05/21/2022 22:45:16 MainProcess _training_0 _base _get_headers DEBUG height: 16, total_width: 216 05/21/2022 22:45:16 MainProcess _training_0 _base _get_headers DEBUG texts: ['Original (A)', 'Original > Original', 'Original > Swap'], text_sizes: [(41, 6), (66, 6), (58, 6)], text_x: [15, 75, 151], text_y: 11 05/21/2022 22:45:16 MainProcess _training_0 _base _get_headers DEBUG header_box.shape: (16, 216, 3) 05/21/2022 22:45:16 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)]) 05/21/2022 22:45:16 MainProcess _training_0 _base _process_full DEBUG full_size: 384, prediction_size: 64, color: (0, 0, 255) 05/21/2022 22:45:16 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 384, 384, 3), target_size: 72, scale: 0.1875) 05/21/2022 22:45:16 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 72, 72, 3)) 05/21/2022 22:45:17 MainProcess _training_0 _base _process_full DEBUG Overlayed background. Shape: (14, 72, 72, 3) 05/21/2022 22:45:17 MainProcess _training_0 _base _compile_masked DEBUG masked shapes: [(14, 64, 64, 3), (14, 64, 64, 3), (14, 64, 64, 3)] 05/21/2022 22:45:17 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 72, 72, 3) 05/21/2022 22:45:17 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 72, 72, 3) 05/21/2022 22:45:17 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 72, 72, 3) 05/21/2022 22:45:17 MainProcess _training_0 _base _get_headers DEBUG side: 'b', width: 72 05/21/2022 22:45:17 MainProcess _training_0 _base _get_headers DEBUG height: 16, total_width: 216 05/21/2022 22:45:17 MainProcess _training_0 _base _get_headers DEBUG texts: ['Swap (B)', 'Swap > Swap', 'Swap > Original'], text_sizes: [(34, 6), (50, 6), (58, 6)], text_x: [19, 83, 151], text_y: 11 05/21/2022 22:45:17 MainProcess _training_0 _base _get_headers DEBUG header_box.shape: (16, 216, 3) 05/21/2022 22:45:17 MainProcess _training_0 _base _duplicate_headers DEBUG side: a header.shape: (16, 216, 3) 05/21/2022 22:45:17 MainProcess _training_0 _base _duplicate_headers DEBUG side: b header.shape: (16, 216, 3) 05/21/2022 22:45:17 MainProcess _training_0 _base _stack_images DEBUG Stack images 05/21/2022 22:45:17 MainProcess _training_0 _base get_transpose_axes DEBUG Even number of images to stack 05/21/2022 22:45:17 MainProcess _training_0 _base _stack_images DEBUG Stacked images 05/21/2022 22:45:17 MainProcess _training_0 _base show_sample DEBUG Compiled sample 05/21/2022 22:45:17 MainProcess _training_0 train _show DEBUG Updating preview: (name: Training - 'S': Save Now. 'R': Refresh Preview. 'M': Toggle Mask. 'ENTER': Save and Quit) 05/21/2022 22:45:17 MainProcess _training_0 train _show DEBUG Generating preview for GUI 05/21/2022 22:45:17 MainProcess _training_0 train _show DEBUG Generated preview for GUI: '.gui_training_preview.jpg' 05/21/2022 22:45:17 MainProcess _training_0 train _show DEBUG Updated preview: (name: Training - 'S': Save Now. 'R': Refresh Preview. 'M': Toggle Mask. 'ENTER': Save and Quit) 05/21/2022 22:45:17 MainProcess _training_0 train _run_training_cycle DEBUG Save Iteration: (iteration: 312500 05/21/2022 22:45:17 MainProcess _training_0 _base _save DEBUG Backing up and saving models 05/21/2022 22:45:17 MainProcess _training_0 _base _get_save_averages DEBUG Getting save averages 05/21/2022 22:45:17 MainProcess _training_0 _base _get_save_averages DEBUG Average losses since last save: [0.016500654708594083, 0.025551701448857784] 05/21/2022 22:45:17 MainProcess _training_0 _base _should_backup DEBUG Should backup: False 05/21/2022 22:45:18 MainProcess _training_0 _base save DEBUG Saving State 05/21/2022 22:45:18 MainProcess _training_0 serializer save DEBUG filename: C:\Users\camer\Documents\Desktop\Worx 2\Models\original_state.json, data type: 05/21/2022 22:45:18 MainProcess _training_0 serializer _check_extension DEBUG Original filename: 'C:\Users\camer\Documents\Desktop\Worx 