Hello! Please make it possible to save the final frames to a separate folder during video processing, as it is implemented in SimSwap. This is convenient when you can view a frame if a long video is being processed so as not to waste time if the result turns out to be bad. Or it will give the opportunity to make a GIF from these frames yourself. Thanks!

К сожалению не умею правильно делать пулл-реквесты, поэтому прошу разработчиков поправить или сделать пулл-реквест @AlexanderGroshev

1. В sberbank-ai/sber-swap/utils/inference/masks.py строка 7 lmrks = np.array( lmrks.copy(), dtype=np.int ) нужно исправить на lmrks = np.array( lmrks.copy(), dtype=np.int32) . Это уберёт предупреждения вроде Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations lmrks = np.array( lmrks.copy(), dtype=np.int ) которых реально чересчур много и которые сильно забивают полезный вывод в консоль.
2. В sber-swap/utils/inference/video_processing.py строки 29 и 30 - в os.system(f"ffmpeg -i добавить-v -8, чтобы получилось os.system(f"ffmpeg -v -8 -i {video_with_sound} -vn... Это уберёт вывод работы FFmpeg и сделает вывод в консоль более чище и не будет забивать его лишней информацией.
3. В sber-swap/utils/inference/video_processing.py строка 156 - исправить cv2.VideoWriter_fourcc(*'MP4V') на cv2.VideoWriter_fourcc(*'mp4v') - это решить проблему OpenCV: FFMPEG: tag 0x5634504d/'MP4V' и связанные с ней.

Остальное что нашёл в пулл-реквесте поправил @AlexanderGroshev. Спасибо!

Hello ! When I run from coordinate_reg.image_infer import Handler:

OSError Traceback (most recent call last) ~\AppData\Local\Temp\ipykernel_21280\3719535116.py in ----> 1 from coordinate_reg.image_infer import Handler

~\sber-swap\coordinate_reg\image_infer.py in 2 import numpy as np 3 import os ----> 4 import mxnet as mx 5 from skimage import transform as trans 6 import insightface

~\anaconda3\envs\original\lib\site-packages\mxnet_init_.py in 22 from future import absolute_import 23 ---> 24 from .context import Context, current_context, cpu, gpu, cpu_pinned 25 from . import engine 26 from .base import MXNetError

~\anaconda3\envs\original\lib\site-packages\mxnet\context.py in 22 import warnings 23 import ctypes ---> 24 from .base import classproperty, with_metaclass, _MXClassPropertyMetaClass 25 from .base import _LIB 26 from .base import check_call

~\anaconda3\envs\original\lib\site-packages\mxnet\base.py in 211 version = libinfo.version 212 # library instance of mxnet --> 213 _LIB = _load_lib() 214 215 # type definitions

~\anaconda3\envs\original\lib\site-packages\mxnet\base.py in _load_lib() 202 """Load library by searching possible path.""" 203 lib_path = libinfo.find_lib_path() --> 204 lib = ctypes.CDLL(lib_path[0], ctypes.RTLD_LOCAL) 205 # DMatrix functions 206 lib.MXGetLastError.restype = ctypes.c_char_p

~\anaconda3\envs\original\lib\ctypes_init_.py in init(self, name, mode, handle, use_errno, use_last_error) 354 355 if handle is None: --> 356 self._handle = _dlopen(self._name, mode) 357 else: 358 self._handle = handle

OSError: [WinError 126] Не найден указанный модуль

Hi FaceSwap ! When I run this code:

python inference.py --source_paths {PATH_TO_IMAGE} --target_faces_paths {PATH_TO_IMAGE} --target_video {PATH_TO_VIDEO}

I have the following error:

TypeError: Descriptors cannot not be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are:

1. Downgrade the protobuf package to 3.20.x or lower.
2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).

More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates

Hi FaceSwap,

Please state the correct versions in requirements.txt:

