[Guide] Using Faceswap on Nvidia RTX 30xx cards

Installing and setting up FaceSwap


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dlinkdnsnas
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by dlinkdnsnas »

Are you running command prompt as ADMIN?

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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by bryanlyon »

dlinkdnsnas wrote: Wed Jan 06, 2021 5:59 pm

Are you running command prompt as ADMIN?

DO NOT DO THIS! DO NOT INSTALL OR RUN FACESWAP AS ADMIN!

It is not necessary and can lead to problems.

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abigflea
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by abigflea »

No, not tried it in Admin.
When I do, Bryan beats me with a old videocard in a sock.

:o I dunno what I'm doing :shock:
2X RTX 3090 : RTX 3080 : RTX: 2060 : 2x RTX 2080 Super : Ghetto 1060

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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by torzdf »

abigflea wrote: Wed Jan 06, 2021 4:26 pm

write permissions error on second attempt after reinstalling miniconda.

That's between you and Bill Gates to resolve ;)

My word is final

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elon
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by elon »

torzdf wrote: Thu Jan 07, 2021 8:02 pm
abigflea wrote: Wed Jan 06, 2021 4:26 pm

write permissions error on second attempt after reinstalling miniconda.

That's between you and Bill Gates to resolve ;)

I solved all my 3090 problem now.

Very Satisfied.

it is Same or higher speed than 2080ti x 3way

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Evanchen
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by Evanchen »

Hi Sirs,
I followed the instruction to install it. but I encountered some problems.
It seems like issue happened and it caused the installation not successful.
I am not familiar with Conda environment.
Could you help to take a look on this ? Thanks !! :)
My graphic card : RTX3070
Nvidia driver: 457.51
CUDA version : 11.0
CuDNN version : 8.0.4

  1. When I typing command which is "conda activate faceswap" in Anaconda Prompt.
    It shows following information.
    code C:\Users\chris>conda activate faceswap
    Could not find conda environment: faceswap
    You can list all discoverable environments with conda info --envs.[/code]

  2. When I typing command which is "conda remove tensorflow" in Anaconda Prompt.
    code C:\Users\chris>conda remove tensorflow
    Collecting package metadata (repodata.json): done
    Solving environment: failed

PackagesNotFoundError: The following packages are missing from the target environment:

  • tensorflow[/code]

