Hi, running on a GTX970M.
Found the iterations dreadfully slow so looked into GPU usage with an app from MSI.
Turns out the GPU is doing nothing and it's my CPUs Doing all the work.
So I wonder if faceswap is confused with the gfx card as the laptop has an on board GPU too and it is trying to use that, finds no cuda and fall back to CPU?
Any way to force the usage of the GTX970m?
I'd rather not fork out £2000 for a new laptop while this is still in such great shape...
Thanks.
Code: Select all
============ System Information ============
encoding: cp1252
git_branch: master
git_commits: 808e008 Bugfix -Weights freezing/loading for dfl-sae
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: NVIDIA GeForce GTX 970M
gpu_devices_active: GPU_0
gpu_driver: 472.12
gpu_vram: GPU_0: 6144MB
os_machine: AMD64
os_platform: Windows-10-10.0.19043-SP0
os_release: 10
py_command: E:\Viktor\SOFTWARE\faceswapToo/faceswap.py gui
py_conda_version: conda 4.10.3
py_implementation: CPython
py_version: 3.8.12
py_virtual_env: True
sys_cores: 8
sys_processor: Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
sys_ram: Total: 48969MB, Available: 20898MB, Used: 28071MB, Free: 20898MB
=============== Pip Packages ===============
absl-py==0.15.0
astunparse==1.6.3
cachetools==4.2.4
certifi==2021.10.8
charset-normalizer==2.0.7
clang==5.0
cycler==0.10.0
fastcluster==1.1.26
ffmpy==0.2.3
flatbuffers==1.12
gast==0.4.0
google-auth==1.35.0
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.42.0
h5py==3.1.0
idna==3.3
imageio @ file:///tmp/build/80754af9/imageio_1617700267927/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1629987409325/work
importlib-metadata==4.8.2
joblib @ file:///tmp/build/80754af9/joblib_1635411271373/work
keras==2.6.0
Keras-Preprocessing==1.1.2
kiwisolver @ file:///C:/ci/kiwisolver_1612282606037/work
Markdown==3.3.6
matplotlib @ file:///C:/ci/matplotlib-base_1592837548929/work
mkl-fft==1.3.0
mkl-random==1.1.1
mkl-service==2.3.0
numpy @ file:///C:/ci/numpy_and_numpy_base_1603466732592/work
nvidia-ml-py==11.495.46
oauthlib==3.1.1
olefile @ file:///Users/ktietz/demo/mc3/conda-bld/olefile_1629805411829/work
opencv-python==4.5.4.60
opt-einsum==3.3.0
Pillow==8.4.0
protobuf==3.19.1
psutil @ file:///C:/ci/psutil_1612298324802/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==228
requests==2.26.0
requests-oauthlib==1.3.0
rsa==4.7.2
scikit-learn @ file:///C:/ci/scikit-learn_1635188126022/work
scipy @ file:///C:/ci/scipy_1616703433439/work
sip==4.19.13
six==1.15.0
tensorboard==2.6.0
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.0
tensorflow-estimator==2.6.0
tensorflow-gpu==2.6.2
termcolor==1.1.0
threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work
tornado @ file:///C:/ci/tornado_1606942392901/work
tqdm @ file:///tmp/build/80754af9/tqdm_1635330843403/work
typing-extensions==3.7.4.3
urllib3==1.26.7
Werkzeug==2.0.2
wincertstore==0.2
wrapt==1.12.1
zipp==3.6.0
============== Conda Packages ==============
# packages in environment at C:\Users\vr\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
absl-py 0.15.0 pypi_0 pypi
