For example, in the model training, the CPU load is too high and the GPU load is 0. Try to output the system information as follows (cudnn has been correctly installed, but it can not be detected, I don't know if this matter). I would appreciate it if you could help me.
Following is "Output system information"
Code: Select all
============ System Information ============
encoding: cp936
git_branch: master
git_commits: c24bf2b GUI - Revert Conda default font fix
gpu_cuda: 10.2
gpu_cudnn: No global version found. Check Conda packages for Conda cuDNN
gpu_devices: GPU_0: GeForce GTX 1060
gpu_devices_active: GPU_0
gpu_driver: 457.30
gpu_vram: GPU_0: 6144MB
os_machine: AMD64
os_platform: Windows-10-10.0.18362-SP0
os_release: 10
py_command: D:\Software\faceswap/faceswap.py gui
py_conda_version: conda 4.9.2
py_implementation: CPython
py_version: 3.8.5
py_virtual_env: True
sys_cores: 8
sys_processor: Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
sys_ram: Total: 16258MB, Available: 10086MB, Used: 6171MB, Free: 10086MB
=============== Pip Packages ===============
absl-py==0.11.0
astunparse==1.6.3
cachetools==4.1.1
certifi==2020.11.8
cycler==0.10.0
fastcluster==1.1.26
ffmpy==0.2.3
gast==0.3.3
google-auth==1.23.0
google-auth-oauthlib==0.4.2
google-pasta==0.2.0
grpcio==1.33.2
h5py==2.10.0
imageio @ file:///tmp/build/80754af9/imageio_1594161405741/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1589202782679/work
joblib @ file:///tmp/build/80754af9/joblib_1601912903842/work
Keras-Preprocessing==1.1.2
kiwisolver @ file:///C:/ci/kiwisolver_1604014703538/work
Markdown==3.3.3
matplotlib @ file:///C:/ci/matplotlib-base_1592837548929/work
mkl-fft==1.2.0
mkl-random==1.1.1
mkl-service==2.3.0
numpy==1.18.5
nvidia-ml-py3 @ git+https://github.com/deepfakes/nvidia-ml-py3.git@6fc29ac84b32bad877f078cb4a777c1548a00bf6
oauthlib==3.1.0
olefile==0.46
opencv-python==4.4.0.46
opt-einsum==3.3.0
pathlib==1.0.1
Pillow @ file:///C:/ci/pillow_1603823068645/work
protobuf==3.14.0
psutil @ file:///C:/ci/psutil_1598370330503/work
pyasn1==0.4.8
pyasn1-modules==0.2.8
pyparsing==2.4.7
python-dateutil==2.8.1
pywin32==227
requests-oauthlib==1.3.0
rsa==4.6
scikit-learn @ file:///C:/ci/scikit-learn_1598377018496/work
scipy @ file:///C:/ci/scipy_1604596260408/work
sip==4.19.13
six @ file:///C:/ci/six_1605187374963/work
tensorboard==2.2.2
tensorboard-plugin-wit==1.7.0
tensorflow-gpu==2.2.1
tensorflow-gpu-estimator==2.2.0
termcolor==1.1.0
threadpoolctl @ file:///tmp/tmp9twdgx9k/threadpoolctl-2.1.0-py3-none-any.whl
tornado==6.0.4
tqdm @ file:///tmp/build/80754af9/tqdm_1605303662894/work
Werkzeug==1.0.1
wincertstore==0.2
wrapt==1.12.1
============== Conda Packages ==============
# packages in environment at C:\Users\QS\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
blas 1.0 mkl
ca-certificates 2020.10.14 0
certifi 2020.11.8 py38haa95532_0
cycler 0.10.0 py38_0
fastcluster 1.1.26 py38h251f6bf_2 conda-forge
ffmpeg 4.3.1 ha925a31_0 conda-forge
freetype 2.10.4 hd328e21_0
git 2.23.0 h6bb4b03_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
imageio 2.9.0 py_0
imageio-ffmpeg 0.4.2 py_0 conda-forge
intel-openmp 2020.2 254
joblib 0.17.0 py_0
jpeg 9b hb83a4c4_2
kiwisolver 1.3.0 py38hd77b12b_0
libpng 1.6.37 h2a8f88b_0
libtiff 4.1.0 h56a325e_1
lz4-c 1.9.2 hf4a77e7_3