  • When I typing command which is "pip install tensorflow-gpu==2.4" in Anaconda Prompt.
    code C:\Users\chris>pip install tensorflow-gpu==2.4
    Requirement already satisfied: tensorflow-gpu==2.4 in c:\users\chris\anaconda3\lib\site-packages (2.4.0)
    Requirement already satisfied: numpy~=1.19.2 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (1.19.2)
    Requirement already satisfied: six~=1.15.0 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (1.15.0)
    Requirement already satisfied: h5py~=2.10.0 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (2.10.0)
    Requirement already satisfied: grpcio~=1.32.0 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (1.32.0)
    Requirement already satisfied: wrapt~=1.12.1 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (1.12.1)
    Requirement already satisfied: absl-py~=0.10 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (0.11.0)
    Requirement already satisfied: opt-einsum~=3.3.0 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (3.3.0)
    Requirement already satisfied: wheel~=0.35 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (0.35.1)
    Requirement already satisfied: tensorflow-estimator<2.5.0,>=2.4.0rc0 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (2.4.0)
    Requirement already satisfied: keras-preprocessing~=1.1.2 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (1.1.2)
    Requirement already satisfied: typing-extensions~=3.7.4 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (3.7.4.3)
    Requirement already satisfied: flatbuffers~=1.12.0 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (1.12)
    Requirement already satisfied: protobuf>=3.9.2 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (3.14.0)
    Requirement already satisfied: gast==0.3.3 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (0.3.3)
    Requirement already satisfied: tensorboard~=2.4 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (2.4.0)
    Requirement already satisfied: termcolor~=1.1.0 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (1.1.0)
    Requirement already satisfied: google-pasta~=0.2 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (0.2.0)
    Requirement already satisfied: astunparse~=1.6.3 in c:\users\chris\anaconda3\lib\site-packages (from tensorflow-gpu==2.4) (1.6.3)
    Requirement already satisfied: requests<3,>=2.21.0 in c:\users\chris\anaconda3\lib\site-packages (from tensorboard~=2.4->tensorflow-gpu==2.4) (2.24.0)
    Requirement already satisfied: google-auth<2,>=1.6.3 in c:\users\chris\anaconda3\lib\site-packages (from tensorboard~=2.4->tensorflow-gpu==2.4) (1.24.0)
    Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in c:\users\chris\anaconda3\lib\site-packages (from tensorboard~=2.4->tensorflow-gpu==2.4) (1.7.0)
    Requirement already satisfied: markdown>=2.6.8 in c:\users\chris\anaconda3\lib\site-packages (from tensorboard~=2.4->tensorflow-gpu==2.4) (3.3.3)
    Requirement already satisfied: werkzeug>=0.11.15 in c:\users\chris\anaconda3\lib\site-packages (from tensorboard~=2.4->tensorflow-gpu==2.4) (1.0.1)
    Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in c:\users\chris\anaconda3\lib\site-packages (from tensorboard~=2.4->tensorflow-gpu==2.4) (0.4.2)
    Requirement already satisfied: setuptools>=41.0.0 in c:\users\chris\anaconda3\lib\site-packages (from tensorboard~=2.4->tensorflow-gpu==2.4) (50.3.1.post20201107)
    Requirement already satisfied: chardet<4,>=3.0.2 in c:\users\chris\anaconda3\lib\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow-gpu==2.4) (3.0.4)
    Requirement already satisfied: idna<3,>=2.5 in c:\users\chris\anaconda3\lib\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow-gpu==2.4) (2.10)
    Requirement already satisfied: certifi>=2017.4.17 in c:\users\chris\anaconda3\lib\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow-gpu==2.4) (2020.6.20)
    Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in c:\users\chris\anaconda3\lib\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow-gpu==2.4) (1.25.11)
    Requirement already satisfied: rsa<5,>=3.1.4; python_version >= "3.6" in c:\users\chris\anaconda3\lib\site-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow-gpu==2.4) (4.6)
    Requirement already satisfied: cachetools<5.0,>=2.0.0 in c:\users\chris\anaconda3\lib\site-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow-gpu==2.4) (4.2.0)
    Requirement already satisfied: pyasn1-modules>=0.2.1 in c:\users\chris\anaconda3\lib\site-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow-gpu==2.4) (0.2.8)
    Requirement already satisfied: requests-oauthlib>=0.7.0 in c:\users\chris\anaconda3\lib\site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow-gpu==2.4) (1.3.0)
    Requirement already satisfied: pyasn1>=0.1.3 in c:\users\chris\anaconda3\lib\site-packages (from rsa<5,>=3.1.4; python_version >= "3.6"->google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow-gpu==2.4) (0.4.8)
    Requirement already satisfied: oauthlib>=3.0.0 in c:\users\chris\anaconda3\lib\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow-gpu==2.4) (3.1.0)
    [/code]

  • I can open the faceswap software , it seems like running in CPU mode.
    Even the information shows setting backend to NVIDIA. but when I tried to run the extract/train mode , the GPU loading rate only 5% , CPU loading rate is 100%.

Code: Select all

Loading...
Setting Faceswap backend to NVIDIA
01/08/2021 23:55:49 INFO     Log level set to: INFO
01/08/2021 23:55:51 INFO     Model A Directory: E:\videodata\1
01/08/2021 23:55:51 INFO     Model B Directory: E:\videodata\2
01/08/2021 23:55:51 INFO     Training data directory: E:\videodata\4
01/08/2021 23:55:51 INFO     ===================================================
01/08/2021 23:55:51 INFO       Starting
01/08/2021 23:55:51 INFO       Press 'Stop' to save and quit
01/08/2021 23:55:51 INFO     ===================================================
01/08/2021 23:55:52 INFO     Loading data, this may take a while...
01/08/2021 23:55:52 INFO     Loading Model from Original plugin...
01/08/2021 23:55:52 INFO     Using configuration saved in state file
01/08/2021 23:55:53 INFO     Loaded model from disk: 'E:\videodata\4\original.h5'
01/08/2021 23:55:53 INFO     Loading Trainer from Original plugin...