2\Models\original_state.json', final filename: 'C:\Users\camer\Documents\Desktop\Worx 2\Models\original_state.json' 05/21/2022 22:45:18 MainProcess _training_0 serializer marshal DEBUG data type: 05/21/2022 22:45:18 MainProcess _training_0 serializer marshal DEBUG returned data type: 05/21/2022 22:45:18 MainProcess _training_0 _base save DEBUG Saved State 05/21/2022 22:45:18 MainProcess _training_0 _base _save INFO [Saved models] - Average loss since last save: face_a: 0.01650, face_b: 0.02555 05/21/2022 22:47:31 MainProcess _training_0 _base generate_preview DEBUG Generating preview 05/21/2022 22:47:31 MainProcess _training_0 _base compile_sample DEBUG Compiling samples: (side: 'a', samples: 14) 05/21/2022 22:47:31 MainProcess _training_0 _base compile_sample DEBUG Compiling samples: (side: 'b', samples: 14) 05/21/2022 22:47:31 MainProcess _training_0 _base show_sample DEBUG Showing sample 05/21/2022 22:47:31 MainProcess _training_0 _base _get_predictions DEBUG Getting Predictions 05/21/2022 22:47:31 MainProcess _training_0 _base _get_predictions DEBUG Returning predictions: {'a_a': (14, 64, 64, 3), 'b_b': (14, 64, 64, 3), 'a_b': (14, 64, 64, 3), 'b_a': (14, 64, 64, 3)} 05/21/2022 22:47:31 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)]) 05/21/2022 22:47:31 MainProcess _training_0 _base _process_full DEBUG full_size: 384, prediction_size: 64, color: (0, 0, 255) 05/21/2022 22:47:31 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 384, 384, 3), target_size: 72, scale: 0.1875) 05/21/2022 22:47:31 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 72, 72, 3)) 05/21/2022 22:47:31 MainProcess _training_0 _base _process_full DEBUG Overlayed background. Shape: (14, 72, 72, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _compile_masked DEBUG masked shapes: [(14, 64, 64, 3), (14, 64, 64, 3), (14, 64, 64, 3)] 05/21/2022 22:47:32 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 72, 72, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 72, 72, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 72, 72, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _get_headers DEBUG side: 'a', width: 72 05/21/2022 22:47:32 MainProcess _training_0 _base _get_headers DEBUG height: 16, total_width: 216 05/21/2022 22:47:32 MainProcess _training_0 _base _get_headers DEBUG texts: ['Original (A)', 'Original > Original', 'Original > Swap'], text_sizes: [(41, 6), (66, 6), (58, 6)], text_x: [15, 75, 151], text_y: 11 05/21/2022 22:47:32 MainProcess _training_0 _base _get_headers DEBUG header_box.shape: (16, 216, 3) 05/21/2022 22:47:32 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)]) 05/21/2022 22:47:32 MainProcess _training_0 _base _process_full DEBUG full_size: 384, prediction_size: 64, color: (0, 0, 255) 05/21/2022 22:47:32 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 384, 384, 3), target_size: 72, scale: 0.1875) 05/21/2022 22:47:32 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 72, 72, 3)) 05/21/2022 22:47:32 MainProcess _training_0 _base _process_full DEBUG Overlayed background. Shape: (14, 72, 72, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _compile_masked DEBUG masked shapes: [(14, 64, 64, 3), (14, 64, 64, 3), (14, 64, 64, 3)] 05/21/2022 22:47:32 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 72, 72, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 72, 72, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 72, 72, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _get_headers DEBUG side: 'b', width: 72 05/21/2022 22:47:32 MainProcess _training_0 _base _get_headers DEBUG height: 16, total_width: 216 05/21/2022 22:47:32 MainProcess _training_0 _base _get_headers DEBUG texts: ['Swap (B)', 'Swap > Swap', 'Swap > Original'], text_sizes: [(34, 6), (50, 6), (58, 6)], text_x: [19, 83, 151], text_y: 11 05/21/2022 22:47:32 MainProcess _training_0 _base _get_headers DEBUG header_box.shape: (16, 216, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _duplicate_headers DEBUG side: a header.shape: (16, 216, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _duplicate_headers DEBUG side: b header.shape: (16, 216, 3) 05/21/2022 22:47:32 MainProcess _training_0 _base _stack_images DEBUG Stack images 05/21/2022 22:47:32 MainProcess _training_0 _base get_transpose_axes DEBUG Even number of images to stack 05/21/2022 22:47:32 MainProcess _training_0 _base _stack_images DEBUG Stacked images 05/21/2022 22:47:32 MainProcess _training_0 _base show_sample DEBUG Compiled sample 05/21/2022 22:47:32 MainProcess _training_0 train _show DEBUG Updating preview: (name: Training - 'S': Save Now. 'R': Refresh Preview. 'M': Toggle Mask. 'ENTER': Save and Quit) 05/21/2022 22:47:32 MainProcess _training_0 train _show DEBUG Generating preview for GUI 05/21/2022 22:47:32 MainProcess _training_0 train _show DEBUG Generated preview for GUI: '.gui_training_preview.jpg' 05/21/2022 22:47:32 MainProcess _training_0 train _show DEBUG Updated preview: (name: Training - 'S': Save Now. 'R': Refresh Preview. 'M': Toggle Mask. 'ENTER': Save and Quit) 05/21/2022 22:47:32 MainProcess _training_0 train _run_training_cycle DEBUG Save Iteration: (iteration: 312750 05/21/2022 22:47:32 MainProcess _training_0 _base _save DEBUG Backing up and saving models 05/21/2022 22:47:32 MainProcess _training_0 _base _get_save_averages DEBUG Getting save averages 05/21/2022 22:47:32 MainProcess _training_0 _base _get_save_averages DEBUG Average losses since last save: [0.016150376942008732, 0.025526697732508184] 05/21/2022 22:47:32 MainProcess _training_0 _base _should_backup DEBUG Should backup: False 05/21/2022 22:47:33 MainProcess _training_0 _base save DEBUG Saving State 05/21/2022 22:47:33 MainProcess _training_0 serializer save DEBUG filename: C:\Users\camer\Documents\Desktop\Worx 2\Models\original_state.json, data type: 05/21/2022 22:47:33 MainProcess _training_0 serializer _check_extension DEBUG Original filename: 'C:\Users\camer\Documents\Desktop\Worx 2\Models\original_state.json', final filename: 'C:\Users\camer\Documents\Desktop\Worx 2\Models\original_state.json' 05/21/2022 22:47:33 MainProcess _training_0 serializer marshal DEBUG data type: 05/21/2022 22:47:33 MainProcess _training_0 serializer marshal DEBUG returned data type: 05/21/2022 22:47:33 MainProcess _training_0 _base save DEBUG Saved State 05/21/2022 22:47:33 MainProcess _training_0 _base _save INFO [Saved models] - Average loss since last save: face_a: 0.01615, face_b: 0.02553 05/21/2022 22:49:05 MainProcess _training_0 multithreading run DEBUG Error in thread (_training_0): [Errno 22] Invalid argument 05/21/2022 22:49:06 MainProcess MainThread train _monitor DEBUG Thread error detected 05/21/2022 22:49:06 MainProcess MainThread train _monitor DEBUG Closed Monitor 05/21/2022 22:49:06 MainProcess MainThread train _end_thread DEBUG Ending Training thread 05/21/2022 22:49:06 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting... 05/21/2022 22:49:06 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training' 05/21/2022 22:49:06 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training_0' 05/21/2022 22:49:06 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training_0' Traceback (most recent call last): File "C:\Users\camer\faceswap\lib\cli\launcher.py", line 182, in execute_script process.process() File "C:\Users\camer\faceswap\scripts\train.py", line 190, in process self._end_thread(thread, err) File "C:\Users\camer\faceswap\scripts\train.py", line 230, in _end_thread thread.join() File "C:\Users\camer\faceswap\lib\multithreading.py", line 121, in join raise thread.err[1].with_traceback(thread.err[2]) File "C:\Users\camer\faceswap\lib\multithreading.py", line 37, in run self._target(*self._args, **self._kwargs) File "C:\Users\camer\faceswap\scripts\train.py", line 252, in _training raise err File "C:\Users\camer\faceswap\scripts\train.py", line 242, in _training self._run_training_cycle(model, trainer) File "C:\Users\camer\faceswap\scripts\train.py", line 327, in _run_training_cycle trainer.train_one_step(viewer, timelapse) File "C:\Users\camer\faceswap\plugins\train\trainer\_base.py", line 225, in train_one_step self._print_loss(loss) File "C:\Users\camer\faceswap\plugins\train\trainer\_base.py", line 314, in _print_loss print(f"\r{output}", end="") OSError: [Errno 22] Invalid argument ============ System Information ============ encoding: cp1252 git_branch: master git_commits: c2595c4 bugfix - add missing mask key to alignments on legacy update gpu_cuda: 11.5 gpu_cudnn: No global version found. Check Conda packages for Conda cuDNN gpu_devices: GPU_0: NVIDIA GeForce GTX 1080 gpu_devices_active: GPU_0 gpu_driver: 472.39 gpu_vram: GPU_0: 8192MB os_machine: AMD64 os_platform: Windows-10-10.0.19044-SP0 os_release: 10 py_command: C:\Users\camer\faceswap\faceswap.py train -A C:/Users/camer/Documents/Desktop/Worx 2/Sorted A -B C:/Users/camer/Documents/Desktop/Worx 2/Sorted (B) -m C:/Users/camer/Documents/Desktop/Worx 2/Models -t original -bs 16 -it 1000000 -s 250 -ss 25000 -ps 100 -L INFO -gui py_conda_version: conda 4.12.0 py_implementation: CPython py_version: 3.9.12 py_virtual_env: True sys_cores: 8 sys_processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel sys_ram: Total: 32712MB, Available: 19316MB, Used: 13395MB, Free: 19316MB =============== Pip Packages =============== absl-py==1.0.0 astunparse==1.6.3 cachetools==5.1.0 certifi==2022.5.18.1 charset-normalizer==2.0.12 colorama @ file:///tmp/build/80754af9/colorama_1607707115595/work cycler @ file:///tmp/build/80754af9/cycler_1637851556182/work fastcluster @ file:///D:/bld/fastcluster_1649783471014/work ffmpy==0.2.3 flatbuffers==2.0 fonttools==4.25.0 gast==0.5.3 google-auth==2.6.6 google-auth-oauthlib==0.4.6 google-pasta==0.2.0 grpcio==1.46.1 h5py==3.6.0 idna==3.3 imageio @ file:///tmp/build/80754af9/imageio_1617700267927/work imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1649960641006/work importlib-metadata==4.11.3 joblib @ file:///tmp/build/80754af9/joblib_1635411271373/work keras==2.8.0 Keras-Preprocessing==1.1.2 kiwisolver @ file:///C:/ci/kiwisolver_1644962577370/work libclang==14.0.1 Markdown==3.3.7 matplotlib @ file:///C:/ci/matplotlib-suite_1647423638658/work mkl-fft==1.3.1 mkl-random @ file:///C:/ci/mkl_random_1626186184308/work mkl-service==2.4.0 munkres==1.1.4 numpy @ file:///C:/ci/numpy_and_numpy_base_1652784039997/work nvidia-ml-py==11.510.69 oauthlib==3.2.0 opencv-python==4.5.5.64 opt-einsum==3.3.0 packaging @ file:///tmp/build/80754af9/packaging_1637314298585/work Pillow==9.0.1 protobuf==3.20.1 psutil @ file:///C:/ci/psutil_1612298199233/work pyasn1==0.4.8 pyasn1-modules==0.2.8 pyparsing @ file:///tmp/build/80754af9/pyparsing_1635766073266/work python-dateutil @ file:///tmp/build/80754af9/python-dateutil_1626374649649/work pywin32==302 requests==2.27.1 requests-oauthlib==1.3.1 rsa==4.8 scikit-learn @ file:///C:/ci/scikit-learn_1642617276183/work scipy @ file:///C:/ci/scipy_1641555170412/work sip==4.19.13 six @ file:///tmp/build/80754af9/six_1644875935023/work tensorboard==2.8.0 tensorboard-data-server==0.6.1 tensorboard-plugin-wit==1.8.1 tensorflow-estimator==2.8.0 tensorflow-gpu==2.8.1 tensorflow-io-gcs-filesystem==0.26.0 termcolor==1.1.0 threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work tornado @ file:///C:/ci/tornado_1606924294691/work tqdm @ file:///C:/ci/tqdm_1650636210717/work typing_extensions==4.2.0 urllib3==1.26.9 Werkzeug==2.1.2 wincertstore==0.2 wrapt==1.14.1 zipp==3.8.0 ============== Conda Packages ============== # packages in environment at C:\Users\camer\anaconda3\envs\faceswap: # # Name