mirror of
https://github.com/deepfakes/faceswap
synced 2025-06-07 10:43:27 -04:00
Add mask dilation/erosion option for training
This commit is contained in:
torzdf
parent
2b08b8d2a6
commit
4502824481
6 changed files with 156 additions and 78 deletions
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@ -88,8 +88,8 @@ class DetectedFace():
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landmarks_xy: np.ndarray | None = None,
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mask: dict[str, "Mask"] | None = None,
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filename: str | None = None) -> None:
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logger.trace("Initializing %s: (image: %s, left: %s, width: %s, top: %s, " # type: ignore
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"height: %s, landmarks_xy: %s, mask: %s, filename: %s)",
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logger.trace("Initializing %s: (image: %s, left: %s, " # type:ignore[attr-defined]
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"width: %s, top: %s, height: %s, landmarks_xy: %s, mask: %s, filename: %s)",
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self.__class__.__name__,
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image.shape if image is not None and image.any() else image, left, width, top,
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height, landmarks_xy, mask, filename)
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@ -105,7 +105,7 @@ class DetectedFace():
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self._training_masks: tuple[bytes, tuple[int, int, int]] | None = None
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self._aligned: AlignedFace | None = None
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logger.trace("Initialized %s", self.__class__.__name__) # type: ignore
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logger.trace("Initialized %s", self.__class__.__name__) # type:ignore[attr-defined]
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@property
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def aligned(self) -> AlignedFace:
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@ -167,7 +167,7 @@ class DetectedFace():
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The centering to store the mask at. One of `"legacy"`, `"face"`, `"head"`.
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Default: `"face"`
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"""
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logger.trace("name: '%s', mask shape: %s, affine_matrix: %s, " # type: ignore
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logger.trace("name: '%s', mask shape: %s, affine_matrix: %s, " # type:ignore[attr-defined]
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"interpolator: %s, storage_size: %s, storage_centering: %s)", name,
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mask.shape, affine_matrix, interpolator, storage_size, storage_centering)
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fsmask = Mask(storage_size=storage_size, storage_centering=storage_centering)
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@ -183,7 +183,7 @@ class DetectedFace():
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landmarks: :class:`numpy.ndarray`
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The 68 point face landmarks to add for the face
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"""
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logger.trace("landmarks shape: '%s'", landmarks.shape) # type: ignore
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logger.trace("landmarks shape: '%s'", landmarks.shape) # type:ignore[attr-defined]
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self._landmarks_xy = landmarks
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def add_identity(self, name: str, embedding: np.ndarray, ) -> None:
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@ -197,7 +197,7 @@ class DetectedFace():
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embedding: numpy.ndarray
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The identity embedding
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"""
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logger.trace("name: '%s', embedding shape: %s", # type: ignore
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logger.trace("name: '%s', embedding shape: %s", # type:ignore[attr-defined]
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name, embedding.shape)
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assert name == "vggface2"
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assert embedding.shape[0] == 512
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@ -210,7 +210,7 @@ class DetectedFace():
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def get_landmark_mask(self,
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area: T.Literal["eye", "face", "mouth"],
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blur_kernel: int,
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dilation: int) -> np.ndarray:
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dilation: float) -> np.ndarray:
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""" Add a :class:`LandmarksMask` to this detected face
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Landmark based masks are generated from face Aligned Face landmark points. An aligned
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@ -224,8 +224,8 @@ class DetectedFace():
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specific areas
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blur_kernel: int
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The size of the kernel for blurring the mask edges
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dilation: int
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The amount of dilation to apply to the mask. `0` for none. Default: `0`
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dilation: float
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The amount of dilation to apply to the mask. as a percentage of the mask size
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Returns
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-------
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@ -233,7 +233,7 @@ class DetectedFace():
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The generated landmarks mask for the selected area
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"""
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# TODO Face mask generation from landmarks
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logger.trace("area: %s, dilation: %s", area, dilation) # type: ignore
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logger.trace("area: %s, dilation: %s", area, dilation) # type:ignore[attr-defined]
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areas = {"mouth": [slice(48, 60)], "eye": [slice(36, 42), slice(42, 48)]}
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points = [self.aligned.landmarks[zone]
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for zone in areas[area]]
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@ -307,7 +307,7 @@ class DetectedFace():
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for name, mask in self.mask.items()},
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identity={k: v.tolist() for k, v in self._identity.items()},
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thumb=self.thumbnail)
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logger.trace("Returning: %s", alignment) # type: ignore
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logger.trace("Returning: %s", alignment) # type:ignore[attr-defined]
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return alignment
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def from_alignment(self, alignment: AlignmentFileDict,
