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View Code? Open in Web Editor NEWA script to make it easy to swap faces in videos using the faceswap library, and YouTube videos.
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how to use the faceit = FaceIt('fallon_to_oliver', 'fallon', 'oliver')
Setup your model and training data in code, e.g.:
Create the model with params: model name, person A name, person B name.
faceit = FaceIt('fallon_to_oliver', 'fallon', 'oliver')
Add any number of videos for person A by specifying the YouTube url of the video.
faceit.add_video('fallon', 'fallon_emmastone.mp4', 'https://www.youtube.com/watch?v=bLBSoC_2IY8')
faceit.add_video('fallon', 'fallon_single.mp4', 'https://www.youtube.com/watch?v=xfFVuXN0FSI')
faceit.add_video('fallon', 'fallon_sesamestreet.mp4', 'https://www.youtube.com/watch?v=SHogg7pJI_M')
Do the same for person B.
faceit.add_video('oliver', 'oliver_trumpcard.mp4', 'https://www.youtube.com/watch?v=JlxQ3IUWT0I')
faceit.add_video('oliver', 'oliver_taxreform.mp4', 'https://www.youtube.com/watch?v=g23w7WPSaU8')
faceit.add_video('oliver', 'oliver_zazu.mp4', 'https://www.youtube.com/watch?v=Y0IUPwXSQqg')
Thanks
When i try to run preprocessing i got ModuleNotFoundError
Traceback (most recent call last):
File "faceit.py", line 19, in
from scripts.extract import ExtractTrainingData
ModuleNotFoundError: No module named 'scripts.extract'
How much time does this face swap take? Quick, can you send more results of face changing
How much time does this face swap take? Quick, can you send more results of face changing
PLEASE HELP : NO MODULE named 'lib.utils'
When i run faceit.py i get this error:
Anyone knows why?
I have installed lib package but maybe i have to install something else?
thanks a lot.
import faceswap issue
When I run the faceit.py, it says
No module named 'lib.utils'
I tried to change the sys.path.append(‘’) to my path but it still doesn’t work. Do you mind showing me how you make it work or where do I make it wrong?
OSError: [Errno 17] File exists: '/faceit/data/processed/fallon_mom.mp4_faces'
[extract-faces] about to extract faces for data/processed/fallon_mom.mp4_faces
Input Directory: /media/killwithme/Ubuntu extended/projects/faceit/data/processed/fallon_mom.mp4_frames
Output Directory: /media/killwithme/Ubuntu extended/projects/faceit/data/processed/fallon_mom.mp4_faces
Starting, this may take a while...
Traceback (most recent call last):
File "faceit.py", line 362, in
faceit.preprocess()
File "faceit.py", line 172, in preprocess
self.extract_faces()
File "faceit.py", line 79, in extract_faces
self._process_media(self._extract_faces)
File "faceit.py", line 88, in _process_media
func(person, video)
File "faceit.py", line 153, in _extract_faces
self._faceswap.extract(self._video_frames_path(video), video_faces_dir, self._people[person]['faces'])
File "faceit.py", line 310, in extract
self._run_script(args_str)
File "faceit.py", line 324, in _run_script
args.func(args)
File "faceswap/lib/cli.py", line 42, in process_arguments
self.output_dir = get_folder(self.arguments.output_dir)
File "faceswap/lib/utils.py", line 11, in get_folder
output_dir.mkdir(parents=True)
File "/home/killwithme/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pathlib.py", line 1106, in mkdir
self._accessor.mkdir(self, mode)
File "/home/killwithme/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pathlib.py", line 346, in wrapped
return strfunc(str(pathobj), *args)
OSError: [Errno 17] File exists: '/media/killwithme/Ubuntu extended/projects/faceit/data/processed/fallon_mom.mp4_faces'
Can i use mp4 instead of youtube link?
I wanna ask if it works if i preprocess mp4 to another mp4 not a youtube link
ModuleNotFoundError: No module named 'lib.utils' from colab Environment for faceit as deepfake project
i am trying to test the faceit by colab google via this link:
but when i try o install this part of its code:
import faceit
# Create the model with params: model name, person A name, person B name.
faceit = FaceIt('fallon_to_oliver', 'fallon', 'oliver')
# Add any number of videos for person A by specifying the YouTube url of the video.
faceit.add_video('fallon', 'fallon_emmastone1.mp4', 'https://www.youtube.com/watch?v=9p5_6eicatI')
faceit.add_video('fallon', 'fallon_single1.mp4', 'https://www.youtube.com/watch?v=bEQl6Pt-654')
faceit.add_video('fallon', 'fallon_sesamestreet1.mp4', 'https://www.youtube.com/watch?v=72ElvvAjvHc')
# Do the same for person B.
faceit.add_video('oliver', 'oliver_trumpcard1.mp4', 'https://www.youtube.com/watch?v=jZjmlJPJgug')
faceit.add_video('oliver', 'oliver_taxreform1.mp4', 'https://www.youtube.com/watch?v=z4gBMw64aqk')
faceit.add_video('oliver', 'oliver_zazu1.mp4', 'https://www.youtube.com/watch?v=1f2iawp0y5Y')
i get this erroro:
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-60-5b08ef1ca42e> in <module>()
----> 1 import faceit
2 # Create the model with params: model name, person A name, person B name.
3 faceit = FaceIt('fallon_to_oliver', 'fallon', 'oliver')
4
5 # Add any number of videos for person A by specifying the YouTube url of the video.
/content/faceit/faceit.py in <module>()
16 sys.path.append('faceswap')
17
---> 18 from lib.utils import FullHelpArgumentParser
19 from scripts.extract import ExtractTrainingData
20 from scripts.train import TrainingProcessor
ModuleNotFoundError: No module named 'lib.utils'
---------------------------------------------------------------------------
NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.