Reading training images (A):   0%|          | 0/368 [00:00<?, ?it/s]
Reading training images (A):  55%|█████▌    | 203/368 [00:00<00:00, 1931.61it/s]


Reading training images (B):   0%|          | 0/388 [00:00<?, ?it/s]
Reading training images (B):  17%|█▋        | 65/388 [00:00<00:00, 624.44it/s]
Reading training images (B):  75%|███████▌  | 292/388 [00:00<00:00, 1566.48it/s]01/08/2021 23:55:54 INFO     Reading alignments from: 'E:\videodata\1\8_alignments.fsa'

01/08/2021 23:55:54 INFO     Reading alignments from: 'E:\videodata\2\BBB_alignments.fsa'
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abigflea
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by abigflea »

Looks as though you skipped one of the first steps.
.
Looks as though the conda environment wasn't created , or you named the environment something other than "faceswap"

Install FaceSwap first, per the instructions.
That will create the conda environment... Then continue with the instructions

:o I dunno what I'm doing :shock:
2X RTX 3090 : RTX 3080 : RTX: 2060 : 2x RTX 2080 Super : Ghetto 1060

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derad
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by derad »

Ok, followed this process. I noticed extraction is significantly more "zoomed out" than it was before. I loaded a previous project file and kept the settings the same. See below for before / after.

Is this expected behavior?

Before

Image

After

Image

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Evanchen
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by Evanchen »

Hi abigflea ,
Thanks for your help. Now I already finished installation again and solve the ""conda environment".
But I tried to run the extract/train mode , the GPU loading rate still only 5% , CPU loading rate is 100%.
I put some faceswap information as below , could you help to take a look on this ? :)

Output system information from faceswap

Code: Select all

============ System Information ============
encoding:            cp950
git_branch:          master
git_commits:         163b8fe sysinfo/setup - Standardize cuda/cudnn checks
gpu_cuda:            11.0
gpu_cudnn:           8.0.5
gpu_devices:         GPU_0: GeForce RTX 3070
gpu_devices_active:  GPU_0
gpu_driver:          457.51
gpu_vram:            GPU_0: 8192MB
os_machine:          AMD64
os_platform:         Windows-10-10.0.18362-SP0
os_release:          10
py_command:          C:\Users\chris\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:           16
sys_processor:       AMD64 Family 23 Model 8 Stepping 2, AuthenticAMD
sys_ram:             Total: 32715MB, Available: 19321MB, Used: 13394MB, Free: 19321MB

=============== Pip Packages ===============
absl-py==0.11.0
astunparse==1.6.3
cachetools==4.2.0
certifi==2020.12.5
chardet==4.0.0
cycler==0.10.0
fastcluster==1.1.26
ffmpy==0.2.3
flatbuffers==1.12
gast==0.3.3
google-auth==1.24.0
google-auth-oauthlib==0.4.2
google-pasta==0.2.0
grpcio==1.32.0
h5py==2.10.0
idna==2.10
imageio @ file:///tmp/build/80754af9/imageio_1594161405741/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1609799311556/work
joblib @ file:///tmp/build/80754af9/joblib_1607970656719/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 @ file:///C:/ci/numpy_and_numpy_base_1603466732592/work
nvidia-ml-py3 @ git+https://github.com/deepfakes/nvidia-ml-py3.git@6fc29ac84b32bad877f078cb4a777c1548a00bf6
oauthlib==3.1.0
olefile==0.46
opencv-python==4.5.1.48
opt-einsum==3.3.0
pathlib==1.0.1
Pillow @ file:///C:/ci/pillow_1609786840597/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==2.25.1
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==2.4.0
tensorboard-plugin-wit==1.7.0
tensorflow-estimator==2.4.0
tensorflow-gpu==2.4.0
termcolor==1.1.0
threadpoolctl @ file:///tmp/tmp9twdgx9k/threadpoolctl-2.1.0-py3-none-any.whl
tornado @ file:///C:/ci/tornado_1606942392901/work
tqdm @ file:///tmp/build/80754af9/tqdm_1609788246169/work
typing-extensions==3.7.4.3
urllib3==1.26.2
Werkzeug==1.0.1
wincertstore==0.2
wrapt==1.12.1