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@ -332,8 +332,8 @@ class DetectedFace():
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Default: ``False``
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"""
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logger.trace("Creating from alignment: (alignment: %s, has_image: %s)", # type: ignore
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alignment, bool(image is not None))
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logger.trace("Creating from alignment: (alignment: %s," # type:ignore[attr-defined]
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" has_image: %s)", alignment, bool(image is not None))
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self.left = alignment["x"]
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self.width = alignment["w"]
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self.top = alignment["y"]
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@ -358,9 +358,9 @@ class DetectedFace():
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self.mask[name].from_dict(mask_dict)
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if image is not None and image.any():
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self._image_to_face(image)
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logger.trace("Created from alignment: (left: %s, width: %s, top: %s, " # type: ignore
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"height: %s, landmarks: %s, mask: %s)", self.left, self.width, self.top,
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self.height, self.landmarks_xy, self.mask)
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logger.trace("Created from alignment: (left: %s, width: %s, " # type:ignore[attr-defined]
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"top: %s, height: %s, landmarks: %s, mask: %s)",
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self.left, self.width, self.top, self.height, self.landmarks_xy, self.mask)
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def to_png_meta(self) -> PNGHeaderAlignmentsDict:
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""" Return the detected face formatted for insertion into a png itxt header.
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@ -403,14 +403,14 @@ class DetectedFace():
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for key, val in alignment.get("identity", {}).items():
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assert key in ["vggface2"]
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self._identity[T.cast(T.Literal["vggface2"], key)] = np.array(val, dtype="float32")
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logger.trace("Created from png exif header: (left: %s, width: %s, top: %s " # type: ignore
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" height: %s, landmarks: %s, mask: %s, identity: %s)", self.left, self.width,
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self.top, self.height, self.landmarks_xy, self.mask,
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logger.trace("Created from png exif header: (left: %s, " # type:ignore[attr-defined]
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"width: %s, top: %s height: %s, landmarks: %s, mask: %s, identity: %s)",
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self.left, self.width, self.top, self.height, self.landmarks_xy, self.mask,
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{k: v.shape for k, v in self._identity.items()})
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def _image_to_face(self, image: np.ndarray) -> None:
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""" set self.image to be the cropped face from detected bounding box """
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logger.trace("Cropping face from image") # type: ignore
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logger.trace("Cropping face from image") # type:ignore[attr-defined]
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self.image = image[self.top: self.bottom,
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self.left: self.right]
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@ -467,10 +467,11 @@ class DetectedFace():
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"""
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if self._aligned and not force:
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# Don't reload an already aligned face
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logger.trace("Skipping alignment calculation for already aligned face") # type: ignore
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logger.trace("Skipping alignment calculation for already " # type:ignore[attr-defined]
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"aligned face")
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else:
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logger.trace("Loading aligned face: (size: %s, dtype: %s)", # type: ignore
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size, dtype)
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logger.trace("Loading aligned face: (size: %s, " # type:ignore[attr-defined]
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"dtype: %s)", size, dtype)
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self._aligned = AlignedFace(self.landmarks_xy,
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image=image,
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centering=centering,
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@ -507,7 +508,8 @@ class Mask():
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def __init__(self,
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storage_size: int = 128,
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storage_centering: CenteringType = "face") -> None:
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logger.trace("Initializing: %s (storage_size: %s, storage_centering: %s)", # type: ignore
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logger.trace("Initializing: %s (storage_size: %s, " # type:ignore[attr-defined]
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"storage_centering: %s)",
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self.__class__.__name__, storage_size, storage_centering)
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self.stored_size = storage_size
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self.stored_centering = storage_centering
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@ -520,19 +522,21 @@ class Mask():
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self._blur_passes: int = 0
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self._blur_kernel: float | int = 0
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self._threshold = 0.0
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self._dilation: tuple[T.Literal["erode", "dilate"], np.ndarray | None] = ("erode", None)
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self._sub_crop_size = 0
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self._sub_crop_slices: dict[T.Literal["in", "out"], list[slice]] = {}
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self.set_blur_and_threshold()
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logger.trace("Initialized: %s", self.__class__.__name__) # type: ignore
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logger.trace("Initialized: %s", self.__class__.__name__) # type:ignore[attr-defined]
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@property
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def mask(self) -> np.ndarray:
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""" :class:`numpy.ndarray`: The mask at the size of :attr:`stored_size` with any requested
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blurring, threshold amount and centering applied."""