To view examples of installing some common dependencies, click the
"Open Examples" button below.
---------------------------------------------------------------------------
So i have tried to use some old version of faceswap ( the 1 version in my GitHub repo):
!git clone http://github.com/So-AI-love/Deepface-faceswap.git
and try install faceswap by myself like this:
%cd 'Deepface-faceswap'
!python setup.py build_ext --inplace
, or try install different Linux util library by this command:
!sudo apt-get update -y
!sudo apt-get install -y staden-io-lib-utils
!sudo apt-get install python.lib.utils
!sudo apt install python3-darts.lib.utils.lru
But it was not successful.
I would appropriate, any help to solve it.
Asked also here:
update the import
The original import code in faceit.py was
from moviepy.video.fx.all import crop
But the IDE says it has something wrong with it.
So I search online and find that it should be updated to
from moviepy.video.fx.crop import crop
And it works.
Another solution is displayed in the documentation like
from moviepy.video.fx.scroll import crop newclip = myclip.fx( vfx.crop, x1=15)
But I haven't tried this one.
which library shoudld i chice?
Dear Author:
Envirment:windows10+splider(ancanda)
Here is my problem:I am not sure which library installed on mo computer even i read the Document adout CUDA(https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html#verify-you-have-cuda-enabled-system),so, I should install the compiler CUDA or the part of the list pachage?
RuntimeError: Error while calling cudnnConvolutionForward
When I try to run recognition I getting this:
File "faceswap/lib/FaceFilter.py", line 9, in init
self.encoding = face_recognition.face_encodings(image)[0] # Note: we take only first face, so the reference file should only contain one face.
File "/usr/local/lib/python3.6/dist-packages/face_recognition/api.py", line 210, in face_encodings
return [np.array(face_encoder.compute_face_descriptor(face_image, raw_landmark_set, num_jitters)) for raw_landmark_set in raw_landmarks]
File "/usr/local/lib/python3.6/dist-packages/face_recognition/api.py", line 210, in
return [np.array(face_encoder.compute_face_descriptor(face_image, raw_landmark_set, num_jitters)) for raw_landmark_set in raw_landmarks]
RuntimeError: Error while calling cudnnConvolutionForward( context(), &alpha, descriptor(data), data.device(), (const cudnnFilterDescriptor_t)filter_handle, filters.device(), (const cudnnConvolutionDescriptor_t)conv_handle, (cudnnConvolutionFwdAlgo_t)forward_algo, forward_workspace, forward_workspace_size_in_bytes, &beta, descriptor(output), output.device()) in file /tmp/pip-wheel-b9ck8go0/dlib/dlib/cuda/cudnn_dlibapi.cpp:1004. code: 8, reason: CUDNN_STATUS_EXECUTION_FAILED
GAN Model Weights
I'm willing to transfer your model.
Is there a way you could share your model weights ?
faceit.py convert throws error if imagemagick not installed (if running GAN model)
Running faceit.py convert throws error if ImageMagick is not installed. moviepy states that ImageMagick is required for writing text, and more specifically is required for TextClip. Suggest updating requirements.txt or making text optional.
(tensorflow_p36) ubuntu@instance-1:~/GAN/faceit$ python3.6 faceit.py convert stark_to_hulk stark_suitup.mp4 --start 40 --duration 55 --side-by-side --use-gan --face-filter --width 800
Using TensorFlow backend.
Loading Model from Model_GAN plugin...
Discriminator models loaded.
Generator models loaded.
Loading Convert from Convert_GAN plugin...
Traceback (most recent call last):
File "/home/ubuntu/miniconda3/envs/tensorflow_p36/lib/python3.6/site-packages/moviepy/video/VideoClip.py", line 1164, in __init__
subprocess_call(cmd, verbose=False)
File "/home/ubuntu/miniconda3/envs/tensorflow_p36/lib/python3.6/site-packages/moviepy/tools.py", line 42, in subprocess_call
proc = sp.Popen(cmd, **popen_params)
File "/home/ubuntu/miniconda3/envs/tensorflow_p36/lib/python3.6/subprocess.py", line 709, in __init__
restore_signals, start_new_session)
File "/home/ubuntu/miniconda3/envs/tensorflow_p36/lib/python3.6/subprocess.py", line 1344, in _execute_child
raise child_exception_type(errno_num, err_msg, err_filename)
FileNotFoundError: [Errno 2] No such file or directory: 'unset': 'unset'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "faceit.py", line 365, in <module>
faceit.convert(args.video, duration = args.duration, swap_model = args.swap_model, face_filter = args.face_filter, start_time = args.start_time, use_gan = args.use_gan, photos = args.photos, crop_x = args.crop_x, width = args.width, side_by_side = args.side_by_side)
File "faceit.py", line 274, in convert
video = add_caption("Original", video)
File "faceit.py", line 269, in add_caption
text = (TextClip(caption, font='Amiri-regular', color='white', fontsize=80).
File "/home/ubuntu/miniconda3/envs/tensorflow_p36/lib/python3.6/site-packages/moviepy/video/VideoClip.py", line 1173, in __init__
raise IOError(error)
OSError: MoviePy Error: creation of None failed because of the following error:
[Errno 2] No such file or directory: 'unset': 'unset'.
.This error can be due to the fact that ImageMagick is not installed on your computer, or (for Windows users) that you didn't specify the path to the ImageMagick binary in file conf.py, or that the path you specified is incorrect
Aborted (core dumped)
I am getting the following error when running the train script.
I am using faceIT from the FaceIT-Live repository.
I would like to know if anyone faced the same issue or if you have any idea what is going wrong.
Kind regards
Using TensorFlow backend.
WARNING:tensorflow:From /opt/conda/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1264: calling reduce_prod (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
WARNING:tensorflow:From /opt/conda/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1349: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
Failed loading existing training data.
