Error starting training: TypeError: 'NoneType' object is not subscriptable

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bist
Posts: 3
Joined: Fri Feb 02, 2024 3:11 pm
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Error starting training: TypeError: 'NoneType' object is not subscriptable

Post by bist »

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02/02/2024 23:02:43 CRITICAL An unexpected crash has occurred. Crash report written to 'C:\Users\90363\faceswap\crash_report.2024.02.02.230238914277.log'. You MUST provide this file if seeking assistance. Please verify you are running the latest version of faceswap before reporting





02/02/2024 23:00:58 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _get_headers                   DEBUG    side: 'a', width: 72
02/02/2024 23:00:58 MainProcess     _training                      _base           _get_headers                   DEBUG    height: 16, total_width: 216
02/02/2024 23:00:58 MainProcess     _training                      _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
02/02/2024 23:00:58 MainProcess     _training                      _base           _get_headers                   DEBUG    header_box.shape: (16, 216, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _to_full_frame                 DEBUG    side: 'b', number of sample arrays: 3, prediction.shapes: [(14, 64, 64, 3), (14, 64, 64, 3)])
02/02/2024 23:00:58 MainProcess     _training                      _base           _process_full                  DEBUG    full_size: 74, prediction_size: 64, color: (0.0, 0.0, 1.0)
02/02/2024 23:00:58 MainProcess     _training                      _base           _resize_sample                 DEBUG    Resizing sample: (side: 'b', sample.shape: (14, 74, 74, 3), target_size: 72, scale: 0.972972972972973)
02/02/2024 23:00:58 MainProcess     _training                      _base           _resize_sample                 DEBUG    Resized sample: (side: 'b' shape: (14, 72, 72, 3))
02/02/2024 23:00:58 MainProcess     _training                      _base           _process_full                  DEBUG    Overlayed background. Shape: (14, 72, 72, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _compile_masked                DEBUG    masked shapes: [(14, 64, 64, 3), (14, 64, 64, 3), (14, 64, 64, 3)]
02/02/2024 23:00:58 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _get_headers                   DEBUG    side: 'b', width: 72
02/02/2024 23:00:58 MainProcess     _training                      _base           _get_headers                   DEBUG    height: 16, total_width: 216
02/02/2024 23:00:58 MainProcess     _training                      _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
02/02/2024 23:00:58 MainProcess     _training                      _base           _get_headers                   DEBUG    header_box.shape: (16, 216, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _duplicate_headers             DEBUG    side: a header.shape: (16, 216, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _duplicate_headers             DEBUG    side: b header.shape: (16, 216, 3)
02/02/2024 23:00:58 MainProcess     _training                      _base           _stack_images                  DEBUG    Stack images
02/02/2024 23:00:58 MainProcess     _training                      _base           get_transpose_axes             DEBUG    Even number of images to stack
02/02/2024 23:00:58 MainProcess     _training                      _base           _stack_images                  DEBUG    Stacked images
02/02/2024 23:00:58 MainProcess     _training                      _base           _compile_preview               DEBUG    Compiled sample
02/02/2024 23:00:58 MainProcess     _training                      _base           output_timelapse               DEBUG    Created time-lapse: 'D:\D\1706886058.jpg'
02/02/2024 23:00:58 MainProcess     _training                      train           _run_training_cycle            DEBUG    Saving (save_iterations: True, save_now: False) Iteration: (iteration: 1)
02/02/2024 23:00:58 MainProcess     _training                      io              save                           DEBUG    Backing up and saving models
02/02/2024 23:00:58 MainProcess     _training                      io              _get_save_averages             DEBUG    Getting save averages
02/02/2024 23:00:58 MainProcess     _training                      io              _get_save_averages             DEBUG    Average losses since last save: [0.3055972158908844, 0.30632156133651733]
02/02/2024 23:00:58 MainProcess     _training                      io              _should_backup                 DEBUG    Set initial save iteration loss average for 'a': 0.3055972158908844
02/02/2024 23:00:58 MainProcess     _training                      io              _should_backup                 DEBUG    Set initial save iteration loss average for 'b': 0.30632156133651733
02/02/2024 23:00:58 MainProcess     _training                      io              _should_backup                 DEBUG    Updated lowest historical save iteration averages from: {'a': 0.3055972158908844, 'b': 0.30632156133651733} to: {'a': 0.3055972158908844, 'b': 0.30632156133651733}
02/02/2024 23:00:58 MainProcess     _training                      io              _should_backup                 DEBUG    Should backup: True
02/02/2024 23:00:58 MainProcess     _training                      attrs           create                         DEBUG    Creating converter from 5 to 3
02/02/2024 23:00:59 MainProcess     _training                      model           save                           DEBUG    Saving State
02/02/2024 23:00:59 MainProcess     _training                      serializer      save                           DEBUG    filename: D:\C\original_state.json, data type: <class 'dict'>
02/02/2024 23:00:59 MainProcess     _training                      serializer      _check_extension               DEBUG    Original filename: 'D:\C\original_state.json', final filename: 'D:\C\original_state.json'
02/02/2024 23:00:59 MainProcess     _training                      serializer      marshal                        DEBUG    data type: <class 'dict'>