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mask = self.stored_mask
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if self._threshold != 0.0 or self._blur_kernel != 0:
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if self._dilation[-1] is not None or self._threshold != 0.0 or self._blur_kernel != 0:
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mask = mask.copy()
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self._dilate_mask(mask)
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if self._threshold != 0.0:
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mask[mask < self._threshold] = 0.0
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mask[mask > 255.0 - self._threshold] = 255.0
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@ -546,7 +550,7 @@ class Mask():
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slice_in, slice_out = self._sub_crop_slices["in"], self._sub_crop_slices["out"]
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out[slice_out[0], slice_out[1], :] = mask[slice_in[0], slice_in[1], :]
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mask = out
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logger.trace("mask shape: %s", mask.shape) # type: ignore
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logger.trace("mask shape: %s", mask.shape) # type:ignore[attr-defined]
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return mask
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@property
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@ -556,7 +560,7 @@ class Mask():
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assert self._mask is not None
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dims = (self.stored_size, self.stored_size, 1)
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mask = np.frombuffer(decompress(self._mask), dtype="uint8").reshape(dims)
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logger.trace("stored mask shape: %s", mask.shape) # type: ignore
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logger.trace("stored mask shape: %s", mask.shape) # type:ignore[attr-defined]
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return mask
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@property
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@ -567,9 +571,9 @@ class Mask():
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[0, self.stored_size - 1],
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[self.stored_size - 1, self.stored_size - 1],
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[self.stored_size - 1, 0]], np.int32).reshape((-1, 1, 2))
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matrix = cv2.invertAffineTransform(self._affine_matrix)
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matrix = cv2.invertAffineTransform(self.affine_matrix)
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roi = cv2.transform(points, matrix).reshape((4, 2))
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logger.trace("Returning: %s", roi) # type: ignore
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logger.trace("Returning: %s", roi) # type:ignore[attr-defined]
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return roi
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@property
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@ -584,6 +588,22 @@ class Mask():
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assert self._interpolator is not None
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return self._interpolator
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def _dilate_mask(self, mask: np.ndarray) -> None:
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""" Erode/Dilate the mask. The action is performed in-place on the given mask.
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No action is performed if a dilation amount has not been set
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Parameters
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----------
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mask: :class:`numpy.ndarray`
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The mask to be eroded/dilated
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"""
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if self._dilation[-1] is None:
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return
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func = cv2.erode if self._dilation[0] == "erode" else cv2.dilate
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func(mask, self._dilation[-1], dst=mask, iterations=1)
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def get_full_frame_mask(self, width: int, height: int) -> np.ndarray:
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""" Return the stored mask in a full size frame of the given dimensions
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@ -600,13 +620,13 @@ class Mask():
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"""
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frame = np.zeros((width, height, 1), dtype="uint8")
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mask = cv2.warpAffine(self.mask,
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self._affine_matrix,
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self.affine_matrix,
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(width, height),
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frame,
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flags=cv2.WARP_INVERSE_MAP | self._interpolator,
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flags=cv2.WARP_INVERSE_MAP | self.interpolator,
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borderMode=cv2.BORDER_CONSTANT)
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logger.trace("mask shape: %s, mask dtype: %s, mask min: %s, mask max: %s", # type: ignore
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mask.shape, mask.dtype, mask.min(), mask.max())
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logger.trace("mask shape: %s, mask dtype: %s, mask min: %s, " # type:ignore[attr-defined]
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"mask max: %s", mask.shape, mask.dtype, mask.min(), mask.max())
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return mask
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def add(self, mask: np.ndarray, affine_matrix: np.ndarray, interpolator: int) -> None:
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@ -624,9 +644,9 @@ class Mask():
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interpolator, int:
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The CV2 interpolator required to transform this mask to it's original frame
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"""
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logger.trace("mask shape: %s, mask dtype: %s, mask min: %s, mask max: %s, " # type: ignore
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"affine_matrix: %s, interpolator: %s)", mask.shape, mask.dtype, mask.min(),
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affine_matrix, mask.max(), interpolator)
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logger.trace("mask shape: %s, mask dtype: %s, mask min: %s, " # type:ignore[attr-defined]
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"mask max: %s, affine_matrix: %s, interpolator: %s)",
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mask.shape, mask.dtype, mask.min(), affine_matrix, mask.max(), interpolator)
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self._affine_matrix = self._adjust_affine_matrix(mask.shape[0], affine_matrix)
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self._interpolator = interpolator
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self.replace_mask(mask)
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@ -645,6 +665,26 @@ class Mask():
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interpolation=cv2.INTER_AREA) * 255.0).astype("uint8")
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self._mask = compress(mask.tobytes())
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def set_dilation(self, amount: float) -> None:
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""" Set the internal dilation object for returned masks
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Parameters
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----------
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amount: float
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The amount of erosion/dilation to apply as a percentage of the total mask size.