Version Build Channel absl-py 1.0.0 pypi_0 pypi astunparse 1.6.3 pypi_0 pypi blas 1.0 mkl brotli 1.0.9 ha925a31_2 ca-certificates 2022.5.18.1 h5b45459_0 conda-forge cachetools 5.1.0 pypi_0 pypi certifi 2022.5.18.1 py39hcbf5309_0 conda-forge charset-normalizer 2.0.12 pypi_0 pypi colorama 0.4.4 pyhd3eb1b0_0 cudatoolkit 11.2.2 h933977f_10 conda-forge cudnn 8.1.0.77 h3e0f4f4_0 conda-forge cycler 0.11.0 pyhd3eb1b0_0 fastcluster 1.2.6 py39h2e25243_1 conda-forge ffmpeg 4.3.1 ha925a31_0 conda-forge ffmpy 0.2.3 pypi_0 pypi flatbuffers 2.0 pypi_0 pypi fonttools 4.25.0 pyhd3eb1b0_0 freetype 2.10.4 hd328e21_0 gast 0.5.3 pypi_0 pypi git 2.34.1 haa95532_0 google-auth 2.6.6 pypi_0 pypi google-auth-oauthlib 0.4.6 pypi_0 pypi google-pasta 0.2.0 pypi_0 pypi grpcio 1.46.1 pypi_0 pypi h5py 3.6.0 pypi_0 pypi icc_rt 2019.0.0 h0cc432a_1 icu 58.2 ha925a31_3 idna 3.3 pypi_0 pypi imageio 2.9.0 pyhd3eb1b0_0 imageio-ffmpeg 0.4.7 pyhd8ed1ab_0 conda-forge importlib-metadata 4.11.3 pypi_0 pypi intel-openmp 2021.4.0 haa95532_3556 joblib 1.1.0 pyhd3eb1b0_0 jpeg 9e h2bbff1b_0 keras 2.8.0 pypi_0 pypi keras-preprocessing 1.1.2 pypi_0 pypi kiwisolver 1.3.2 py39hd77b12b_0 libclang 14.0.1 pypi_0 pypi libpng 1.6.37 h2a8f88b_0 libtiff 4.2.0 he0120a3_1 libwebp 1.2.2 h2bbff1b_0 lz4-c 1.9.3 h2bbff1b_1 markdown 3.3.7 pypi_0 pypi matplotlib 3.5.1 py39haa95532_1 matplotlib-base 3.5.1 py39hd77b12b_1 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 munkres 1.1.4 py_0 numpy 1.22.3 py39h7a0a035_0 numpy-base 1.22.3 py39hca35cd5_0 nvidia-ml-py 11.510.69 pypi_0 pypi oauthlib 3.2.0 pypi_0 pypi opencv-python 4.5.5.64 pypi_0 pypi openssl 1.1.1o h8ffe710_0 conda-forge opt-einsum 3.3.0 pypi_0 pypi packaging 21.3 pyhd3eb1b0_0 pillow 9.0.1 py39hdc2b20a_0 pip 21.2.4 py39haa95532_0 protobuf 3.20.1 pypi_0 pypi psutil 5.8.0 py39h2bbff1b_1 pyasn1 0.4.8 pypi_0 pypi pyasn1-modules 0.2.8 pypi_0 pypi pyparsing 3.0.4 pyhd3eb1b0_0 pyqt 5.9.2 py39hd77b12b_6 python 3.9.12 h6244533_0 python-dateutil 2.8.2 pyhd3eb1b0_0 python_abi 3.9 2_cp39 conda-forge pywin32 302 py39h2bbff1b_2 qt 5.9.7 vc14h73c81de_0 requests 2.27.1 pypi_0 pypi requests-oauthlib 1.3.1 pypi_0 pypi rsa 4.8 pypi_0 pypi scikit-learn 1.0.2 py39hf11a4ad_1 scipy 1.7.3 py39h0a974cb_0 setuptools 61.2.0 py39haa95532_0 sip 4.19.13 py39hd77b12b_0 six 1.16.0 pyhd3eb1b0_1 sqlite 3.38.3 h2bbff1b_0 tensorboard 2.8.0 pypi_0 pypi tensorboard-data-server 0.6.1 pypi_0 pypi tensorboard-plugin-wit 1.8.1 pypi_0 pypi tensorflow-estimator 2.8.0 pypi_0 pypi tensorflow-gpu 2.8.1 pypi_0 pypi tensorflow-io-gcs-filesystem 0.26.0 pypi_0 pypi termcolor 1.1.0 pypi_0 pypi threadpoolctl 2.2.0 pyh0d69192_0 tk 8.6.11 h2bbff1b_1 tornado 6.1 py39h2bbff1b_0 tqdm 4.64.0 py39haa95532_0 typing-extensions 4.2.0 pypi_0 pypi tzdata 2022a hda174b7_0 urllib3 1.26.9 pypi_0 pypi vc 14.2 h21ff451_1 vs2015_runtime 14.27.29016 h5e58377_2 werkzeug 2.1.2 pypi_0 pypi wheel 0.37.1 pyhd3eb1b0_0 wincertstore 0.2 py39haa95532_2 wrapt 1.14.1 pypi_0 pypi xz 5.2.5 h8cc25b3_1 zipp 3.8.0 pypi_0 pypi zlib 1.2.12 h8cc25b3_2 zstd 1.5.2 h19a0ad4_0 =============== State File ================= { "name": "original", "sessions": { "1": { "timestamp": 1651944435.8638968, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 63000, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "2": { "timestamp": 1651961544.9597995, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 26250, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "3": { "timestamp": 1651969329.5357494, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 67500, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "4": { "timestamp": 1651987595.3865733, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 155250, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "5": { "timestamp": 1652030407.1559572, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 10500, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "6": { "timestamp": 