astunparse 1.6.3 pypi_0 pypi
blas 1.0 mkl
ca-certificates 2021.10.26 haa95532_2
cachetools 4.2.4 pypi_0 pypi
certifi 2021.10.8 py38haa95532_0
charset-normalizer 2.0.7 pypi_0 pypi
clang 5.0 pypi_0 pypi
cycler 0.10.0 py38_0
fastcluster 1.1.26 py38h5d928e2_3 conda-forge
ffmpeg 4.3.1 ha925a31_0 conda-forge
ffmpy 0.2.3 pypi_0 pypi
flatbuffers 1.12 pypi_0 pypi
freetype 2.10.4 hd328e21_0
gast 0.4.0 pypi_0 pypi
git 2.32.0 haa95532_1
google-auth 1.35.0 pypi_0 pypi
google-auth-oauthlib 0.4.6 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.42.0 pypi_0 pypi
h5py 3.1.0 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 0.4.5 pyhd8ed1ab_0 conda-forge
importlib-metadata 4.8.2 pypi_0 pypi
intel-openmp 2021.4.0 haa95532_3556
joblib 1.1.0 pyhd3eb1b0_0
jpeg 9d h2bbff1b_0
keras 2.6.0 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
kiwisolver 1.3.1 py38hd77b12b_0
libpng 1.6.37 h2a8f88b_0
libtiff 4.2.0 hd0e1b90_0
libwebp 1.2.0 h2bbff1b_0
lz4-c 1.9.3 h2bbff1b_1
markdown 3.3.6 pypi_0 pypi
matplotlib 3.2.2 0
matplotlib-base 3.2.2 py38h64f37c6_0
mkl 2020.2 256
mkl-service 2.3.0 py38h196d8e1_0
mkl_fft 1.3.0 py38h46781fe_0
mkl_random 1.1.1 py38h47e9c7a_0
numpy 1.19.2 py38hadc3359_0
numpy-base 1.19.2 py38ha3acd2a_0
nvidia-ml-py 11.495.46 pypi_0 pypi
oauthlib 3.1.1 pypi_0 pypi
olefile 0.46 pyhd3eb1b0_0
opencv-python 4.5.4.60 pypi_0 pypi
openssl 1.1.1l h2bbff1b_0
opt-einsum 3.3.0 pypi_0 pypi
pillow 8.4.0 py38hd45dc43_0
pip 21.2.2 py38haa95532_0
protobuf 3.19.1 pypi_0 pypi
psutil 5.8.0 py38h2bbff1b_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 py38ha925a31_4
python 3.8.12 h6244533_0
python-dateutil 2.8.2 pyhd3eb1b0_0
python_abi 3.8 2_cp38 conda-forge
pywin32 228 py38hbaba5e8_1
qt 5.9.7 vc14h73c81de_0
requests 2.26.0 pypi_0 pypi
requests-oauthlib 1.3.0 pypi_0 pypi
rsa 4.7.2 pypi_0 pypi
scikit-learn 1.0.1 py38hf11a4ad_0
scipy 1.6.2 py38h14eb087_0
setuptools 58.0.4 py38haa95532_0
sip 4.19.13 py38ha925a31_0
six 1.15.0 pypi_0 pypi
sqlite 3.36.0 h2bbff1b_0
tensorboard 2.6.0 pypi_0 pypi
tensorboard-data-server 0.6.1 pypi_0 pypi
tensorboard-plugin-wit 1.8.0 pypi_0 pypi
tensorflow-estimator 2.6.0 pypi_0 pypi
tensorflow-gpu 2.6.2 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
threadpoolctl 2.2.0 pyh0d69192_0
tk 8.6.11 h2bbff1b_0
tornado 6.1 py38h2bbff1b_0
tqdm 4.62.3 pyhd3eb1b0_1
typing-extensions 3.7.4.3 pypi_0 pypi
urllib3 1.26.7 pypi_0 pypi
vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 2.0.2 pypi_0 pypi
wheel 0.37.0 pyhd3eb1b0_1
wincertstore 0.2 py38haa95532_2
wrapt 1.12.1 pypi_0 pypi
xz 5.2.5 h62dcd97_0
zipp 3.6.0 pypi_0 pypi
zlib 1.2.11 h62dcd97_4
zstd 1.4.9 h19a0ad4_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: gaussian
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: 86
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
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: 81.37
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: bisenet-fp_face
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
[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