02/02/2024 23:00:59 MainProcess     _training                      serializer      marshal                        DEBUG    returned data type: <class 'bytes'>
02/02/2024 23:00:59 MainProcess     _training                      model           save                           DEBUG    Saved State
02/02/2024 23:00:59 MainProcess     _training                      io              save                           INFO     [Saved model] - Average loss since last save: face_a: 0.30560, face_b: 0.30632
02/02/2024 23:00:59 MainProcess     _training                      generator       generate_preview               DEBUG    Generating preview (is_timelapse: False)
02/02/2024 23:00:59 MainProcess     _training                      generator       generate_preview               DEBUG    Generated samples: is_timelapse: False, images: {'feed': {'a': (14, 64, 64, 3), 'b': (14, 64, 64, 3)}, 'samples': {'a': (14, 74, 74, 3), 'b': (14, 74, 74, 3)}, 'sides': {'a': (14, 64, 64, 1), 'b': (14, 64, 64, 1)}}
02/02/2024 23:00:59 MainProcess     _training                      generator       compile_sample                 DEBUG    Compiling samples: (side: 'a', samples: 14)
02/02/2024 23:00:59 MainProcess     _training                      generator       compile_sample                 DEBUG    Compiling samples: (side: 'b', samples: 14)
02/02/2024 23:00:59 MainProcess     _training                      generator       compile_sample                 DEBUG    Compiled Samples: {'a': [(14, 64, 64, 3), (14, 74, 74, 3), (14, 64, 64, 1)], 'b': [(14, 64, 64, 3), (14, 74, 74, 3), (14, 64, 64, 1)]}
02/02/2024 23:00:59 MainProcess     _training                      _base           show_sample                    DEBUG    Showing sample
02/02/2024 23:00:59 MainProcess     _training                      _base           _get_predictions               DEBUG    Getting Predictions
02/02/2024 23:01:00 MainProcess     _training                      _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)}
02/02/2024 23:01:00 MainProcess     _training                      _base           _to_full_frame                 DEBUG    side: 'a', number of sample arrays: 3, prediction.shapes: [(14, 64, 64, 3), (14, 64, 64, 3)])
02/02/2024 23:01:00 MainProcess     _training                      _base           _process_full                  DEBUG    full_size: 74, prediction_size: 64, color: (0.0, 0.0, 1.0)
02/02/2024 23:01:00 MainProcess     _training                      _base           _resize_sample                 DEBUG    Resizing sample: (side: 'a', sample.shape: (14, 74, 74, 3), target_size: 72, scale: 0.972972972972973)
02/02/2024 23:01:00 MainProcess     _training                      _base           _resize_sample                 DEBUG    Resized sample: (side: 'a' shape: (14, 72, 72, 3))
02/02/2024 23:01:00 MainProcess     _training                      _base           _process_full                  DEBUG    Overlayed background. Shape: (14, 72, 72, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _compile_masked                DEBUG    masked shapes: [(14, 64, 64, 3), (14, 64, 64, 3), (14, 64, 64, 3)]
02/02/2024 23:01:00 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _get_headers                   DEBUG    side: 'a', width: 72
02/02/2024 23:01:00 MainProcess     _training                      _base           _get_headers                   DEBUG    height: 16, total_width: 216
02/02/2024 23:01:00 MainProcess     _training                      _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
02/02/2024 23:01:00 MainProcess     _training                      _base           _get_headers                   DEBUG    header_box.shape: (16, 216, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _to_full_frame                 DEBUG    side: 'b', number of sample arrays: 3, prediction.shapes: [(14, 64, 64, 3), (14, 64, 64, 3)])
02/02/2024 23:01:00 MainProcess     _training                      _base           _process_full                  DEBUG    full_size: 74, prediction_size: 64, color: (0.0, 0.0, 1.0)
02/02/2024 23:01:00 MainProcess     _training                      _base           _resize_sample                 DEBUG    Resizing sample: (side: 'b', sample.shape: (14, 74, 74, 3), target_size: 72, scale: 0.972972972972973)
02/02/2024 23:01:00 MainProcess     _training                      _base           _resize_sample                 DEBUG    Resized sample: (side: 'b' shape: (14, 72, 72, 3))
02/02/2024 23:01:00 MainProcess     _training                      _base           _process_full                  DEBUG    Overlayed background. Shape: (14, 72, 72, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _compile_masked                DEBUG    masked shapes: [(14, 64, 64, 3), (14, 64, 64, 3), (14, 64, 64, 3)]
02/02/2024 23:01:00 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _overlay_foreground            DEBUG    Overlayed foreground. Shape: (14, 72, 72, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _get_headers                   DEBUG    side: 'b', width: 72
02/02/2024 23:01:00 MainProcess     _training                      _base           _get_headers                   DEBUG    height: 16, total_width: 216
02/02/2024 23:01:00 MainProcess     _training                      _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
02/02/2024 23:01:00 MainProcess     _training                      _base           _get_headers                   DEBUG    header_box.shape: (16, 216, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _duplicate_headers             DEBUG    side: a header.shape: (16, 216, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _duplicate_headers             DEBUG    side: b header.shape: (16, 216, 3)
02/02/2024 23:01:00 MainProcess     _training                      _base           _stack_images                  DEBUG    Stack images
02/02/2024 23:01:00 MainProcess     _training                      _base           get_transpose_axes             DEBUG    Even number of images to stack
02/02/2024 23:01:00 MainProcess     _training                      _base           _stack_images                  DEBUG    Stacked images