1652038917.0331426, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 119500, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "7": { "timestamp": 1652071437.2549534, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 250, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "8": { "timestamp": 1652111418.519775, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 30250, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "9": { "timestamp": 1652124292.0861027, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 550250, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "10": { "timestamp": 1652538975.7679245, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 149500, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "11": { "timestamp": 1652580065.0160604, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 160250, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "12": { "timestamp": 1652671090.2125194, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 257750, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "13": { "timestamp": 1652748823.934612, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 15500, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "14": { "timestamp": 1652771726.9681857, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 72000, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "15": { "timestamp": 1652824107.496356, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 237250, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "16": { "timestamp": 1653081307.0370674, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 24750, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } }, "17": { "timestamp": 1653087987.2206154, "no_logs": false, "loss_names": [ "total", "face_a", "face_b" ], "batchsize": 16, "iterations": 312750, "config": { "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "nan_protection": true, "convert_batchsize": 16, "eye_multiplier": 3, "mouth_multiplier": 2 } } }, "lowest_avg_loss": { "a": 0.016062058884650468, "b": 0.024901844017207624 }, "iterations": 2252500, "config": { "centering": "face", "coverage": 87.5, "optimizer": "adam", "learning_rate": 5e-05, "epsilon_exponent": -7, "allow_growth": false, "mixed_precision": false, "nan_protection": true, "convert_batchsize": 16, "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, "lowmem": false } } ================= 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: False [align.fan] batch-size: 12 [detect.cv2_dnn] confidence: 50 [detect.mtcnn] minsize: 20 scalefactor: 0.709 batch-size: 8 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 weights: faceswap include_ears: False include_hair: False include_glasses: True [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: -7 reflect_padding: False allow_growth: False mixed_precision: False nan_protection: True 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.phaze_a] output_size: 128 shared_fc: none enable_gblock: True split_fc: True split_gblock: False split_decoders: False enc_architecture: fs_original enc_scaling: 40 enc_load_weights: True bottleneck_type: dense bottleneck_norm: none bottleneck_size: 1024 bottleneck_in_encoder: True fc_depth: 1 fc_min_filters: 1024 fc_max_filters: 1024 fc_dimensions: 4 fc_filter_slope: -0.5 fc_dropout: 0.0 fc_upsampler: upsample2d fc_upsamples: 1 fc_upsample_filters: 512 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: subpixel dec_norm: none dec_min_filters: 64 dec_max_filters: 512 dec_filter_slope: -0.45 dec_res_blocks: 1 dec_output_kernel: 5 dec_gaussian: True dec_skip_last_residual: True freeze_layers: keras_encoder load_layers: encoder fs_original_depth: 4 fs_original_min_filters: 128 fs_original_max_filters: 1024 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 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