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Negative values erode the mask. Positive values dilate the mask
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"""
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if amount == 0:
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self._dilation = ("erode", None)
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return
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action: T.Literal["erode", "dilate"] = "erode" if amount < 0 else "dilate"
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kernel = int(round(self.stored_size * abs(amount / 100.), 0))
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self._dilation = (action, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (kernel, kernel)))
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logger.trace("action: '%s', amount: %s, kernel: %s, ", # type:ignore[attr-defined]
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action, amount, kernel)
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def set_blur_and_threshold(self,
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blur_kernel: int = 0,
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blur_type: T.Literal["gaussian", "normalized"] | None = "gaussian",
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@ -666,8 +706,9 @@ class Mask():
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The threshold amount to minimize/maximize mask values to 0 and 100. Percentage value.
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Default: 0
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"""
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logger.trace("blur_kernel: %s, blur_type: %s, blur_passes: %s, " # type: ignore
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"threshold: %s", blur_kernel, blur_type, blur_passes, threshold)
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logger.trace("blur_kernel: %s, blur_type: %s, " # type:ignore[attr-defined]
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"blur_passes: %s, threshold: %s",
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blur_kernel, blur_type, blur_passes, threshold)
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if blur_type is not None:
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blur_kernel += 0 if blur_kernel == 0 or blur_kernel % 2 == 1 else 1
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self._blur_kernel = blur_kernel
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@ -719,9 +760,9 @@ class Mask():
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slice(max(roi[0] * -1, 0),
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crop_size - min(crop_size, max(0, roi[2] - self.stored_size)))]
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logger.trace("src_size: %s, coverage_ratio: %s, sub_crop_size: %s, " # type: ignore
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"sub_crop_slices: %s", roi, coverage_ratio, self._sub_crop_size,
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self._sub_crop_slices)
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logger.trace("src_size: %s, coverage_ratio: %s, " # type:ignore[attr-defined]
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"sub_crop_size: %s, sub_crop_slices: %s",
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roi, coverage_ratio, self._sub_crop_size, self._sub_crop_slices)
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def _adjust_affine_matrix(self, mask_size: int, affine_matrix: np.ndarray) -> np.ndarray:
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""" Adjust the affine matrix for the mask's storage size
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@ -741,7 +782,7 @@ class Mask():
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zoom = self.stored_size / mask_size
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zoom_mat = np.array([[zoom, 0, 0.], [0, zoom, 0.]])
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adjust_mat = np.dot(zoom_mat, np.concatenate((affine_matrix, np.array([[0., 0., 1.]]))))