02/02/2024 23:01:00 MainProcess     _training                      _base           _compile_preview               DEBUG    Compiled sample
02/02/2024 23:01:00 MainProcess     _training                      train           _show                          DEBUG    Updating preview: (name: Training - 'S': Save Now. 'R': Refresh Preview. 'M': Toggle Mask. 'F': Toggle Screen Fit-Actual Size. 'ENTER': Save and Quit)
02/02/2024 23:01:00 MainProcess     _training                      train           _show                          DEBUG    Generating preview for GUI
02/02/2024 23:01:00 MainProcess     _training                      train           _show                          DEBUG    Generated preview for GUI: 'C:\Users\90363\faceswap\lib\gui\.cache\preview\.gui_training_preview.png'
02/02/2024 23:01:00 MainProcess     _training                      train           _show                          DEBUG    Updated preview: (name: Training - 'S': Save Now. 'R': Refresh Preview. 'M': Toggle Mask. 'F': Toggle Screen Fit-Actual Size. 'ENTER': Save and Quit)
02/02/2024 23:01:00 MainProcess     _training                      train           _run_training_cycle            INFO     [Preview Updated]
02/02/2024 23:02:24 MainProcess     _run                           cache           cache_metadata                 VERBOSE  Cache filled: 'D:\A'
02/02/2024 23:02:38 MainProcess     _training                      _base           output_timelapse               DEBUG    Ouputting time-lapse
02/02/2024 23:02:38 MainProcess     _training                      _base           output_timelapse               DEBUG    Getting time-lapse samples
02/02/2024 23:02:38 MainProcess     _training                      generator       generate_preview               DEBUG    Generating preview (is_timelapse: True)
02/02/2024 23:02:38 MainProcess     _training                      multithreading  check_and_raise_error          DEBUG    Thread error caught: [(<class 'TypeError'>, TypeError("'NoneType' object is not subscriptable"), <traceback object at 0x000001D716E3E580>)]
02/02/2024 23:02:38 MainProcess     _training                      multithreading  run                            DEBUG    Error in thread (_training): 'NoneType' object is not subscriptable
02/02/2024 23:02:38 MainProcess     MainThread                     train           _monitor                       DEBUG    Thread error detected
02/02/2024 23:02:38 MainProcess     MainThread                     train           _monitor                       DEBUG    Closed Monitor
02/02/2024 23:02:38 MainProcess     MainThread                     train           _end_thread                    DEBUG    Ending Training thread
02/02/2024 23:02:38 MainProcess     MainThread                     train           _end_thread                    CRITICAL Error caught! Exiting...
02/02/2024 23:02:38 MainProcess     MainThread                     multithreading  join                           DEBUG    Joining Threads: '_training'
02/02/2024 23:02:38 MainProcess     MainThread                     multithreading  join                           DEBUG    Joining Thread: '_training'
02/02/2024 23:02:38 MainProcess     MainThread                     multithreading  join                           ERROR    Caught exception in thread: '_training'
Traceback (most recent call last):
  File "C:\Users\90363\faceswap\lib\cli\launcher.py", line 225, in execute_script
    process.process()
  File "C:\Users\90363\faceswap\scripts\train.py", line 209, in process
    self._end_thread(thread, err)
  File "C:\Users\90363\faceswap\scripts\train.py", line 249, in _end_thread
    thread.join()
  File "C:\Users\90363\faceswap\lib\multithreading.py", line 224, in join
    raise thread.err[1].with_traceback(thread.err[2])
  File "C:\Users\90363\faceswap\lib\multithreading.py", line 100, in run
    self._target(*self._args, **self._kwargs)
  File "C:\Users\90363\faceswap\scripts\train.py", line 274, in _training
    raise err
  File "C:\Users\90363\faceswap\scripts\train.py", line 264, in _training
    self._run_training_cycle(model, trainer)
  File "C:\Users\90363\faceswap\scripts\train.py", line 352, in _run_training_cycle
    trainer.train_one_step(viewer, timelapse)
  File "C:\Users\90363\faceswap\plugins\train\trainer\_base.py", line 267, in train_one_step
    self._update_viewers(viewer, timelapse_kwargs)
  File "C:\Users\90363\faceswap\plugins\train\trainer\_base.py", line 373, in _update_viewers
    self._timelapse.output_timelapse(timelapse_kwargs)
  File "C:\Users\90363\faceswap\plugins\train\trainer\_base.py", line 881, in output_timelapse
    self._samples.images = self._feeder.generate_preview(is_timelapse=True)
  File "C:\Users\90363\faceswap\lib\training\generator.py", line 877, in generate_preview
    side_feed, side_samples = next(iterator[side])
  File "C:\Users\90363\faceswap\lib\multithreading.py", line 296, in iterator
    self.check_and_raise_error()
  File "C:\Users\90363\faceswap\lib\multithreading.py", line 173, in check_and_raise_error
    raise error[1].with_traceback(error[2])
  File "C:\Users\90363\faceswap\lib\multithreading.py", line 100, in run
    self._target(*self._args, **self._kwargs)
  File "C:\Users\90363\faceswap\lib\multithreading.py", line 279, in _run
    for item in self.generator(*self._gen_args, **self._gen_kwargs):
  File "C:\Users\90363\faceswap\lib\training\generator.py", line 217, in _minibatch
    retval = self._process_batch(img_paths)
  File "C:\Users\90363\faceswap\lib\training\generator.py", line 330, in _process_batch
    raw_faces, detected_faces = self._get_images_with_meta(filenames)
  File "C:\Users\90363\faceswap\lib\training\generator.py", line 241, in _get_images_with_meta
    raw_faces = self._face_cache.cache_metadata(filenames)
  File "C:\Users\90363\faceswap\lib\training\cache.py", line 246, in cache_metadata
    self._validate_version(meta, filename)
  File "C:\Users\90363\faceswap\lib\training\cache.py", line 306, in _validate_version
    alignment_version = png_meta["source"]["alignments_version"]
TypeError: 'NoneType' object is not subscriptable

