As a side note:
Also, just noticed that the dlib wheel file also does not work.
got some time tomorrow and will do more testing of my environment
Also, just noticed that the dlib wheel file also does not work.
2024-09-28 21:41:26.603
F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vscodeformer\__init__.py:98: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
module.load_state_dict(torch.load(model_path, map_location="cpu")["params_ema"])
F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vscodeformer\__init__.py:98: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
module.load_state_dict(torch.load(model_path, map_location="cpu")["params_ema"])
2024-09-28 21:41:26.826
Failed to evaluate the script:
Python exception: cannot access local variable 'dlib' where it is not associated with a value
Traceback (most recent call last):
File "src\\cython\\vapoursynth.pyx", line 3387, in vapoursynth._vpy_evaluate
File "src\\cython\\vapoursynth.pyx", line 3388, in vapoursynth._vpy_evaluate
File "J:\tmp\tempPreviewVapoursynthFile21_41_23_246.vpy", line 73, in
clip = CodeFormer(clip=clip, upscale=1, detector=1, weight=1.000, num_streams=3) # 720x576
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch\utils\_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vscodeformer\__init__.py", line 103, in codeformer
FaceRestoreHelper(upscale, det_model=detection_model, use_parse=True, device=device) for _ in range(num_streams)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vscodeformer\face_restoration_helper.py", line 113, in __init__
self.face_detector, self.shape_predictor_5 = self.init_dlib()
^^^^^^^^^^^^^^^^
File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vscodeformer\face_restoration_helper.py", line 173, in init_dlib
face_detector = dlib.cnn_face_detection_model_v1(detection_path)
^^^^
UnboundLocalError: cannot access local variable 'dlib' where it is not associated with a value