============== Conda Packages ==============
# packages in environment at C:\Users\chris\anaconda3\envs\faceswap:
#
# Name                    Version                   Build  Channel
absl-py                   0.11.0                   pypi_0    pypi
astunparse                1.6.3                    pypi_0    pypi
blas                      1.0                         mkl  
ca-certificates 2020.12.8 haa95532_0
cachetools 4.2.0 pypi_0 pypi certifi 2020.12.5 py38haa95532_0
chardet 4.0.0 pypi_0 pypi cycler 0.10.0 py38_0
fastcluster 1.1.26 py38h251f6bf_2 conda-forge ffmpeg 4.2.2 he774522_0
ffmpy 0.2.3 pypi_0 pypi flatbuffers 1.12 pypi_0 pypi freetype 2.10.4 hd328e21_0
gast 0.3.3 pypi_0 pypi git 2.23.0 h6bb4b03_0
google-auth 1.24.0 pypi_0 pypi google-auth-oauthlib 0.4.2 pypi_0 pypi google-pasta 0.2.0 pypi_0 pypi grpcio 1.32.0 pypi_0 pypi h5py 2.10.0 pypi_0 pypi icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 2.10 pypi_0 pypi imageio 2.9.0 py_0
imageio-ffmpeg 0.4.3 pyhd8ed1ab_0 conda-forge intel-openmp 2020.2 254
joblib 1.0.0 pyhd3eb1b0_0
jpeg 9b hb83a4c4_2
keras-preprocessing 1.1.2 pypi_0 pypi 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
markdown 3.3.3 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 1.2.0 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 oauthlib 3.1.0 pypi_0 pypi olefile 0.46 py_0
opencv-python 4.5.1.48 pypi_0 pypi openssl 1.1.1i h2bbff1b_0
opt-einsum 3.3.0 pypi_0 pypi pathlib 1.0.1 py_1
pillow 8.1.0 py38h4fa10fc_0
pip 20.3.3 py38haa95532_0
protobuf 3.14.0 pypi_0 pypi psutil 5.7.2 py38he774522_0
pyasn1 0.4.8 pypi_0 pypi pyasn1-modules 0.2.8 pypi_0 pypi 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
requests 2.25.1 pypi_0 pypi requests-oauthlib 1.3.0 pypi_0 pypi rsa 4.6 pypi_0 pypi scikit-learn 0.23.2 py38h47e9c7a_0
scipy 1.5.2 py38h14eb087_0
setuptools 51.0.0 py38haa95532_2
sip 4.19.13 py38ha925a31_0
six 1.15.0 py38haa95532_0
sqlite 3.33.0 h2a8f88b_0
tensorboard 2.4.0 pypi_0 pypi tensorboard-plugin-wit 1.7.0 pypi_0 pypi tensorflow-estimator 2.4.0 pypi_0 pypi tensorflow-gpu 2.4.0 pypi_0 pypi termcolor 1.1.0 pypi_0 pypi threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.10 he774522_0
tornado 6.1 py38h2bbff1b_0
tqdm 4.55.1 pyhd3eb1b0_0
typing-extensions 3.7.4.3 pypi_0 pypi urllib3 1.26.2 pypi_0 pypi vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 1.0.1 pypi_0 pypi wheel 0.36.2 pyhd3eb1b0_0
wincertstore 0.2 py38_0
wrapt 1.12.1 pypi_0 pypi 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] centering: face coverage: 68.75 icnr_init: False conv_aware_init: True optimizer: adam learning_rate: 5e-05 reflect_padding: False allow_growth: True 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.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.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

The following information shows up when I am executing "Train" function ,

Code: Select all

Loading...
Setting Faceswap backend to NVIDIA
01/09/2021 10:12:49 INFO     Log level set to: INFO
01/09/2021 10:12:51 INFO     Model A Directory: E:\videodata\1
01/09/2021 10:12:51 INFO     Model B Directory: E:\videodata\2
01/09/2021 10:12:51 INFO     Training data directory: E:\videodata\4
01/09/2021 10:12:51 INFO     ===================================================
01/09/2021 10:12:51 INFO       Starting
01/09/2021 10:12:51 INFO       Press 'Stop' to save and quit
01/09/2021 10:12:51 INFO     ===================================================
01/09/2021 10:12:52 INFO     Loading data, this may take a while...
01/09/2021 10:12:52 INFO     Loading Model from Dfl_H128 plugin...
01/09/2021 10:12:52 INFO     Using configuration saved in state file
01/09/2021 10:12:52 INFO     Setting allow growth for GPU: PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')
01/09/2021 10:12:54 INFO     Loaded model from disk: 'E:\videodata\4\dfl_h128.h5'
01/09/2021 10:12:54 INFO     Loading Trainer from Original plugin...