============ System Information ============
backend:             nvidia
encoding:            cp936
git_branch:          master
git_commits:         dea021c bugfix - setup.py   - Install xorg-libxft for Linux users   - Force tensorflow-cpu from pip
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 GTX 1650
gpu_devices_active:  GPU_0
gpu_driver:          462.30
gpu_vram:            GPU_0: 4096MB (1075MB free)
os_machine:          AMD64
os_platform:         Windows-10-10.0.22621-SP0
os_release:          10
py_command:          C:\Users\90363\faceswap\faceswap.py train -A D:/A -B D:/B -m D:/C -t original -bs 14 -it 1000000 -D default -s 250 -ss 25000 -tia D:/A -tib D:/B -to D:/D -L INFO -gui
py_conda_version:    conda 24.1.0
py_implementation:   CPython
py_version:          3.10.13
py_virtual_env:      True
sys_cores:           8
sys_processor:       Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
sys_ram:             Total: 8072MB, Available: 1413MB, Used: 6658MB, Free: 1413MB

=============== Pip Packages ===============
absl-py==2.1.0
astunparse==1.6.3
cachetools==5.3.2
certifi==2024.2.2
charset-normalizer==3.3.2
colorama @ file:///C:/b/abs_a9ozq0l032/croot/colorama_1672387194846/work
contourpy @ file:///C:/b/abs_853rfy8zse/croot/contourpy_1700583617587/work
cycler @ file:///tmp/build/80754af9/cycler_1637851556182/work
fastcluster @ file:///D:/bld/fastcluster_1695650232190/work
ffmpy @ file:///home/conda/feedstock_root/build_artifacts/ffmpy_1659474992694/work
flatbuffers==23.5.26
fonttools==4.25.0
gast==0.4.0
google-auth==2.27.0
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.60.1
h5py==3.10.0
idna==3.6
imageio @ file:///C:/b/abs_3eijmwdodc/croot/imageio_1695996500830/work
imageio-ffmpeg==0.4.9
joblib @ file:///C:/b/abs_1anqjntpan/croot/joblib_1685113317150/work
keras==2.10.0
Keras-Preprocessing==1.1.2
kiwisolver @ file:///C:/b/abs_88mdhvtahm/croot/kiwisolver_1672387921783/work
libclang==16.0.6
Markdown==3.5.2
MarkupSafe==2.1.4
matplotlib @ file:///C:/b/abs_e26vnvd5s1/croot/matplotlib-suite_1698692153288/work
mkl-fft @ file:///C:/b/abs_19i1y8ykas/croot/mkl_fft_1695058226480/work
mkl-random @ file:///C:/b/abs_edwkj1_o69/croot/mkl_random_1695059866750/work
mkl-service==2.4.0
munkres==1.1.4
numexpr @ file:///C:/b/abs_5fucrty5dc/croot/numexpr_1696515448831/work
numpy @ file:///C:/b/abs_16b2j7ad8n/croot/numpy_and_numpy_base_1704311752418/work/dist/numpy-1.26.3-cp310-cp310-win_amd64.whl#sha256=e84057072c37569bd0e11652dc2a75980d4d360f2391adf6a29a2fb1622d20ff
nvidia-ml-py @ file:///home/conda/feedstock_root/build_artifacts/nvidia-ml-py_1698947663801/work
oauthlib==3.2.2
opencv-python==4.9.0.80
opt-einsum==3.3.0
packaging @ file:///C:/b/abs_28t5mcoltc/croot/packaging_1693575224052/work
Pillow @ file:///C:/b/abs_153xikw91n/croot/pillow_1695134603563/work
ply==3.11
protobuf==3.19.6
psutil @ file:///C:/Windows/Temp/abs_b2c2fd7f-9fd5-4756-95ea-8aed74d0039flsd9qufz/croots/recipe/psutil_1656431277748/work
pyasn1==0.5.1
pyasn1-modules==0.3.0
pyparsing @ file:///C:/Users/BUILDE~1/AppData/Local/Temp/abs_7f_7lba6rl/croots/recipe/pyparsing_1661452540662/work
PyQt5==5.15.10
PyQt5-sip @ file:///C:/b/abs_c0pi2mimq3/croot/pyqt-split_1698769125270/work/pyqt_sip
python-dateutil @ file:///tmp/build/80754af9/python-dateutil_1626374649649/work
pywin32==306
pywinpty @ file:///C:/ci_310/pywinpty_1644230983541/work/target/wheels/pywinpty-2.0.2-cp310-none-win_amd64.whl
requests==2.31.0
requests-oauthlib==1.3.1
rsa==4.9
scikit-learn @ file:///C:/b/abs_daon7wm2p4/croot/scikit-learn_1694788586973/work
scipy==1.11.4
sip @ file:///C:/b/abs_edevan3fce/croot/sip_1698675983372/work
six @ file:///tmp/build/80754af9/six_1644875935023/work
tensorboard==2.10.1
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow==2.10.1
tensorflow-estimator==2.10.0
tensorflow-io-gcs-filesystem==0.31.0
termcolor==2.4.0
threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work
tomli @ file:///C:/Windows/TEMP/abs_ac109f85-a7b3-4b4d-bcfd-52622eceddf0hy332ojo/croots/recipe/tomli_1657175513137/work
tornado @ file:///C:/b/abs_0cbrstidzg/croot/tornado_1696937003724/work
tqdm @ file:///C:/b/abs_f76j9hg7pv/croot/tqdm_1679561871187/work
typing_extensions==4.9.0
urllib3==2.2.0
Werkzeug==3.0.1
wrapt==1.16.0