matplotlib 3.2.2 0
matplotlib-base 3.2.2 py38h64f37c6_0
mkl 2020.2 256
mkl-service 2.3.0 py38h2bbff1b_0
mkl_fft 1.2.0 py38h45dec08_0
mkl_random 1.1.1 py38h47e9c7a_0
numpy 1.19.2 py38hadc3359_0
numpy-base 1.19.2 py38ha3acd2a_0
nvidia-ml-py3 7.352.1 pypi_0 pypi
olefile 0.46 py_0
openssl 1.1.1h he774522_0
pathlib 1.0.1 py_1
pillow 8.0.1 py38h4fa10fc_0
pip 20.2.4 py38haa95532_0
psutil 5.7.2 py38he774522_0
pyparsing 2.4.7 py_0
pyqt 5.9.2 py38ha925a31_4
python 3.8.5 h5fd99cc_1
python-dateutil 2.8.1 py_0
python_abi 3.8 1_cp38 conda-forge
pywin32 227 py38he774522_1
qt 5.9.7 vc14h73c81de_0
scikit-learn 0.23.2 py38h47e9c7a_0
scipy 1.5.2 py38h14eb087_0
setuptools 50.3.1 py38haa95532_1
sip 4.19.13 py38ha925a31_0
six 1.15.0 py38haa95532_0
sqlite 3.33.0 h2a8f88b_0
threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.10 he774522_0
tornado 6.0.4 py38he774522_1
tqdm 4.51.0 pyhd3eb1b0_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_3
wheel 0.35.1 pyhd3eb1b0_0
wincertstore 0.2 py38_0
xz 5.2.5 h62dcd97_0
zlib 1.2.11 h62dcd97_4
zstd 1.4.5 h04227a9_0
================= Configs ==================
--------- .faceswap ---------
backend: nvidia
--------- convert.ini ---------
[color.color_transfer]
clip: True
preserve_paper: True
[color.manual_balance]
colorspace: HSV
balance_1: 0.0
balance_2: 0.0
balance_3: 0.0
contrast: 0.0
brightness: 0.0
[color.match_hist]
threshold: 99.0
[mask.box_blend]
type: gaussian
distance: 11.0
radius: 5.0
passes: 1
[mask.mask_blend]
type: normalized
kernel_size: 3
passes: 4
threshold: 4
erosion: 0.0
[scaling.sharpen]
method: none
amount: 150
radius: 0.3
threshold: 5.0
[writer.ffmpeg]
container: mp4
codec: libx264
crf: 23
preset: medium
tune: none
profile: auto
level: auto
skip_mux: False
[writer.gif]
fps: 25
loop: 0
palettesize: 256
subrectangles: False
[writer.opencv]
format: png
draw_transparent: False
jpg_quality: 75
png_compress_level: 3
[writer.pillow]
format: png
draw_transparent: False
optimize: False
gif_interlace: True
jpg_quality: 75
png_compress_level: 3
tif_compression: tiff_deflate
--------- extract.ini ---------
[global]
allow_growth: 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
icnr_init: False
conv_aware_init: False
optimizer: adam
learning_rate: 5e-05
reflect_padding: False
allow_growth: False
mixed_precision: False
convert_batchsize: 16
[global.loss]
loss_function: ssim
mask_loss_function: mse
l2_reg_term: 100
eye_multiplier: 3
mouth_multiplier: 2
penalized_mask_loss: True
mask_type: extended
mask_blur_kernel: 3
mask_threshold: 4
learn_mask: False
[model.dfl_h128]
lowmem: False
[model.dfl_sae]
input_size: 128
clipnorm: True
architecture: df
autoencoder_dims: 0
encoder_dims: 42
decoder_dims: 21
multiscale_decoder: False
[model.dlight]
features: best
details: good
output_size: 256
[model.original]
lowmem: False
[model.realface]
input_size: 64
output_size: 128
dense_nodes: 1536
complexity_encoder: 128
complexity_decoder: 512
[model.unbalanced]
input_size: 128
lowmem: False
clipnorm: True
nodes: 1024
complexity_encoder: 128
complexity_decoder_a: 384
complexity_decoder_b: 512
[model.villain]
lowmem: False
[trainer.original]
preview_images: 14
zoom_amount: 5
rotation_range: 10
shift_range: 5
flip_chance: 50
disable_warp: False
color_lightness: 30
color_ab: 8
color_clahe_chance: 50
color_clahe_max_size: 4