Page 1 of 1
Manual installation of tensorflow after using Windows installer?
Posted: Sat Oct 03, 2020 12:27 pm
by Anonym
Error upon opening Faceswap -
Setting Faceswap backend to NVIDIA
10/03/2020 08:18:57 INFO Log level set to: INFO
10/03/2020 08:18:57 ERROR There was an error importing Tensorflow. This is most likely because you do not have TensorFlow installed, or you are trying to run tensorflow-gpu on a system without an Nvidia graphics card. Original import error: No module named 'tensorflow'
[/spoiler]
From the installer -
INFO Installing tensorflow-gpu<2.3.0,>=2.2.0
INFO "tensorflow-gpu<2.3.0,>=2.2.0" not available in Conda. Installing with pip
INFO Installing cudatoolkit==10.1.243
WARNING Couldn't install cudatoolkit==10.1.243 with Conda. Please install this package manually
INFO Installing cudnn==7.6.5
INFO Installing tensorflow-gpu<2.3.0,>=2.2.0
WARNING Couldn't install tensorflow-gpu<2.3.0,>=2.2.0 with pip. Please install this package manually
I've followed the FAQ and removed everything faceswap, python, conda, miniconda, etc related from Users, Program Files + (x86), as well as appdata, rebooted, and tried to clean install multiple times. Drivers are up to date. Unsure how to continue.
Re: Manual installation of tensorflow after using Windows installer?
Posted: Sun Oct 04, 2020 12:46 am
by torzdf
Start > Anaconda Prompt
Code: Select all
conda activate faceswap
cd faceswap
python -c "from lib.sysinfo import sysinfo ; print(sysinfo)"
Post output
Re: Manual installation of tensorflow after using Windows installer?
Posted: Sun Oct 04, 2020 1:38 am
by Anonym
Code: Select all
============ System Information ============
encoding: cp1252
git_branch: master
git_commits: 8861101 Setup.py - Minor change to cudnn locator
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 770
gpu_devices_active: GPU_0
gpu_driver: 456.55
gpu_vram: GPU_0: 2048MB
os_machine: AMD64
os_platform: Windows-10-10.0.18362-SP0
os_release: 10
py_command: -c
py_conda_version: conda 4.8.5
py_implementation: CPython
py_version: 3.8.5
py_virtual_env: True
sys_cores: 8
sys_processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
sys_ram: Total: 16270MB, Available: 11945MB, Used: 4325MB, Free: 11945MB
=============== Pip Packages ===============
certifi==2020.6.20
cycler==0.10.0
fastcluster==1.1.26
ffmpy==0.2.3
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_1594236160679/work
kiwisolver==1.2.0
matplotlib==3.2.2
mkl-fft==1.2.0
mkl-random==1.1.1
mkl-service==2.3.0
numpy @ file:///C:/ci/numpy_and_numpy_base_1596215850360/work
nvidia-ml-py3 @ git+https://github.com/deepfakes/nvidia-ml-py3.git@6fc29ac84b32bad877f078cb4a777c1548a00bf6
olefile==0.46
opencv-python==4.4.0.44
pathlib==1.0.1
Pillow @ file:///C:/ci/pillow_1594298230227/work
psutil @ file:///C:/ci/psutil_1598370330503/work
pyparsing==2.4.7
python-dateutil==2.8.1
pywin32==227
scikit-learn @ file:///C:/ci/scikit-learn_1598377018496/work
scipy @ file:///C:/ci/scipy_1592916963468/work
six==1.15.0
threadpoolctl @ file:///tmp/tmp9twdgx9k/threadpoolctl-2.1.0-py3-none-any.whl
tqdm @ file:///tmp/build/80754af9/tqdm_1600709023549/work
wincertstore==0.2
============== Conda Packages ==============
# packages in environment at C:\Users\William\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
blas 1.0 mkl
ca-certificates 2020.7.22 0
certifi 2020.6.20 py38_0
cudatoolkit 10.2.89 h74a9793_1
cudnn 7.6.5 cuda10.2_0
cycler 0.10.0 pypi_0 pypi
fastcluster 1.1.26 py38hbe40bda_1 conda-forge
ffmpeg 4.3.1 ha925a31_0 conda-forge
ffmpy 0.2.3 pypi_0 pypi
freetype 2.10.2 hd328e21_0
git 2.23.0 h6bb4b03_0
icc_rt 2019.0.0 h0cc432a_1
imageio 2.9.0 py_0
imageio-ffmpeg 0.4.2 py_0 conda-forge
intel-openmp 2020.2 254
joblib 0.16.0 py_0
jpeg 9b hb83a4c4_2
kiwisolver 1.2.0 pypi_0 pypi
libpng 1.6.37 h2a8f88b_0
libtiff 4.1.0 h56a325e_1
lz4-c 1.9.2 h62dcd97_1
matplotlib 3.2.2 pypi_0 pypi
mkl 2020.2 256
mkl-service 2.3.0 py38hb782905_0
mkl_fft 1.2.0 py38h45dec08_0
mkl_random 1.1.1 py38h47e9c7a_0
numpy 1.19.1 py38h5510c5b_0
numpy-base 1.19.1 py38ha3acd2a_0
nvidia-ml-py3 7.352.1 pypi_0 pypi
olefile 0.46 py_0
opencv-python 4.4.0.44 pypi_0 pypi
openssl 1.1.1h he774522_0
pathlib 1.0.1 py_1
pillow 7.2.0 py38hcc1f983_0
pip 20.2.3 py38_0
psutil 5.7.2 py38he774522_0
pyparsing 2.4.7 pypi_0 pypi
python 3.8.5 h5fd99cc_1
python-dateutil 2.8.1 pypi_0 pypi
python_abi 3.8 1_cp38 conda-forge
pywin32 227 py38he774522_1
scikit-learn 0.23.2 py38h47e9c7a_0
scipy 1.5.0 py38h9439919_0
setuptools 49.6.0 py38_1
six 1.15.0 py_0
sqlite 3.33.0 h2a8f88b_0
threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.10 he774522_0
tqdm 4.49.0 py_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_3
wheel 0.35.1 py_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: unsharp_mask
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
--------- 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
Re: Manual installation of tensorflow after using Windows installer?
Posted: Sun Oct 04, 2020 1:44 am
by torzdf
Your GPU is too old for the latest Faceswap, but you can still use the 1.0 release.
Follow the uninstall instructions here:
app.php/faqpage#f1r2
and install version 1.0:
https://github.com/deepfakes/faceswap/r ... tag/v1.0.0