Unable to open file (truncated file: eof = 203175792, sblock->base_addr = 0, stored_eoa = 203176624)
Loading Trainer from Model_Original plugin...
Starting. Press "Enter" to stop training and save model
2020-01-07 09:51:15.190757: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2020-01-07 09:51:15.191228: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:895] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-01-07 09:51:15.191603: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1105] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.582
pciBusID: 0000:01:00.0
totalMemory: 10.91GiB freeMemory: 10.73GiB
2020-01-07 09:51:15.249092: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:895] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-01-07 09:51:15.249482: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1105] Found device 1 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.582
pciBusID: 0000:02:00.0
totalMemory: 10.92GiB freeMemory: 10.77GiB
2020-01-07 09:51:15.249523: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Device peer to peer matrix
2020-01-07 09:51:15.249556: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1126] DMA: 0 1
2020-01-07 09:51:15.249566: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1136] 0: Y N
2020-01-07 09:51:15.249573: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1136] 1: N Y
2020-01-07 09:51:15.249582: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1195] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-01-07 09:51:15.249590: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1195] Creating TensorFlow device (/device:GPU:1) -> (device: 1, name: GeForce GTX 1080 Ti, pci bus id: 0000:02:00.0, compute capability: 6.1)
: cannot connect to X server localhost:10.0: 0.20013
Not a datatype (not a datatype)
*** Error in `python': double free or corruption (fasttop): 0x00007f6580ada520 ***
======= Backtrace: =========
/lib/x86_64-linux-gnu/libc.so.6(+0x777e5)[0x7f6c817597e5]
/lib/x86_64-linux-gnu/libc.so.6(+0x8037a)[0x7f6c8176237a]
/lib/x86_64-linux-gnu/libc.so.6(cfree+0x4c)[0x7f6c8176653c]
/opt/conda/lib/python3.6/site-packages/h5py/.libs/libhdf5-18d08926.so.10.2.1(H5FL_garbage_coll+0x1af)[0x7f6c0dbae63f]
/opt/conda/lib/python3.6/site-packages/h5py/.libs/libhdf5-18d08926.so.10.2.1(H5FL_term_interface+0x9)[0x7f6c0dbaf869]
/opt/conda/lib/python3.6/site-packages/h5py/.libs/libhdf5-18d08926.so.10.2.1(+0x382a5)[0x7f6c0db212a5]
/lib/x86_64-linux-gnu/libc.so.6(+0x39ff8)[0x7f6c8171bff8]
/lib/x86_64-linux-gnu/libc.so.6(+0x3a045)[0x7f6c8171c045]
/opt/conda/lib/python3.6/site-packages/cv2/.libs/libQtGui-6d0f14dd.so.4.8.7(+0x27bf97)[0x7f6c76f66f97]
/opt/conda/lib/python3.6/site-packages/cv2/.libs/libQtGui-6d0f14dd.so.4.8.7(_ZN19QApplicationPrivate9constructEP9_XDisplaymm+0xc8)[0x7f6c76ef65d8]
/opt/conda/lib/python3.6/site-packages/cv2/.libs/libQtGui-6d0f14dd.so.4.8.7(_ZN12QApplicationC2ERiPPci+0x5f)[0x7f6c76ef684f]
/opt/conda/lib/python3.6/site-packages/cv2/cv2.cpython-36m-x86_64-linux-gnu.so(+0xc24468)[0x7f6c7aa78468]
/opt/conda/lib/python3.6/site-packages/cv2/cv2.cpython-36m-x86_64-linux-gnu.so(+0xc309fd)[0x7f6c7aa849fd]
/opt/conda/lib/python3.6/site-packages/cv2/cv2.cpython-36m-x86_64-linux-gnu.so(+0xc1b833)[0x7f6c7aa6f833]
/opt/conda/lib/python3.6/site-packages/cv2/cv2.cpython-36m-x86_64-linux-gnu.so(+0x1eea15)[0x7f6c7a042a15]
python(_PyCFunction_FastCallDict+0x154)[0x55ae1f20c364]
python(+0x19eebc)[0x55ae1f29eebc]
python(_PyEval_EvalFrameDefault+0x30a)[0x55ae1f2c062a]
python(+0x198b8b)[0x55ae1f298b8b]
python(+0x19ef95)[0x55ae1f29ef95]
python(_PyEval_EvalFrameDefault+0x30a)[0x55ae1f2c062a]
python(+0x198b8b)[0x55ae1f298b8b]
python(+0x19ef95)[0x55ae1f29ef95]
python(_PyEval_EvalFrameDefault+0x30a)[0x55ae1f2c062a]
python(+0x198b8b)[0x55ae1f298b8b]
python(+0x19ef95)[0x55ae1f29ef95]
python(_PyEval_EvalFrameDefault+0x30a)[0x55ae1f2c062a]
python(+0x197f24)[0x55ae1f297f24]
python(+0x198dc1)[0x55ae1f298dc1]
python(+0x19ef95)[0x55ae1f29ef95]
python(_PyEval_EvalFrameDefault+0x30a)[0x55ae1f2c062a]
python(+0x197f24)[0x55ae1f297f24]
python(+0x198dc1)[0x55ae1f298dc1]
python(+0x19ef95)[0x55ae1f29ef95]
python(_PyEval_EvalFrameDefault+0x30a)[0x55ae1f2c062a]