Reading training images (A):   0%|          | 0/368 [00:00<?, ?it/s]
Reading training images (A):  52%|█████▏    | 190/368 [00:00<00:00, 1825.29it/s]


Reading training images (B):   0%|          | 0/388 [00:00<?, ?it/s]
Reading training images (B):  54%|█████▍    | 210/388 [00:00<00:00, 2056.98it/s]
01/09/2021 10:12:55 INFO     Reading alignments from: 'E:\videodata\1\8_alignments.fsa'
01/09/2021 10:12:55 INFO     Reading alignments from: 'E:\videodata\2\BBB_alignments.fsa'
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torzdf
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by torzdf »

derad wrote: Fri Jan 08, 2021 11:42 pm

Ok, followed this process. I noticed extraction is significantly more "zoomed out" than it was before. I loaded a previous project file and kept the settings the same. See below for before / after.

Is this expected behavior?

Before

Image

After

Image

This is correct. See here:

https://github.com/deepfakes/faceswap/pull/1095

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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by torzdf »

Evanchen wrote: Sat Jan 09, 2021 2:16 am

But I tried to run the extract/train mode , the GPU loading rate still only 5% , CPU loading rate is 100%.

See here:
app.php/faqpage#f0r3

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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by C0dingschmuser »

elon wrote: Thu Jan 07, 2021 10:06 pm

I solved all my 3090 problem now.

Very Satisfied.

it is Same or higher speed than 2080ti x 3way

[mention]elon[/mention] How did you fix the freezing issues?
I have a 3070 and my Training freezes randomly on Dfl-H128, reducing Batch Size doesn't seem to help either.

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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by abigflea »

Using Win10
Nvidia 457.51 (Do not use 460.xx - bad juju)
Only : 3060Ti + 2070
Followed post exactly.

Kept getting the "brotli" error, no matter how many drivers/software I uninstalled, environments removed.

Google search gave me:

Code: Select all

conda install -c anaconda urllib3

and it worked.

3060Ti now running.
Although with both cards I'm getting a strangely low possible batch and only a few 1000 iteration before a OOM crash.
Getting a batch of 3-5 with either card.
Normally with Villian get 1214 batch.

Still 2070 works fantastic with a normal Faceswap install.
At a batch of 3, I can tell the 3060Ti is at minimum 12% faster than a 2070.

Code: Select all

============ System Information ============
encoding:            cp1252
git_branch:          master
git_commits:         163b8fe sysinfo/setup - Standardize cuda/cudnn checks
gpu_cuda:            11.0
gpu_cudnn:           8.0.5
gpu_devices:         GPU_0: GeForce RTX 3060 Ti, GPU_1: GeForce RTX 2070
gpu_devices_active:  GPU_0, GPU_1
gpu_driver:          457.51
gpu_vram:            GPU_0: 8192MB, GPU_1: 8192MB
os_machine:          AMD64
os_platform:         Windows-10-10.0.19041-SP0
os_release:          10
py_command:          C:\Users\abigf\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:           12
sys_processor:       AMD64 Family 23 Model 8 Stepping 2, AuthenticAMD
sys_ram:             Total: 32712MB, Available: 26730MB, Used: 5982MB, Free: 26730MB

