sessions": {
"1": {
"timestamp": 1591084995.354819,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 64,
"iterations": 1,
"config": {
"learning_rate": 5e-05
}
},
"2": {
"timestamp": 1591093982.0619726,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 64,
"iterations": 101,
"config": {
"learning_rate": 5e-05
}
}
},
"lowest_avg_loss": {
"a": 0.10190289102494716,
"b": 0.1120093747228384
},
"iterations": 102,
"inputs": {
"face_in": [
64,
64,
3
]
},
"training_size": 256,
"config": {
"coverage": 68.75,
"mask_type": null,
"mask_blur_kernel": 3,
"mask_threshold": 4,
"learn_mask": false,
"icnr_init": false,
"conv_aware_init": false,
"reflect_padding": false,
"penalized_mask_loss": true,
"loss_function": "mae",
"learning_rate": 5e-05,
"lowmem": false
}
}
================= Configs ==================
--------- .faceswap ---------
backend: amd
--------- 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: unsharp_mask
amount: 150
radius: 0.3
threshold: 5.0
[writer.ffmpeg]
container: mp4
codec: libx264
crf: 23
preset: medium
tune: none
profile: auto
level: auto
[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: False
[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: 4
[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]
coverage: 68.75
mask_type: none
mask_blur_kernel: 3
mask_threshold: 4
learn_mask: False
icnr_init: False
conv_aware_init: False
reflect_padding: False
penalized_mask_loss: True
loss_function: mae
learning_rate: 5e-05
[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
color_lightness: 30
color_ab: 8
color_clahe_chance: 50
color_clahe_max_size: 4