python(PyEval_EvalCodeEx+0x329)[0x55ae1f2998d9]
python(PyEval_EvalCode+0x1c)[0x55ae1f29a67c]
python(+0x214ce4)[0x55ae1f314ce4]
python(PyRun_FileExFlags+0xa1)[0x55ae1f3150e1]
python(PyRun_SimpleFileExFlags+0x1c4)[0x55ae1f3152e4]
python(Py_Main+0x5ff)[0x55ae1f318daf]
python(main+0xee)[0x55ae1f1df8be]
/lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xf0)[0x7f6c81702830]
python(+0x1c70da)[0x55ae1f2c70da]
======= Memory map: ========
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200200000-200400000 rw-s 00000000 00:06 493 /dev/nvidiactl
200400000-202400000 rw-s 00000000 00:06 493 /dev/nvidiactl
202400000-205400000 rw-s 00000000 00:06 493 /dev/nvidiactl
205400000-206000000 ---p 00000000 00:00 0
206000000-206200000 rw-s 00000000 00:06 493 /dev/nvidiactl
206200000-206400000 rw-s 00000000 00:06 493 /dev/nvidiactl
206400000-206600000 rw-s 206400000 00:06 496 /dev/nvidia-uvm
206600000-206800000 rw-s 00000000 00:06 493 /dev/nvidiactl
206800000-206a00000 ---p 00000000 00:00 0
206a00000-206c00000 rw-s 00000000 00:06 493 /dev/nvidiactl
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207200000-209200000 rw-s 00000000 00:06 493 /dev/nvidiactl
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20c200000-20ce00000 ---p 00000000 00:00 0
20ce00000-20d000000 rw-s 00000000 00:06 493 /dev/nvidiactl
20d000000-20d200000 rw-s 00000000 00:06 493 /dev/nvidiactl
20d200000-20d400000 rw-s 20d200000 00:06 496 /dev/nvidia-uvm
20d400000-20d600000 rw-s 00000000 00:06 493 /dev/nvidiactl
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7f6c7e85e000-7f6c7e85f000 r--p 00006000 00:81 1850 /opt/conda/lib/python3.6/lib-dynload/zlib.cpython-36m-x86_64-linux-gnu.so
7f6c7e85f000-7f6c7e861000 rw-p 00007000 00:81 1850 /opt/conda/lib/python3.6/lib-dynload/zlib.cpython-36m-x86_64-linux-gnu.so
7f6c7e861000-7f6c7e8e1000 rw-p 00000000 00:00 0
7f6c7e8e1000-7f6c7e8e8000 r-xp 00000000 00:81 1851 /opt/conda/lib/python3.6/lib-dynload/select.cpython-36m-x86_64-linux-gnu.so
7f6c7e8e8000-7f6c7eae7000 ---p 00007000 00:81 1851 /opt/conda/lib/python3.6/lib-dynload/select.cpython-36m-x86_64-linux-gnu.so
7f6c7eae7000-7f6c7eae8000 r--p 00006000 00:81 1851 /opt/conda/lib/python3.6/lib-dynload/select.cpython-36m-x86_64-linux-gnu.so
7f6c7eae8000-7f6c7eaea000 rw-p 00007000 00:81 1851 /opt/conda/lib/python3.6/lib-dynload/select.cpython-36m-x86_64-linux-gnu.so
7f6c7eaea000-7f6c7eaed000 r-xp 00000000 00:81 1846 /opt/conda/lib/python3.6/lib-dynload/_posixsubprocess.cpython-36m-x86_64-linux-gnu.so
7f6c7eaed000-7f6c7ecec000 ---p 00003000 00:81 1846 /opt/conda/lib/python3.6/lib-dynload/_posixsubprocess.cpython-36m-x86_64-linux-gnu.so
7f6c7ecec000-7f6c7eced000 r--p 00002000 00:81 1846 /opt/conda/lib/python3.6/lib-dynload/_posixsubprocess.cpython-36m-x86_64-linux-gnu.so
7f6c7eced000-7f6c7ecee000 rw-p 00003000 00:81 1846 /opt/conda/lib/python3.6/lib-dynload/_posixsubprocess.cpython-36m-x86_64-linux-gnu.so
7f6c7ecee000-7f6c7ecf2000 r-xp 00000000 00:81 1812 /opt/conda/lib/python3.6/lib-dynload/termios.cpython-36m-x86_64-linux-gnu.so
7f6c7ecf2000-7f6c7eef2000 ---p 00004000 00:81 1812 /opt/conda/lib/python3.6/lib-dynload/termios.cpython-36m-x86_64-linux-gnu.so
7f6c7eef2000-7f6c7eef3000 r--p 00004000 00:81 1812 /opt/conda/lib/python3.6/lib-dynload/termios.cpython-36m-x86_64-linux-gnu.so
7f6c7eef3000-7f6c7eef5000 rw-p 00005000 00:81 1812 /opt/conda/lib/python3.6/lib-dynload/termios.cpython-36m-x86_64-linux-gnu.so
7f6c7eef5000-7f6c7ef35000 rw-p 00000000 00:00 0
7f6c7ef35000-7f6c7ef3c000 r-xp 00000000 00:81 1953 /opt/conda/lib/libffi.so.6.0.4
7f6c7ef3c000-7f6c7f13c000 ---p 00007000 00:81 1953 /opt/conda/lib/libffi.so.6.0.4
7f6c7f13c000-7f6c7f13d000 r--p 00007000 00:81 1953 /opt/conda/lib/libffi.so.6.0.4
7f6c7f13d000-7f6c7f13e000 rw-p 00008000 00:81 1953 /opt/conda/lib/libffi.so.6.0.4
7f6c7f13e000-7f6c7f15c000 r-xp 00000000 00:81 1853 /opt/conda/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so
7f6c7f15c000-7f6c7f35c000 ---p 0001e000 00:81 1853 /opt/conda/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so
7f6c7f35c000-7f6c7f35d000 r--p 0001e000 00:81 1853 /opt/conda/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so