• ERROR: Could not find a version that satisfies the requirement torch==1.6.0+cu101 (from versions: 1.7.1, 1.8.0, 1.8.1, 1.9.0, 1.9.1, 1.10.0, 1.10.1, 1.10.2, 1.11.0, 1.12.0, 1.12.1, 1.13.0) ERROR: No matching distribution found for torch==1.6.0+cu101
• ERROR: Could not find a version that satisfies the requirement torchvision==0.7.0+cu101 (from versions: 0.1.6, 0.1.7, 0.1.8, 0.1.9, 0.2.0, 0.2.1, 0.2.2, 0.2.2.post2, 0.2.2.post3, 0.8.2, 0.9.0, 0.9.1, 0.10.0, 0.10.1, 0.11.0, 0.11.1, 0.11.2, 0.11.3, 0.12.0, 0.13.0, 0.13.1, 0.14.0) ERROR: No matching distribution found for torchvision==0.7.0+cu101
• ERROR: Could not find a version that satisfies the requirement onnxruntime-gpu==1.4.0 (from versions: none) ERROR: No matching distribution found for onnxruntime-gpu==1.4.0
• ERROR: Could not find a version that satisfies the requirement mxnet-cu101mkl (from versions: none) ERROR: No matching distribution found for mxnet-cu101mkl
• ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. conda-repo-cli 1.0.4 requires pathlib, which is not installed. anaconda-project 0.10.1 requires ruamel-yaml, which is not installed.

Hi! How to change mask height or exclude specific parts of face from swapping? There are situations when you need to exclude poorly or incorrectly formed parts of the face or cut the mask in width or height. Please, сan you tell me where in the code this can be changed? Thank you very much for your help!

Hey! Thank you very much for the work done, we hope that the code will continue to be developed and finalized. There is one question. In the description of the --target_faces_paths option, you noted that you can skip this option and then any face in the photo or video will be selected. Unfortunately, the ability to choose whether to use a face from a screenshot or to automatically select any face does not work. If you skip this parameter, then there will always be an error (for a photo or video)

List of source paths:  ['/content/sber-swap/examples/images/elon_musk.jpg']
List of target paths:  ['examples/images/1.png', 'examples/images/2.png', 'examples/images/3.png']
Traceback (most recent call last):
  File "inference.py", line 153, in <module>
    main(args)
  File "inference.py", line 88, in main
    img = crop_face(img, app, args.crop_size)[0]
  File "/content/sber-swap/utils/inference/image_processing.py", line 16, in crop_face
    image, _ = app.get(image_full, crop_size)
  File "/content/sber-swap/insightface_func/face_detect_crop_multi.py", line 58, in get
    metric='default')
  File "/usr/local/lib/python3.7/dist-packages/insightface/model_zoo/scrfd.py", line 204, in detect
    im_ratio = float(img.shape[0]) / img.shape[1]
AttributeError: 'NoneType' object has no attribute 'shape'

You can skip this parameter only if you remove default=['examples/images/1.png', 'examples/images/2.png', 'examples/images/3.png'], nargs='+'. from it. But then, if necessary, the parameter itself will not work ... Add the ability to choose whether to use automatic face selection or from a screenshot from the video.

Привет! Спасибо большое за проделанную работу, надеемся что код и дальше будет развиваться и дорабатываться. Есть один вопрос. В описании опции --target_faces_paths вы отметили что можно пропустить эту опцию и тогда будет выбираться любое лицо на фото или видео. К сожалению возможность выбирать - использовать лицо со скриншота или чтобы автоматически выбиралось любое лицо (если оно всего одно например) не работает. Если скипнуть этот параметр то всегда (для фото или видео) будет ошибка. Скипнуть этот параметр можно только если убрать из него default=['examples/images/1.png', 'examples/images/2.png', 'examples/images/3.png'], nargs='+'. Но тогда если будет нужно - не будет работать сам параметр...Добавьте возможность выбирать, использовать автоматический выбор лица или со скриншота с видео.

Hello! Please accept my congratulations on the publication on IEEE Xplore!) There have been no updates for a long time, do you plan to develop the repository further, or has it lost interest?

Type Error on Colab In Inference Section

TypeError: can't convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint8, and bool.

Hi! If possible, please correct the output of the result in the next update for a cleaner one! There are a lot of warnings that just clog up the useful output on the console. I didn't copy everything, the rest of the output (warnings) is identical. Thanks!