============== Conda Packages ==============
# packages in environment at C:\Users\90363\MiniConda3\envs\faceswap:
#
# Name                    Version                   Build  Channel
absl-py                   2.1.0                    pypi_0    pypi
aom                       3.7.1                h63175ca_0    conda-forge
astunparse                1.6.3                    pypi_0    pypi
blas                      1.0                         mkl  
brotli                    1.0.9                h2bbff1b_7  
brotli-bin                1.0.9                h2bbff1b_7  
bzip2                     1.0.8                he774522_0  
ca-certificates           2023.12.12           haa95532_0  
cachetools                5.3.2                    pypi_0    pypi
certifi                   2024.2.2                 pypi_0    pypi
charset-normalizer        3.3.2                    pypi_0    pypi
colorama                  0.4.6           py310haa95532_0  
contourpy                 1.2.0           py310h59b6b97_0  
cudatoolkit               11.2.2              h7d7167e_12    conda-forge
cudnn                     8.1.0.77             h3e0f4f4_0    conda-forge
cycler                    0.11.0             pyhd3eb1b0_0  
dav1d                     1.2.1                hcfcfb64_0    conda-forge
expat                     2.5.0                h63175ca_1    conda-forge
fastcluster               1.2.6           py310hecd3228_3    conda-forge
ffmpeg                    6.1.0           gpl_h0859920_103    conda-forge
ffmpy                     0.3.0              pyhb6f538c_0    conda-forge
flatbuffers               23.5.26                  pypi_0    pypi
font-ttf-dejavu-sans-mono 2.37                 hab24e00_0    conda-forge
font-ttf-inconsolata      3.000                h77eed37_0    conda-forge
font-ttf-source-code-pro  2.038                h77eed37_0    conda-forge
font-ttf-ubuntu           0.83                 h77eed37_1    conda-forge
fontconfig                2.14.2               hbde0cde_0    conda-forge
fonts-conda-ecosystem     1                             0    conda-forge
fonts-conda-forge         1                             0    conda-forge
fonttools                 4.25.0             pyhd3eb1b0_0  
freetype                  2.12.1               ha860e81_0  
gast                      0.4.0                    pypi_0    pypi
giflib                    5.2.1                h8cc25b3_3  
git                       2.40.1               haa95532_1  
google-auth               2.27.0                   pypi_0    pypi
google-auth-oauthlib      0.4.6                    pypi_0    pypi
google-pasta              0.2.0                    pypi_0    pypi
grpcio                    1.60.1                   pypi_0    pypi
h5py                      3.10.0                   pypi_0    pypi
icc_rt                    2022.1.0             h6049295_2  
icu                       73.1                 h6c2663c_0  
idna                      3.6                      pypi_0    pypi
imageio                   2.31.4          py310haa95532_0  
imageio-ffmpeg            0.4.9                    pypi_0    pypi
intel-openmp              2023.1.0         h59b6b97_46320  
joblib                    1.2.0           py310haa95532_0  
jpeg                      9e                   h2bbff1b_1  
keras                     2.10.0                   pypi_0    pypi
keras-preprocessing       1.1.2                    pypi_0    pypi
kiwisolver                1.4.4           py310hd77b12b_0  
krb5                      1.20.1               h5b6d351_0  
lerc                      3.0                  hd77b12b_0  
libbrotlicommon           1.0.9                h2bbff1b_7  
libbrotlidec              1.0.9                h2bbff1b_7  
libbrotlienc              1.0.9                h2bbff1b_7  
libclang                  16.0.6                   pypi_0    pypi
libclang13                14.0.6          default_h8e68704_1  
libdeflate                1.17                 h2bbff1b_1  
libexpat                  2.5.0                h63175ca_1    conda-forge
libffi                    3.4.4                hd77b12b_0  
libiconv                  1.17                 hcfcfb64_2    conda-forge
libopus                   1.3.1                h8ffe710_1    conda-forge
libpng                    1.6.39               h8cc25b3_0  
libpq                     12.17                h906ac69_0  
libtiff                   4.5.1                hd77b12b_0  
libwebp                   1.3.2                hbc33d0d_0  
libwebp-base              1.3.2                h2bbff1b_0  
libxml2                   2.12.4               hc3477c8_1    conda-forge
libzlib                   1.2.13               hcfcfb64_5    conda-forge
libzlib-wapi              1.2.13               hcfcfb64_5    conda-forge
lz4-c                     1.9.4                h2bbff1b_0  