7f6c7f35d000-7f6c7f361000 rw-p 0001f000 00:81 1853 /opt/conda/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so
7f6c7f361000-7f6c7f377000 r-xp 00000000 00:81 1948 /opt/conda/lib/libz.so.1.2.11
7f6c7f377000-7f6c7f576000 ---p 00016000 00:81 1948 /opt/conda/lib/libz.so.1.2.11
7f6c7f576000-7f6c7f577000 r--p 00015000 00:81 1948 /opt/conda/lib/libz.so.1.2.11
7f6c7f577000-7f6c7f578000 rw-p 00016000 00:81 1948 /opt/conda/lib/libz.so.1.2.11
7f6c7f578000-7f6c7f57e000 r-xp 00000000 00:81 1818 /opt/conda/lib/python3.6/lib-dynload/binascii.cpython-36m-x86_64-linux-gnu.so
7f6c7f57e000-7f6c7f77d000 ---p 00006000 00:81 1818 /opt/conda/lib/python3.6/lib-dynload/binascii.cpython-36m-x86_64-linux-gnu.so
7f6c7f77d000-7f6c7f77e000 r--p 00005000 00:81 1818 /opt/conda/lib/python3.6/lib-dynload/binascii.cpython-36m-x86_64-linux-gnu.so
7f6c7f77e000-7f6c7f77f000 rw-p 00006000 00:81 1818 /opt/conda/lib/python3.6/lib-dynload/binascii.cpython-36m-x86_64-linux-gnu.so
7f6c7f77f000-7f6c7f7ff000 rw-p 00000000 00:00 0
7f6c7f7ff000-7f6c7f803000 r-xp 00000000 00:81 1863 /opt/conda/lib/python3.6/lib-dynload/_random.cpython-36m-x86_64-linux-gnu.so
7f6c7f803000-7f6c7fa02000 ---p 00004000 00:81 1863 /opt/conda/lib/python3.6/lib-dynload/_random.cpython-36m-x86_64-linux-gnu.so
7f6c7fa02000-7f6c7fa03000 r--p 00003000 00:81 1863 /opt/conda/lib/python3.6/lib-dynload/_random.cpython-36m-x86_64-linux-gnu.so
7f6c7fa03000-7f6c7fa04000 rw-p 00004000 00:81 1863 /opt/conda/lib/python3.6/lib-dynload/_random.cpython-36m-x86_64-linux-gnu.so
7f6c7fa04000-7f6c7fa06000 r-xp 00000000 00:81 1848 /opt/conda/lib/python3.6/lib-dynload/_bisect.cpython-36m-x86_64-linux-gnu.so
7f6c7fa06000-7f6c7fc05000 ---p 00002000 00:81 1848 /opt/conda/lib/python3.6/lib-dynload/_bisect.cpython-36m-x86_64-linux-gnu.so
7f6c7fc05000-7f6c7fc06000 r--p 00001000 00:81 1848 /opt/conda/lib/python3.6/lib-dynload/_bisect.cpython-36m-x86_64-linux-gnu.so
7f6c7fc06000-7f6c7fc07000 rw-p 00002000 00:81 1848 /opt/conda/lib/python3.6/lib-dynload/_bisect.cpython-36m-x86_64-linux-gnu.so
7f6c7fc07000-7f6c7fc1d000 r-xp 00000000 00:81 1860 /opt/conda/lib/python3.6/lib-dynload/_sha3.cpython-36m-x86_64-linux-gnu.so
7f6c7fc1d000-7f6c7fe1c000 ---p 00016000 00:81 1860 /opt/conda/lib/python3.6/lib-dynload/_sha3.cpython-36m-x86_64-linux-gnu.so
7f6c7fe1c000-7f6c7fe1d000 r--p 00015000 00:81 1860 /opt/conda/lib/python3.6/lib-dynload/_sha3.cpython-36m-x86_64-linux-gnu.so
7f6c7fe1d000-7f6c7fe1f000 rw-p 00016000 00:81 1860 /opt/conda/lib/python3.6/lib-dynload/_sha3.cpython-36m-x86_64-linux-gnu.so
7f6c7fe1f000-7f6c7fe2b000 r-xp 00000000 00:81 1868 /opt/conda/lib/python3.6/lib-dynload/_blake2.cpython-36m-x86_64-linux-gnu.so
7f6c7fe2b000-7f6c8002b000 ---p 0000c000 00:81 1868 /opt/conda/lib/python3.6/lib-dynload/_blake2.cpython-36m-x86_64-linux-gnu.so
7f6c8002b000-7f6c8002c000 r--p 0000c000 00:81 1868 /opt/conda/lib/python3.6/lib-dynload/_blake2.cpython-36m-x86_64-linux-gnu.so
7f6c8002c000-7f6c8002d000 rw-p 0000d000 00:81 1868 /opt/conda/lib/python3.6/lib-dynload/_blake2.cpython-36m-x86_64-linux-gnu.so
7f6c8002d000-7f6c8009a000 r--p 00000000 00:81 1909 /opt/conda/lib/libcrypto.so.1.0.0
7f6c8009a000-7f6c801c4000 r-xp 0006d000 00:81 1909 /opt/conda/lib/libcrypto.so.1.0.0
7f6c801c4000-7f6c8024b000 r--p 00197000 00:81 1909 /opt/conda/lib/libcrypto.so.1.0.0
7f6c8024b000-7f6c80267000 r--p 0021d000 00:81 1909 /opt/conda/lib/libcrypto.so.1.0.0
7f6c80267000-7f6c80272000 rw-p 00239000 00:81 1909 /opt/conda/lib/libcrypto.so.1.0.0
7f6c80272000-7f6c80276000 rw-p 00000000 00:00 0
7f6c80276000-7f6c8027c000 r-xp 00000000 00:81 1813 /opt/conda/lib/python3.6/lib-dynload/_hashlib.cpython-36m-x86_64-linux-gnu.so
7f6c8027c000-7f6c8047b000 ---p 00006000 00:81 1813 /opt/conda/lib/python3.6/lib-dynload/_hashlib.cpython-36m-x86_64-linux-gnu.so
7f6c8047b000-7f6c8047c000 r--p 00005000 00:81 1813 /opt/conda/lib/python3.6/lib-dynload/_hashlib.cpython-36m-x86_64-linux-gnu.so
7f6c8047c000-7f6c8047d000 rw-p 00006000 00:81 1813 /opt/conda/lib/python3.6/lib-dynload/_hashlib.cpython-36m-x86_64-linux-gnu.so
7f6c8047d000-7f6c80487000 r-xp 00000000 00:81 1829 /opt/conda/lib/python3.6/lib-dynload/math.cpython-36m-x86_64-linux-gnu.so