/usr/local/lib/python3.7/dist-packages/kornia/augmentation/augmentation.py:1833: DeprecationWarning: GaussianBlur is no longer maintained and will be removed from the future versions. Please use RandomGaussianBlur instead.
  category=DeprecationWarning,
/usr/local/lib/python3.7/dist-packages/scipy/fft/__init__.py:97: DeprecationWarning: The module numpy.dual is deprecated.  Instead of using dual, use the functions directly from numpy or scipy.
  from numpy.dual import register_func
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/lib/python3.7/dist-packages/scipy/sparse/sputils.py:17: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
  supported_dtypes = [np.typeDict[x] for x in supported_dtypes]

and

Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
 16% 46/289 [00:05<00:09, 25.51it/s]/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
 17% 49/289 [00:05<00:09, 25.90it/s]/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
 18% 52/289 [00:05<00:09, 26.29it/s]/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
 19% 55/289 [00:05<00:08, 26.87it/s]/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
 20% 58/289 [00:05<00:08, 27.16it/s]/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
 21% 61/289 [00:05<00:08, 27.57it/s]/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
 22% 64/289 [00:05<00:08, 25.83it/s]/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )
 23% 67/289 [00:05<00:08, 26.18it/s]/content/sber-swap/utils/inference/masks.py:7: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  lmrks = np.array( lmrks.copy(), dtype=np.int )

$ py -m pip install mxnet Collecting mxnet Using cached mxnet-1.7.0.post2-py2.py3-none-win_amd64.whl (33.1 MB) Collecting numpy<1.17.0,>=1.8.2 Using cached numpy-1.16.6.zip (5.1 MB) Preparing metadata (setup.py): started Preparing metadata (setup.py): finished with status 'done' Collecting requests<2.19.0,>=2.18.4 Using cached requests-2.18.4-py2.py3-none-any.whl (88 kB) Collecting graphviz<0.9.0,>=0.8.1 Using cached graphviz-0.8.4-py2.py3-none-any.whl (16 kB) Collecting certifi>=2017.4.17 Using cached certifi-2022.12.7-py3-none-any.whl (155 kB) Collecting chardet<3.1.0,>=3.0.2 Using cached chardet-3.0.4-py2.py3-none-any.whl (133 kB) Collecting idna<2.7,>=2.5 Using cached idna-2.6-py2.py3-none-any.whl (56 kB) Collecting urllib3<1.23,>=1.21.1 Using cached urllib3-1.22-py2.py3-none-any.whl (132 kB) Installing collected packages: urllib3, idna, chardet, numpy, graphviz, certifi, requests, mxnet WARNING: The script chardetect.exe is installed in 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Scripts' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. Attempting uninstall: numpy Found existing installation: numpy 1.24.0 Uninstalling numpy-1.24.0: Successfully uninstalled numpy-1.24.0 DEPRECATION: numpy is being installed using the legacy 'setup.py install' method, because it does not have a 'pyproject.toml' and the 'wheel' package is not installed. pip 23.1 will enforce this behaviour change. A possible replacement is to enable the '--use-pep517' option. Discussion can be found at https://github.com/pypa/pip/issues/8559 Running setup.py install for numpy: started Running setup.py install for numpy: finished with status 'error' error: subprocess-exited-with-error

Running setup.py install for numpy did not run successfully. exit code: 1

[276 lines of output] Running from numpy source directory.

Note: if you need reliable uninstall behavior, then install with pip instead of using setup.py install:

- `pip install .`       (from a git repo or downloaded source
                         release)
- `pip install numpy`   (last NumPy release on PyPi)

C:\Users\Administrator\AppData\Local\Temp\pip-install-_vqy6jc2\numpy_50df99d6d0ce4aa7b689d7b0148eae3d\numpy\distutils\misc_util.py:476: SyntaxWarning: "is" with a literal. Did you mean "=="? return is_string(s) and ('*' in s or '?' is s) blas_opt_info: blas_mkl_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries mkl_rt not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

blis_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries blis not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

openblas_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries openblas not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']' customize GnuFCompiler Could not locate executable g77 Could not locate executable f77 customize IntelVisualFCompiler Could not locate executable ifort Could not locate executable ifl customize AbsoftFCompiler Could not locate executable f90 customize CompaqVisualFCompiler Found executable C:\Program Files\Git\usr\bin\DF.exe Could not locate executable C:\Program customize IntelItaniumVisualFCompiler Could not locate executable efl customize Gnu95FCompiler Could not locate executable gfortran Could not locate executable f95 customize G95FCompiler Could not locate executable g95 customize IntelEM64VisualFCompiler customize IntelEM64TFCompiler Could not locate executable efort Could not locate executable efc customize PGroupFlangCompiler Could not locate executable flang don't know how to compile Fortran code on platform 'nt' NOT AVAILABLE

atlas_3_10_blas_threads_info: Setting PTATLAS=ATLAS No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries tatlas not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

atlas_3_10_blas_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries satlas not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

atlas_blas_threads_info: Setting PTATLAS=ATLAS No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries ptf77blas,ptcblas,atlas not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

atlas_blas_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries f77blas,cblas,atlas not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

accelerate_info: NOT AVAILABLE

C:\Users\Administrator\AppData\Local\Temp\pip-install-_vqy6jc2\numpy_50df99d6d0ce4aa7b689d7b0148eae3d\numpy\distutils\system_info.py:639: UserWarning: Atlas (http://math-atlas.sourceforge.net/) libraries not found. Directories to search for the libraries can be specified in the numpy/distutils/site.cfg file (section [atlas]) or by setting the ATLAS environment variable. self.calc_info() blas_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries blas not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