markdown                  3.5.2                    pypi_0    pypi
markupsafe                2.1.4                    pypi_0    pypi
matplotlib                3.8.0           py310haa95532_0  
matplotlib-base           3.8.0           py310h4ed8f06_0  
mkl                       2023.1.0         h6b88ed4_46358  
mkl-service               2.4.0           py310h2bbff1b_1  
mkl_fft                   1.3.8           py310h2bbff1b_0  
mkl_random                1.2.4           py310h59b6b97_0  
munkres                   1.1.4                      py_0  
numexpr                   2.8.7           py310h2cd9be0_0  
numpy                     1.26.3          py310h055cbcc_0  
numpy-base                1.26.3          py310h65a83cf_0  
nvidia-ml-py              12.535.133         pyhd8ed1ab_0    conda-forge
oauthlib                  3.2.2                    pypi_0    pypi
opencv-python             4.9.0.80                 pypi_0    pypi
openh264                  2.4.0                h63175ca_0    conda-forge
openssl                   3.2.1                hcfcfb64_0    conda-forge
opt-einsum                3.3.0                    pypi_0    pypi
packaging                 23.1            py310haa95532_0  
pillow                    9.4.0           py310hd77b12b_1  
pip                       23.3.1          py310haa95532_0  
ply                       3.11            py310haa95532_0  
protobuf                  3.19.6                   pypi_0    pypi
psutil                    5.9.0           py310h2bbff1b_0  
pyasn1                    0.5.1                    pypi_0    pypi
pyasn1-modules            0.3.0                    pypi_0    pypi
pyparsing                 3.0.9           py310haa95532_0  
pyqt                      5.15.10         py310hd77b12b_0  
pyqt5-sip                 12.13.0         py310h2bbff1b_0  
python                    3.10.13              he1021f5_0  
python-dateutil           2.8.2              pyhd3eb1b0_0  
python_abi                3.10                    2_cp310    conda-forge
pywin32                   306                      pypi_0    pypi
pywinpty                  2.0.2           py310h5da7b33_0  
qt-main                   5.15.2              h19c9488_10  
requests                  2.31.0                   pypi_0    pypi
requests-oauthlib         1.3.1                    pypi_0    pypi
rsa                       4.9                      pypi_0    pypi
scikit-learn              1.3.0           py310h4ed8f06_1  
scipy                     1.11.4          py310h309d312_0  
setuptools                68.2.2          py310haa95532_0  
sip                       6.7.12          py310hd77b12b_0  
six                       1.16.0             pyhd3eb1b0_1  
sqlite                    3.41.2               h2bbff1b_0  
svt-av1                   1.7.0                h63175ca_0    conda-forge
tbb                       2021.8.0             h59b6b97_0  
tensorboard               2.10.1                   pypi_0    pypi
tensorboard-data-server   0.6.1                    pypi_0    pypi
tensorboard-plugin-wit    1.8.1                    pypi_0    pypi
tensorflow                2.10.1                   pypi_0    pypi
tensorflow-estimator      2.10.0                   pypi_0    pypi
tensorflow-io-gcs-filesystem 0.31.0                   pypi_0    pypi
termcolor                 2.4.0                    pypi_0    pypi
threadpoolctl             2.2.0              pyh0d69192_0  
tk                        8.6.12               h2bbff1b_0  
tomli                     2.0.1           py310haa95532_0  
tornado                   6.3.3           py310h2bbff1b_0  
tqdm                      4.65.0          py310h9909e9c_0  
typing-extensions         4.9.0                    pypi_0    pypi
tzdata                    2023d                h04d1e81_0  
ucrt                      10.0.22621.0         h57928b3_0    conda-forge
urllib3                   2.2.0                    pypi_0    pypi
vc                        14.2                 h21ff451_1  
vc14_runtime              14.38.33130         h82b7239_18    conda-forge
vs2015_runtime            14.38.33130         hcb4865c_18    conda-forge
werkzeug                  3.0.1                    pypi_0    pypi
wheel                     0.41.2          py310haa95532_0  
winpty                    0.4.3                         4  
wrapt                     1.16.0                   pypi_0    pypi
x264                      1!164.3095           h8ffe710_2    conda-forge
x265                      3.5                  h2d74725_3    conda-forge
xz                        5.4.5                h8cc25b3_0  
zlib                      1.2.13               hcfcfb64_5    conda-forge
zlib-wapi                 1.2.13               hcfcfb64_5    conda-forge
zstd                      1.5.5                hd43e919_0  