7f6c80487000-7f6c80687000 ---p 0000a000 00:81 1829 /opt/conda/lib/python3.6/lib-dynload/math.cpython-36m-x86_64-linux-gnu.so
7f6c80687000-7f6c80688000 r--p 0000a000 00:81 1829 /opt/conda/lib/python3.6/lib-dynload/math.cpython-36m-x86_64-linux-gnu.so
7f6c80688000-7f6c8068a000 rw-p 0000b000 00:81 1829 /opt/conda/lib/python3.6/lib-dynload/math.cpython-36m-x86_64-linux-gnu.so
7f6c8068a000-7f6c80694000 r-xp 00000000 00:81 1854 /opt/conda/lib/python3.6/lib-dynload/_struct.cpython-36m-x86_64-linux-gnu.so
7f6c80694000-7f6c80894000 ---p 0000a000 00:81 1854 /opt/conda/lib/python3.6/lib-dynload/_struct.cpython-36m-x86_64-linux-gnu.so
7f6c80894000-7f6c80895000 r--p 0000a000 00:81 1854 /opt/conda/lib/python3.6/lib-dynload/_struct.cpython-36m-x86_64-linux-gnu.so
7f6c80895000-7f6c80897000 rw-p 0000b000 00:81 1854 /opt/conda/lib/python3.6/lib-dynload/_struct.cpython-36m-x86_64-linux-gnu.so
7f6c8089f000-7f6c80a20000 rw-p 00000000 00:00 0
7f6c80a20000-7f6c80a23000 r-xp 00000000 00:81 1808 /opt/conda/lib/python3.6/lib-dynload/_heapq.cpython-36m-x86_64-linux-gnu.so
7f6c80a23000-7f6c80c22000 ---p 00003000 00:81 1808 /opt/conda/lib/python3.6/lib-dynload/_heapq.cpython-36m-x86_64-linux-gnu.so
7f6c80c22000-7f6c80c23000 r--p 00002000 00:81 1808 /opt/conda/lib/python3.6/lib-dynload/_heapq.cpython-36m-x86_64-linux-gnu.so
7f6c80c23000-7f6c80c25000 rw-p 00003000 00:81 1808 /opt/conda/lib/python3.6/lib-dynload/_heapq.cpython-36m-x86_64-linux-gnu.so
7f6c80c25000-7f6c80c65000 rw-p 00000000 00:00 0
7f6c80c65000-7f6c80c66000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c66000-7f6c80c67000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c67000-7f6c80c68000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c68000-7f6c80c69000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c69000-7f6c80c6a000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c6a000-7f6c80c6b000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c6b000-7f6c80c6c000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c6c000-7f6c80c6d000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c6d000-7f6c80c6e000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c6e000-7f6c80c6f000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c6f000-7f6c80c70000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c70000-7f6c80c71000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c71000-7f6c80c72000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c72000-7f6c80c73000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c73000-7f6c80c74000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c74000-7f6c80c75000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c75000-7f6c80c76000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c80c76000-7f6c80c79000 r--p 00000000 00:81 3732 /opt/conda/lib/libgcc_s.so.1
7f6c80c79000-7f6c80c85000 r-xp 00003000 00:81 3732 /opt/conda/lib/libgcc_s.so.1
7f6c80c85000-7f6c80c88000 r--p 0000f000 00:81 3732 /opt/conda/lib/libgcc_s.so.1
7f6c80c88000-7f6c80c89000 r--p 00011000 00:81 3732 /opt/conda/lib/libgcc_s.so.1
7f6c80c89000-7f6c80c8a000 rw-p 00012000 00:81 3732 /opt/conda/lib/libgcc_s.so.1
7f6c80c8a000-7f6c80dca000 rw-p 00000000 00:00 0
7f6c80dca000-7f6c80ed2000 r-xp 00000000 00:81 741 /lib/x86_64-linux-gnu/libm-2.23.so
7f6c80ed2000-7f6c810d1000 ---p 00108000 00:81 741 /lib/x86_64-linux-gnu/libm-2.23.so
7f6c810d1000-7f6c810d2000 r--p 00107000 00:81 741 /lib/x86_64-linux-gnu/libm-2.23.so
7f6c810d2000-7f6c810d3000 rw-p 00108000 00:81 741 /lib/x86_64-linux-gnu/libm-2.23.so
7f6c810d3000-7f6c810da000 r-xp 00000000 00:81 552 /lib/x86_64-linux-gnu/librt-2.23.so
7f6c810da000-7f6c812d9000 ---p 00007000 00:81 552 /lib/x86_64-linux-gnu/librt-2.23.so
7f6c812d9000-7f6c812da000 r--p 00006000 00:81 552 /lib/x86_64-linux-gnu/librt-2.23.so
7f6c812da000-7f6c812db000 rw-p 00007000 00:81 552 /lib/x86_64-linux-gnu/librt-2.23.so
7f6c812db000-7f6c812dd000 r-xp 00000000 00:81 530 /lib/x86_64-linux-gnu/libutil-2.23.so
7f6c812dd000-7f6c814dc000 ---p 00002000 00:81 530 /lib/x86_64-linux-gnu/libutil-2.23.so
7f6c814dc000-7f6c814dd000 r--p 00001000 00:81 530 /lib/x86_64-linux-gnu/libutil-2.23.so
7f6c814dd000-7f6c814de000 rw-p 00002000 00:81 530 /lib/x86_64-linux-gnu/libutil-2.23.so