C:\Users\Administrator\AppData\Local\Temp\pip-install-_vqy6jc2\numpy_50df99d6d0ce4aa7b689d7b0148eae3d\numpy\distutils\system_info.py:639: UserWarning: Blas (http://www.netlib.org/blas/) libraries not found. Directories to search for the libraries can be specified in the numpy/distutils/site.cfg file (section [blas]) or by setting the BLAS environment variable. self.calc_info() blas_src_info: NOT AVAILABLE

C:\Users\Administrator\AppData\Local\Temp\pip-install-_vqy6jc2\numpy_50df99d6d0ce4aa7b689d7b0148eae3d\numpy\distutils\system_info.py:639: UserWarning: Blas (http://www.netlib.org/blas/) sources not found. Directories to search for the sources can be specified in the numpy/distutils/site.cfg file (section [blas_src]) or by setting the BLAS_SRC environment variable. self.calc_info() NOT AVAILABLE

'svnversion' is not recognized as an internal or external command, operable program or batch file. non-existing path in 'numpy\distutils': 'site.cfg' lapack_opt_info: lapack_mkl_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries mkl_rt not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

openblas_lapack_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries openblas not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

openblas_clapack_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries openblas,lapack not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

atlas_3_10_threads_info: Setting PTATLAS=ATLAS No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries tatlas,tatlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries tatlas,tatlas not found in C:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries tatlas,tatlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs <class 'numpy.distutils.system_info.atlas_3_10_threads_info'> NOT AVAILABLE

atlas_3_10_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries satlas,satlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries satlas,satlas not found in C:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries satlas,satlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs <class 'numpy.distutils.system_info.atlas_3_10_info'> NOT AVAILABLE

atlas_threads_info: Setting PTATLAS=ATLAS No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries ptf77blas,ptcblas,atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries ptf77blas,ptcblas,atlas not found in C:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries ptf77blas,ptcblas,atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs <class 'numpy.distutils.system_info.atlas_threads_info'> NOT AVAILABLE

atlas_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries f77blas,cblas,atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries f77blas,cblas,atlas not found in C:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack_atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries f77blas,cblas,atlas not found in C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs <class 'numpy.distutils.system_info.atlas_info'> NOT AVAILABLE

lapack_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries lapack not found in ['C:\Users\Administrator\AppData\Local\Programs\Python\Python311\lib', 'C:\', 'C:\Users\Administrator\AppData\Local\Programs\Python\Python311\libs'] NOT AVAILABLE

C:\Users\Administrator\AppData\Local\Temp\pip-install-_vqy6jc2\numpy_50df99d6d0ce4aa7b689d7b0148eae3d\numpy\distutils\system_info.py:639: UserWarning: Lapack (http://www.netlib.org/lapack/) libraries not found. Directories to search for the libraries can be specified in the numpy/distutils/site.cfg file (section [lapack]) or by setting the LAPACK environment variable. self.calc_info() lapack_src_info: NOT AVAILABLE

C:\Users\Administrator\AppData\Local\Temp\pip-install-_vqy6jc2\numpy_50df99d6d0ce4aa7b689d7b0148eae3d\numpy\distutils\system_info.py:639: UserWarning: Lapack (http://www.netlib.org/lapack/) sources not found. Directories to search for the sources can be specified in the numpy/distutils/site.cfg file (section [lapack_src]) or by setting the LAPACK_SRC environment variable. self.calc_info() NOT AVAILABLE