=============== State File =================
{
  "name": "original",
  "sessions": {
    "1": {
      "timestamp": 1706886043.0229857,
      "no_logs": false,
      "loss_names": [
        "total",
        "face_a",
        "face_b"
      ],
      "batchsize": 14,
      "iterations": 1,
      "config": {
        "learning_rate": 5e-05,
        "epsilon_exponent": -7,
        "save_optimizer": "exit",
        "autoclip": false,
        "allow_growth": false,
        "mixed_precision": false,
        "nan_protection": true,
        "convert_batchsize": 16,
        "loss_function": "ssim",
        "loss_function_2": "mse",
        "loss_weight_2": 100,
        "loss_function_3": null,
        "loss_weight_3": 0,
        "loss_function_4": null,
        "loss_weight_4": 0,
        "mask_loss_function": "mse",
        "eye_multiplier": 3,
        "mouth_multiplier": 2
      }
    }
  },
  "lowest_avg_loss": {
    "a": 0.3055972158908844,
    "b": 0.30632156133651733
  },
  "iterations": 1,
  "mixed_precision_layers": [
    "conv_128_0_conv2d",
    "conv_128_0_leakyrelu",
    "conv_256_0_conv2d",
    "conv_256_0_leakyrelu",
    "conv_512_0_conv2d",
    "conv_512_0_leakyrelu",
    "conv_1024_0_conv2d",
    "conv_1024_0_leakyrelu",
    "flatten",
    "dense",
    "dense_1",
    "reshape",
    "upscale_512_0_conv2d_conv2d",
    "upscale_512_0_conv2d_leakyrelu",
    "upscale_512_0_pixelshuffler",
    "upscale_256_0_conv2d_conv2d",
    "upscale_256_0_conv2d_leakyrelu",
    "upscale_256_0_pixelshuffler",
    "upscale_128_0_conv2d_conv2d",
    "upscale_128_0_conv2d_leakyrelu",
    "upscale_128_0_pixelshuffler",
    "upscale_64_0_conv2d_conv2d",
    "upscale_64_0_conv2d_leakyrelu",
    "upscale_64_0_pixelshuffler",
    "face_out_a_0_conv2d",
    "upscale_256_1_conv2d_conv2d",
    "upscale_256_1_conv2d_leakyrelu",
    "upscale_256_1_pixelshuffler",
    "upscale_128_1_conv2d_conv2d",
    "upscale_128_1_conv2d_leakyrelu",
    "upscale_128_1_pixelshuffler",
    "upscale_64_1_conv2d_conv2d",
    "upscale_64_1_conv2d_leakyrelu",
    "upscale_64_1_pixelshuffler",
    "face_out_b_0_conv2d"
  ],
  "config": {
    "centering": "face",
    "coverage": 87.5,
    "optimizer": "adam",
    "learning_rate": 5e-05,
    "epsilon_exponent": -7,
    "save_optimizer": "exit",
    "lr_finder_iterations": 1000,
    "lr_finder_mode": "set",
    "lr_finder_strength": "default",
    "autoclip": false,
    "allow_growth": false,
    "mixed_precision": false,
    "nan_protection": true,
    "convert_batchsize": 16,
    "loss_function": "ssim",
    "loss_function_2": "mse",
    "loss_weight_2": 100,
    "loss_function_3": null,
    "loss_weight_3": 0,
    "loss_function_4": null,
    "loss_weight_4": 0,
    "mask_loss_function": "mse",
    "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.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.patch]
start_index:              0
index_offset:             0
number_padding:           6
include_filename:         True
face_index_location:      before
origin:                   bottom-left
empty_frames:             blank
json_output:              False
separate_mask:            False
bit_depth:                16
format:                   png
png_compress_level:       3
tiff_compression_method:  lzw