7f6c814de000-7f6c814e1000 r-xp 00000000 00:81 560 /lib/x86_64-linux-gnu/libdl-2.23.so
7f6c814e1000-7f6c816e0000 ---p 00003000 00:81 560 /lib/x86_64-linux-gnu/libdl-2.23.so
7f6c816e0000-7f6c816e1000 r--p 00002000 00:81 560 /lib/x86_64-linux-gnu/libdl-2.23.so
7f6c816e1000-7f6c816e2000 rw-p 00003000 00:81 560 /lib/x86_64-linux-gnu/libdl-2.23.so
7f6c816e2000-7f6c818a2000 r-xp 00000000 00:81 690 /lib/x86_64-linux-gnu/libc-2.23.so
7f6c818a2000-7f6c81aa2000 ---p 001c0000 00:81 690 /lib/x86_64-linux-gnu/libc-2.23.so
7f6c81aa2000-7f6c81aa6000 r--p 001c0000 00:81 690 /lib/x86_64-linux-gnu/libc-2.23.so
7f6c81aa6000-7f6c81aa8000 rw-p 001c4000 00:81 690 /lib/x86_64-linux-gnu/libc-2.23.so
7f6c81aa8000-7f6c81aac000 rw-p 00000000 00:00 0
7f6c81aac000-7f6c81ac4000 r-xp 00000000 00:81 772 /lib/x86_64-linux-gnu/libpthread-2.23.so
7f6c81ac4000-7f6c81cc3000 ---p 00018000 00:81 772 /lib/x86_64-linux-gnu/libpthread-2.23.so
7f6c81cc3000-7f6c81cc4000 r--p 00017000 00:81 772 /lib/x86_64-linux-gnu/libpthread-2.23.so
7f6c81cc4000-7f6c81cc5000 rw-p 00018000 00:81 772 /lib/x86_64-linux-gnu/libpthread-2.23.so
7f6c81cc5000-7f6c81cc9000 rw-p 00000000 00:00 0
7f6c81cc9000-7f6c81cef000 r-xp 00000000 00:81 759 /lib/x86_64-linux-gnu/ld-2.23.so
7f6c81cef000-7f6c81cf0000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf0000-7f6c81cf1000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf1000-7f6c81cf2000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf2000-7f6c81cf3000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf3000-7f6c81cf4000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf4000-7f6c81cf5000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf5000-7f6c81cf6000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf6000-7f6c81cf7000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf7000-7f6c81cf8000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf8000-7f6c81cf9000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cf9000-7f6c81cfa000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cfa000-7f6c81cfb000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cfb000-7f6c81cfc000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cfc000-7f6c81cfd000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cfd000-7f6c81cfe000 rw-s 00000000 00:06 493 /dev/nvidiactl
7f6c81cfe000-7f6c81cff000 rwxp 00000000 00:00 0
7f6c81cff000-7f6c81d3f000 rw-p 00000000 00:00 0
7f6c81d3f000-7f6c81d66000 r--p 00000000 00:81 879 /usr/lib/locale/C.UTF-8/LC_CTYPE
7f6c81d66000-7f6c81d67000 r--p 00000000 00:81 878 /usr/lib/locale/C.UTF-8/LC_NUMERIC
7f6c81d67000-7f6c81d68000 r--p 00000000 00:81 877 /usr/lib/locale/C.UTF-8/LC_TIME
7f6c81d68000-7f6c81eda000 r--p 00000000 00:81 876 /usr/lib/locale/C.UTF-8/LC_COLLATE
7f6c81eda000-7f6c81edb000 r--p 00000000 00:81 875 /usr/lib/locale/C.UTF-8/LC_MONETARY
7f6c81edb000-7f6c81edc000 r--p 00000000 00:81 874 /usr/lib/locale/C.UTF-8/LC_MESSAGES/SYS_LC_MESSAGES
7f6c81edc000-7f6c81edd000 r--p 00000000 00:81 872 /usr/lib/locale/C.UTF-8/LC_PAPER
7f6c81edd000-7f6c81ede000 r--p 00000000 00:81 871 /usr/lib/locale/C.UTF-8/LC_NAME
7f6c81ede000-7f6c81edf000 r--p 00000000 00:81 870 /usr/lib/locale/C.UTF-8/LC_ADDRESS
7f6c81edf000-7f6c81ee0000 r--p 00000000 00:81 869 /usr/lib/locale/C.UTF-8/LC_TELEPHONE
7f6c81ee0000-7f6c81ee5000 rw-p 00000000 00:00 0
7f6c81ee5000-7f6c81ee6000 r--p 00000000 00:81 868 /usr/lib/locale/C.UTF-8/LC_MEASUREMENT
7f6c81ee6000-7f6c81eed000 r--s 00000000 00:81 867 /usr/lib/x86_64-linux-gnu/gconv/gconv-modules.cache
7f6c81eed000-7f6c81eee000 r--p 00000000 00:81 866 /usr/lib/locale/C.UTF-8/LC_IDENTIFICATION
7f6c81eee000-7f6c81eef000 r--p 00025000 00:81 759 /lib/x86_64-linux-gnu/ld-2.23.so
7f6c81eef000-7f6c81ef0000 rw-p 00026000 00:81 759 /lib/x86_64-linux-gnu/ld-2.23.so
7f6c81ef0000-7f6c81ef1000 rw-p 00000000 00:00 0
7ffdf4593000-7ffdf45b4000 rw-p 00000000 00:00 0 [stack]
7ffdf45d8000-7ffdf45db000 r--p 00000000 00:00 0 [vvar]
7ffdf45db000-7ffdf45dd000 r-xp 00000000 00:00 0 [vdso]
ffffffffff600000-ffffffffff601000 r-xp 00000000 00:00 0 [vsyscall]
Aborted (core dumped)
Causes file access errors on Windows. A fix is provided in the comment.