=============== Pip Packages ===============
absl-py==0.11.0
astunparse==1.6.3
brotlipy==0.7.0
cachetools==4.2.0
certifi==2020.6.20
cffi @ file:///C:/ci/cffi_1600699246375/work
chardet==4.0.0
cryptography @ file:///C:/ci/cryptography_1601046905460/work
cycler==0.10.0
fastcluster==1.1.26
ffmpy==0.2.3
flatbuffers==1.12
gast==0.3.3
google-auth==1.24.0
google-auth-oauthlib==0.4.2
google-pasta==0.2.0
grpcio==1.32.0
h5py==2.10.0
idna @ file:///tmp/build/80754af9/idna_1593446292537/work
imageio @ file:///tmp/build/80754af9/imageio_1594161405741/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1609799311556/work
joblib @ file:///tmp/build/80754af9/joblib_1607970656719/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 @ file:///C:/ci/numpy_and_numpy_base_1603466732592/work
nvidia-ml-py3 @ git+https://github.com/deepfakes/nvidia-ml-py3.git@6fc29ac84b32bad877f078cb4a777c1548a00bf6
oauthlib==3.1.0
olefile==0.46
opencv-python==4.5.1.48
opt-einsum==3.3.0
pathlib==1.0.1
Pillow @ file:///C:/ci/pillow_1609786840597/work
protobuf==3.14.0
psutil @ file:///C:/ci/psutil_1598370330503/work
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycparser @ file:///tmp/build/80754af9/pycparser_1594388511720/work
pyOpenSSL @ file:///tmp/build/80754af9/pyopenssl_1594392929924/work
pyparsing==2.4.7
PySocks==1.7.1
python-dateutil==2.8.1
pywin32==227
requests==2.25.1
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==2.4.0
tensorboard-plugin-wit==1.7.0
tensorflow-estimator==2.4.0
tensorflow-gpu==2.4.0
termcolor==1.1.0
threadpoolctl @ file:///tmp/tmp9twdgx9k/threadpoolctl-2.1.0-py3-none-any.whl
tornado @ file:///C:/ci/tornado_1606942392901/work
tqdm @ file:///tmp/build/80754af9/tqdm_1609788246169/work
typing-extensions==3.7.4.3
urllib3 @ file:///tmp/build/80754af9/urllib3_1603305693037/work
Werkzeug==1.0.1
win-inet-pton==1.1.0
wincertstore==0.2
wrapt==1.12.1

============== Conda Packages ==============
# packages in environment at C:\Users\abigf\MiniConda3\envs\faceswap:
#
# Name                    Version                   Build  Channel
absl-py                   0.11.0                   pypi_0    pypi
astunparse                1.6.3                    pypi_0    pypi
blas                      1.0                         mkl  
brotli 1.0.9 ha925a31_2
brotlipy 0.7.0 py38he774522_1000 anaconda ca-certificates 2020.10.14 0 anaconda cachetools 4.2.0 pypi_0 pypi certifi 2020.6.20 py38_0 anaconda cffi 1.14.3 py38h7a1dbc1_0 anaconda chardet 4.0.0 pypi_0 pypi cryptography 3.1.1 py38h7a1dbc1_0 anaconda cycler 0.10.0 py38_0
fastcluster 1.1.26 py38h251f6bf_2 conda-forge ffmpeg 4.2.2 he774522_0
ffmpy 0.2.3 pypi_0 pypi flatbuffers 1.12 pypi_0 pypi freetype 2.10.4 hd328e21_0
gast 0.3.3 pypi_0 pypi git 2.23.0 h6bb4b03_0
google-auth 1.24.0 pypi_0 pypi google-auth-oauthlib 0.4.2 pypi_0 pypi google-pasta 0.2.0 pypi_0 pypi grpcio 1.32.0 pypi_0 pypi h5py 2.10.0 pypi_0 pypi icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 2.10 py_0 anaconda imageio 2.9.0 py_0
imageio-ffmpeg 0.4.3 pyhd8ed1ab_0 conda-forge intel-openmp 2020.2 254
joblib 1.0.0 pyhd3eb1b0_0
jpeg 9b hb83a4c4_2
keras-preprocessing 1.1.2 pypi_0 pypi 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
markdown 3.3.3 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 1.2.0 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 oauthlib 3.1.0 pypi_0 pypi olefile 0.46 py_0
opencv-python 4.5.1.48 pypi_0 pypi openssl 1.1.1h he774522_0 anaconda opt-einsum 3.3.0 pypi_0 pypi pathlib 1.0.1 py_1
pillow 8.1.0 py38h4fa10fc_0
pip 20.3.3 py38haa95532_0
protobuf 3.14.0 pypi_0 pypi psutil 5.7.2 py38he774522_0
pyasn1 0.4.8 pypi_0 pypi pyasn1-modules 0.2.8 pypi_0 pypi pycparser 2.20 py_2 anaconda pyopenssl 19.1.0 py_1 anaconda pyparsing 2.4.7 py_0
pyqt 5.9.2 py38ha925a31_4
pysocks 1.7.1 py38_0 anaconda 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
requests 2.25.1 pypi_0 pypi requests-oauthlib 1.3.0 pypi_0 pypi rsa 4.6 pypi_0 pypi scikit-learn 0.23.2 py38h47e9c7a_0
scipy 1.5.2 py38h14eb087_0
setuptools 51.0.0 py38haa95532_2
sip 4.19.13 py38ha925a31_0
six 1.15.0 py38haa95532_0
sqlite 3.33.0 h2a8f88b_0
tensorboard 2.4.0 pypi_0 pypi tensorboard-plugin-wit 1.7.0 pypi_0 pypi tensorflow-estimator 2.4.0 pypi_0 pypi tensorflow-gpu 2.4.0 pypi_0 pypi termcolor 1.1.0 pypi_0 pypi threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.10 he774522_0
tornado 6.1 py38h2bbff1b_0
tqdm 4.55.1 pyhd3eb1b0_0
typing-extensions 3.7.4.3 pypi_0 pypi urllib3 1.25.11 py_0 anaconda vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 1.0.1 pypi_0 pypi wheel 0.36.2 pyhd3eb1b0_0
win_inet_pton 1.1.0 py38_0 anaconda wincertstore 0.2 py38_0
wrapt 1.12.1 pypi_0 pypi 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] centering: face coverage: 69.09 icnr_init: False conv_aware_init: False optimizer: adam learning_rate: 5e-05 reflect_padding: False allow_growth: True mixed_precision: 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.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