[writer.pillow]
format:                   png
draw_transparent:         False
separate_mask:            False
optimize:                 False
gif_interlace:            True
jpg_quality:              75
png_compress_level:       3
tif_compression:          tiff_deflate

--------- extract.ini ---------

[global]
allow_growth:             False
aligner_min_scale:        0.07
aligner_max_scale:        2.0
aligner_distance:         22.5
aligner_roll:             45.0
aligner_features:         True
filter_refeed:            True
save_filtered:            False
realign_refeeds:          True
filter_realign:           True

[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

[recognition.vgg_face2]
batch-size:               16
cpu:                      False

--------- 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
save_optimizer:           exit
lr_finder_iterations:     1000
lr_finder_mode:           set
lr_finder_strength:       default
autoclip:                 False
reflect_padding:          False
allow_growth:             False
mixed_precision:          False
nan_protection:           True
convert_batchsize:        16

[global.loss]
loss_function:            ssim
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:                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
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:              7
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_upscales_in_fc:       0
dec_norm:                 none
dec_min_filters:          64
dec_max_filters:          512
dec_slope_mode:           full
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
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
mask_opacity:             30
mask_color:               #ff0000
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
Last edited by torzdf on Fri Feb 02, 2024 3:44 pm, edited 3 times in total.
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torzdf
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Re: Error starting training: TypeError: 'NoneType' object is not subscriptable

Post by torzdf »

A word of friendly advice. It makes life a lot easier if you describe the exact steps you took to hit this error, otherwise we have very little to go on.

However, what are the contents of these folders, and where did they come from?

D:/A
D:/B

My word is final

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bist
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Re: Error starting training: TypeError: 'NoneType' object is not subscriptable

Post by bist »

A is input A B is input B
I have completed the extraction of the photos
C is Model Dir
D is output

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Re: Error starting training: TypeError: 'NoneType' object is not subscriptable

Post by torzdf »

I meant, specifically, what is the contents of those 2 folders.

What is happening here is that the process is trying to read the Faceswap meta information from the images in these folders. It is unable to. The only reason this would happen is if you had images in that folder that were not generated by the faceswap extract process.

Check those folders. You have images in there that should not be in there.

My word is final

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bist
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Re: Error starting training: TypeError: 'NoneType' object is not subscriptable

Post by bist »

Thank you
I did make modifications to the photos in these two folders

Is it allowed to delete some of the photos in these two folders?

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Re: Error starting training: TypeError: 'NoneType' object is not subscriptable

Post by torzdf »

Yes. That is fine

My word is final

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