When running faceit on Windows, I got random handle and access errors in _extract_frames function.
To fix this, I added the following code:
video_clip.close()
right after print('[extract-frames] frames already exist, skipping extraction: {}'.format(video_frames_dir))
and also at the very end of the _extract_frames function.
Yes, it's mostly a Windows issue because it is much more sensitive about accessing open files. On Linux, you generally can access the same file from many processes without any issues. Still, it's a good practice to close a file after you're done processing it.
update the code
Hi,
Hope you are all well !
I was wondering if it is possible to update the code to the latest version of faceswap and cuda 11.3 ?
Thanks for any insights or inputs on that.
Cheers,
Luc Michalski
models/foo_to_bar/encoder.h5 not found error.
$ python3 faceit.py convert foo_bar bar.mp4 --start 0 --duration 10 --side-by-sid
Using TensorFlow backend.
Loading Model from Model_Original plugin...
WARNING:tensorflow:From /home/xiaobai/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1264: calling reduce_prod (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
WARNING:tensorflow:From /home/xiaobai/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1349: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
Failed loading existing training data.
Unable to open file (unable to open file: name = 'models/foo_to_bar/encoder.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)
model Not Found! A valid model must be provided to continue!
$
My system is Ubuntu 17.10
Failed to extract from image. Reason: bad allocation
Running 'python faceit.py preprocess fallon_to_oliver' results in the error:
'Failed to extract from image: C:\projects\faceit\data\processed\fallon _bank.mp4_frames\frame_000.jpg. Reason: bad allocation'
The video download and extraction of frames works correctly. The error occurs when the script tries to extract the faces from the frame images. From what I have tracked down the error happens in the extract.py at the call to 'self.get_faces(image)':
def handleImage(self, filename):
count = 0
image = cv2.imread(filename)
for idx, face in self.get_faces(image):
count = idx
resized_image = self.extractor.extract(image, face, 256)
output_file = get_folder(self.output_dir) / Path(filename).stem
cv2.imwrite(str(output_file) + str(idx) + Path(filename).suffix, resized_image)
return count + 1
Does anyone know why this happens?
Error AssertionError
File "/jet/var/python/lib/python3.6/threading.py", line 916, in _bootstrap_inner
self.run()
File "/jet/var/python/lib/python3.6/threading.py", line 864, in run
self._target(*self._args, **self._kwargs)
File "/jet/prs/workspace/pi/train.py", line 125, in processThread
model = PluginLoader.get_model(trainer)(get_folder(self.arguments.model_dir))
File "/jet/prs/workspace/pi/PluginLoader.py", line 13, in get_model
return PluginLoader.import("Model", "Model{0}".format(name))
File "/jet/prs/workspace/pi/PluginLoader.py", line 22, in _import
module = import(name, globals(), locals(), [], 0)
File "/jet/prs/workspace/pi/Model_Original.py", line 3, in
from keras.models import Model as KerasModel
File "/jet/var/python/lib/python3.6/site-packages/keras/init.py", line 3, in
from . import utils
File "/jet/var/python/lib/python3.6/site-packages/keras/utils/init.py", line 6, in
from . import conv_utils
File "/jet/var/python/lib/python3.6/site-packages/keras/utils/conv_utils.py", line 3, in
from .. import backend as K
File "/jet/var/python/lib/python3.6/site-packages/keras/backend/init.py", line 71, in
assert _backend in {'theano', 'tensorflow', 'cntk'}
AssertionError
r: MoviePy error
I have tried everything but I Still get this:
Any idea how to fix?
"OSError: MoviePy error: failed to read the first frame of video file data/videos/trump_tale.mp4. That might mean that the file is corrupted. That may also mean that you are using a deprecated version of FFMPEG. On Ubuntu/Debian for instance the version in the repos is deprecated. Please update to a recent version from the website."
ERROR: Cannot uninstall 'imageio'.
Hi,
I am trying to install on Ubuntu 19.04 your program by following this instruction:
https://github.com/chenxinhua/faceit_live
But when I run docker-compose build, I get the following error:
ERROR: Cannot uninstall 'imageio'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
Could you please help me solve the issue...? Thanks very much.
Got invalid syntax.
Got this error when I ran the command python faceit.py convert fallon_to_oliver fallon_emmastone.mp4 --start 40 --duration 55 --side-by-side
2018-04-26 00:01:22.499696: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Loading Model from Model_Original plugin...
Traceback (most recent call last):
File "faceit.py", line 369, in
faceit.convert(args.video, duration = args.duration, swap_model = args.swap_model, face_filter = args.face_filter, start_time = args.start_time, photos = args.photos, crop_x = args.crop_x, width = args.width, side_by_side = args.side_by_side)
File "faceit.py", line 212, in convert
model = PluginLoader.get_model(model_name)(Path(self._model_path(use_gan)))
File "faceswap/plugins/PluginLoader.py", line 13, in get_model
return PluginLoader.import("Model", "Model{0}".format(name))
File "faceswap/plugins/PluginLoader.py", line 22, in _import
module = import(name, globals(), locals(), [], 1)
File "faceswap/plugins/Model_Original.py", line 9, in
from lib.ModelAE import ModelAE, TrainerAE
File "faceswap/lib/ModelAE.py", line 64
end='\r')
^
SyntaxError: invalid syntax
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