:o I dunno what I'm doing :shock:
2X RTX 3090 : RTX 3080 : RTX: 2060 : 2x RTX 2080 Super : Ghetto 1060

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pakovia
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Slow extraction

Post by pakovia »

Hello

i have 3080 gpu and face extraction is really slow only 2,38 it/s
followed all instructions here app.php/faqpage#f1r1 and here viewtopic.php?t=1226 but it is still slow.

thank you

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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by FishBear »

Thank you for the guide! it works for me in the following configuration:

Cuda 11.1.1
cuDNN 8.0.5
TensorFlow 2.4
Nvidia driver 461.09 (latest)

I haven't done any extensive testing but it starts to train and I can see the preview and I can see that it's going through iterations. :D

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pakovia
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by pakovia »

ok so the extraction does work around 25 it/s it also ends with extracted images
but i have some errors

Code: Select all

2021-01-11 20:49:03.683501: E tensorflow/stream_executor/stream.cc:5011] Internal: Failed to enqueue async memset operation: CUDA_ERROR_INVALID_VALUE: invalid argument
2021-01-11 20:49:03.684211: E tensorflow/stream_executor/cuda/cuda_driver.cc:1051] failed to enqueue async memcpy from device to host: CUDA_ERROR_INVALID_VALUE: invalid argument; host dst: 0x65dfb3c9e0; GPU src: (nil); size: 8=0x8
2021-01-11 20:49:03.684536: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-11 20:49:03.686348: F tensorflow/core/common_runtime/gpu/gpu_util.cc:291] GPU->CPU Memcpy failed

or

Code: Select all

2021-01-11 20:52:44.133832: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-11 20:52:44.446660: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-11 20:52:44.761302: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by impost3r »

Any updates on 3080/3090 support in W10?

Is faceswap still unsupported/untested for these new cards or are they more stable now?

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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by torzdf »

Until Anaconda Cloud supports Tensorflow 2.4, this is out of our hands beyond the instructions detailed in the first post:

https://anaconda.org/anaconda/tensorflow-gpu

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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by abigflea »

for Win10 Gforce game Ready Driver 461.40 seems to not break anything new with current manual install described in the first post.

:o I dunno what I'm doing :shock:
2X RTX 3090 : RTX 3080 : RTX: 2060 : 2x RTX 2080 Super : Ghetto 1060

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Re: [Guide] Using Faceswap on Nvidia RTX 30xx cards

Post by impost3r »

RTX 3090 / 461.40 drivers

I needed the brotli fix: conda install -c anaconda urllib3

Then installed with Cuda Toolkit 11.1 and the newer cuDNN. After that no errors.

However, training is extremely slow. Like 1 iteration every 10 seconds regardless of batch size.

I am getting this warning from previously extracted faces (on a 1070 card)

You are using legacy extracted faces but have selected 'face' centering which is incompatible. Switching centering to 'legacy'

Could that be the reason for the extremely slow performance?

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