Describe the bug
I get the following error on the command line if I try to use the "restore faces" option.
/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead.
warnings.warn(
/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=None`.
warnings.warn(msg)
ERROR: Exception in ASGI application
Traceback (most recent call last):
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/uvicorn/protocols/http/h11_impl.py", line 404, in run_asgi
result = await app( # type: ignore[func-returns-value]
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/uvicorn/middleware/proxy_headers.py", line 78, in __call__
return await self.app(scope, receive, send)
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/fastapi/applications.py", line 269, in __call__
await super().__call__(scope, receive, send)
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/starlette/applications.py", line 124, in __call__
await self.middleware_stack(scope, receive, send)
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/starlette/middleware/errors.py", line 184, in __call__
raise exc
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/starlette/middleware/errors.py", line 162, in __call__
await self.app(scope, receive, _send)
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/starlette/exceptions.py", line 93, in __call__
raise exc
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/starlette/exceptions.py", line 82, in __call__
await self.app(scope, receive, sender)
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/fastapi/middleware/asyncexitstack.py", line 21, in __call__
raise e
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/fastapi/middleware/asyncexitstack.py", line 18, in __call__
await self.app(scope, receive, send)
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/starlette/routing.py", line 670, in __call__
await route.handle(scope, receive, send)
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/starlette/routing.py", line 266, in handle
await self.app(scope, receive, send)
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/starlette/routing.py", line 65, in app
response = await func(request)
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/fastapi/routing.py", line 231, in app
raw_response = await run_endpoint_function(
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/fastapi/routing.py", line 160, in run_endpoint_function
return await dependant.call(**values)
File "/home/mmarco/stable-diffusion-krita-plugin/krita_server.py", line 185, in f_txt2img
output_images, info, html = modules.txt2img.txt2img(
File "/home/mmarco/stable-diffusion-krita-plugin/modules/txt2img.py", line 42, in txt2img
processed = process_images(p)
File "/home/mmarco/stable-diffusion-krita-plugin/modules/processing.py", line 359, in process_images
x_sample = modules.face_restoration.restore_faces(x_sample)
File "/home/mmarco/stable-diffusion-krita-plugin/modules/face_restoration.py", line 19, in restore_faces
return face_restorer.restore(np_image)
File "/home/mmarco/stable-diffusion-krita-plugin/modules/codeformer_model.py", line 79, in restore
self.face_helper.get_face_landmarks_5(only_center_face=False, resize=640, eye_dist_threshold=5)
File "/home/mmarco/stable-diffusion-krita-plugin/repositories/CodeFormer/facelib/utils/face_restoration_helper.py", line 151, in get_face_landmarks_5
bboxes = self.face_det.detect_faces(input_img)
File "/home/mmarco/stable-diffusion-krita-plugin/repositories/CodeFormer/facelib/detection/retinaface/retinaface.py", line 231, in detect_faces
keep = py_cpu_nms(bounding_boxes, nms_threshold)
File "/home/mmarco/stable-diffusion-krita-plugin/repositories/CodeFormer/facelib/detection/retinaface/retinaface_utils.py", line 41, in py_cpu_nms
keep = torchvision.ops.nms(
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/torchvision/ops/boxes.py", line 40, in nms
_assert_has_ops()
File "/home/mmarco/stable-diffusion-krita-plugin/venv/lib/python3.8/site-packages/torchvision/extension.py", line 33, in _assert_has_ops
raise RuntimeError(
RuntimeError: Couldn't load custom C++ ops. This can happen if your PyTorch and torchvision versions are incompatible, or if you had errors while compiling torchvision from source. For further information on the compatible versions, check https://github.com/pytorch/vision#installation for the compatibility matrix. Please check your PyTorch version with torch.__version__ and your torchvision version with torchvision.__version__ and verify if they are compatible, and if not please reinstall torchvision so that it matches your PyTorch install.
Total progress: 20it [00:16, 13.72it/s]
To Reproduce
Steps to reproduce the behavior:
Select the "Restore faces" checkbox
Click on 'Apply txt2img'
See error
Expected behavior
An image would be created
Desktop (please complete the following information):
OS: Linux
Additional context
Add any other context about the problem here.
Describe the bug I get the following error on the command line if I try to use the "restore faces" option.
To Reproduce Steps to reproduce the behavior:
Expected behavior An image would be created
Desktop (please complete the following information):
Additional context Add any other context about the problem here.