C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\setuptools_distutils\dist.py:264: UserWarning: Unknown distribution option: 'define_macros' warnings.warn(msg) running install C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\setuptools\command\install.py:34: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools. warnings.warn( running build running config_cc unifing config_cc, config, build_clib, build_ext, build commands --compiler options running config_fc unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options running build_src build_src building py_modules sources creating build creating build\src.win-amd64-3.1 creating build\src.win-amd64-3.1\numpy creating build\src.win-amd64-3.1\numpy\distutils building library "npymath" sources No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/ [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip. Rolling back uninstall of numpy Moving to c:\users\administrator\appdata\local\programs\python\python311\lib\site-packages\numpy-1.24.0.dist-info
from C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages~umpy-1.24.0.dist-info Moving to c:\users\administrator\appdata\local\programs\python\python311\lib\site-packages\numpy
from C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages~umpy Moving to c:\users\administrator\appdata\local\programs\python\python311\scripts\f2py.exe from C:\Users\Administrator\AppData\Local\Temp\pip-uninstall-a_fvs93n\f2py.exe error: legacy-install-failure

Encountered error while trying to install package.

numpy

note: This is an issue with the package mentioned above, not pip. hint: See above for output from the failure.

I cant get the versions working on my side. I tried some of the version but none of them working

File "C:\Users\Administrator\Desktop\Ghost\sber-swap\coordinate_reg\image_infer.py", line 4, in import mxnet as mx ModuleNotFoundError: No module named 'mxnet'

ANYONE HAS a solution for this error?

Igot this error message. whats seems to be the problem

Traceback (most recent call last): File "C:\Users\Administrator\Desktop\ghost\preprocess_vgg.py", line 5, in from insightface_func.face_detect_crop_single import Face_detect_crop File "C:\Users\Administrator\Desktop\ghost\insightface_func\face_detect_crop_single.py", line 8, in from insightface.model_zoo import model_zoo File "C:\Users\Administrator\AppData\Local\Programs\Python\Python39\lib\site-packages\insightface_init_.py", line 16, in from . import model_zoo File "C:\Users\Administrator\AppData\Local\Programs\Python\Python39\lib\site-packages\insightface\model_zoo_init_.py", line 1, in from .model_zoo import get_model File "C:\Users\Administrator\AppData\Local\Programs\Python\Python39\lib\site-packages\insightface\model_zoo\model_zoo.py", line 11, in from .arcface_onnx import * File "C:\Users\Administrator\AppData\Local\Programs\Python\Python39\lib\site-packages\insightface\model_zoo\arcface_onnx.py", line 10, in import onnx File "C:\Users\Administrator\AppData\Local\Programs\Python\Python39\lib\site-packages\onnx_init_.py", line 20, in import onnx.helper # noqa File "C:\Users\Administrator\AppData\Local\Programs\Python\Python39\lib\site-packages\onnx\helper.py", line 17, in from onnx import mapping File "C:\Users\Administrator\AppData\Local\Programs\Python\Python39\lib\site-packages\onnx\mapping.py", line 27, in int(TensorProto.STRING): np.dtype(np.object) File "C:\Users\Administrator\AppData\Local\Programs\Python\Python39\lib\site-packages\numpy_init_.py", line 284, in getattr raise AttributeError("module {!r} has no attribute " AttributeError: module 'numpy' has no attribute 'object'

ANd this

Traceback (most recent call last): File "C:\Users\Administrator\Desktop\ghost\train.py", line 27, in from utils.training.detector import detect_landmarks, paint_eyes File "C:\Users\Administrator\Desktop\ghost\utils\training\detector.py", line 6, in from AdaptiveWingLoss.utils.utils import get_preds_fromhm ModuleNotFoundError: No module named 'AdaptiveWingLoss.utils'

Trying to run the repo on Windows 10. Installed mxnet-cu102-2.0.0b20201108.

The code execution stops on line 115 in image_infer.py file model = mx.mod.Module(symbol=sym, context=ctx, label_names=None)

Full error: AttributeError: module 'mxnet' has no attribute 'mod'

Running the colab example locally, I get this result:

As you can see, this is just the source image again with no swap. Here is my run log: SBER Example.txt

Why is no actual swapping occurring?

Not an issue but I think this could come handy for someone :)

Dockerfile

FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04

RUN apt-get update && apt-get install -y software-properties-common
RUN add-apt-repository ppa:deadsnakes/ppa -y
RUN apt-get update && apt-get install -y \
    wget \
    python3.8 \
    python3.8-distutils \
    ffmpeg \
    libsm6 \
    libxext6

RUN wget https://bootstrap.pypa.io/get-pip.py

RUN python3.8 get-pip.py

COPY requirements.txt requirements.txt

RUN pip install -r requirements.txt

python3.8 inference.py --target_path {PATH_TO_IMAGE} --image_to_image True