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logger.trace("storage_size: %s, mask_size: %s, zoom: %s, " # type: ignore
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logger.trace("storage_size: %s, mask_size: %s, zoom: %s, " # type:ignore[attr-defined]
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"original matrix: %s, adjusted_matrix: %s", self.stored_size, mask_size, zoom,
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affine_matrix.shape, adjust_mat.shape)
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return adjust_mat
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@ -768,7 +809,8 @@ class Mask():
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interpolator=self.interpolator,
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stored_size=self.stored_size,
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stored_centering=self.stored_centering)
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logger.trace({k: v if k != "mask" else type(v) for k, v in retval.items()}) # type: ignore
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logger.trace({k: v if k != "mask" else type(v) # type:ignore[attr-defined]
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for k, v in retval.items()})
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return retval
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def to_png_meta(self) -> MaskAlignmentsFileDict:
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@ -799,7 +841,7 @@ class Mask():
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self.stored_size = mask_dict["stored_size"]
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centering = mask_dict.get("stored_centering")
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self.stored_centering = "face" if centering is None else centering
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logger.trace({k: v if k != "mask" else type(v) # type: ignore
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logger.trace({k: v if k != "mask" else type(v) # type:ignore[attr-defined]
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for k, v in mask_dict.items()})
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@ -826,17 +868,17 @@ class LandmarksMask(Mask):
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storage_centering, str (optional):
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The centering to store the mask at. One of `"legacy"`, `"face"`, `"head"`.
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Default: `"face"`
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dilation: int, optional
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The amount of dilation to apply to the mask. `0` for none. Default: `0`
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dilation: float, optional
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The amount of dilation to apply to the mask. as a percentage of the mask size. Default: 0.0
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"""
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def __init__(self,
|
||||
points: list[np.ndarray],
|
||||
storage_size: int = 128,
|
||||
storage_centering: CenteringType = "face",
|
||||
dilation: int = 0) -> None:
|
||||
dilation: float = 0.0) -> None:
|
||||
super().__init__(storage_size=storage_size, storage_centering=storage_centering)
|
||||
self._points = points
|
||||
self._dilation = dilation
|
||||
self.set_dilation(dilation)
|
||||
|
||||
@property
|
||||
def mask(self) -> np.ndarray:
|
||||
|
|
@ -862,17 +904,15 @@ class LandmarksMask(Mask):
|
|||
for landmarks in self._points:
|
||||
lms = np.rint(landmarks).astype("int")
|
||||
cv2.fillConvexPoly(mask, cv2.convexHull(lms), 1.0, lineType=cv2.LINE_AA)
|
||||
if self._dilation != 0:
|
||||
mask = cv2.dilate(mask,
|
||||
cv2.getStructuringElement(cv2.MORPH_ELLIPSE,
|
||||
(self._dilation, self._dilation)),
|
||||
iterations=1)
|
||||
if self._dilation[-1] is not None:
|
||||
self._dilate_mask(mask)
|
||||
if self._blur_kernel != 0 and self._blur_type is not None:
|
||||
mask = BlurMask(self._blur_type,
|
||||
mask,
|
||||
self._blur_kernel,
|
||||
passes=self._blur_passes).blurred
|
||||
logger.trace("mask: (shape: %s, dtype: %s)", mask.shape, mask.dtype) # type: ignore
|
||||
logger.trace("mask: (shape: %s, dtype: %s)", # type:ignore[attr-defined]
|
||||
mask.shape, mask.dtype)
|
||||
self.add(mask, affine_matrix, interpolator)
|
||||
|
||||
|
||||
|
|
@ -911,15 +951,16 @@ class BlurMask(): # pylint:disable=too-few-public-methods
|
|||
kernel: int | float,
|
||||
is_ratio: bool = False,
|
||||
passes: int = 1) -> None:
|
||||
logger.trace("Initializing %s: (blur_type: '%s', mask_shape: %s, " # type: ignore
|
||||
"kernel: %s, is_ratio: %s, passes: %s)", self.__class__.__name__, blur_type,
|
||||
logger.trace("Initializing %s: (blur_type: '%s', " # type:ignore[attr-defined]
|
||||
"mask_shape: %s, kernel: %s, is_ratio: %s, passes: %s)",
|
||||
self.__class__.__name__, blur_type,
|
||||
mask.shape, kernel, is_ratio, passes)
|
||||
self._blur_type = blur_type
|
||||
self._mask = mask
|
||||
self._passes = passes
|
||||
kernel_size = self._get_kernel_size(kernel, is_ratio)
|
||||
self._kernel_size = self._get_kernel_tuple(kernel_size)
|
||||
logger.trace("Initialized %s", self.__class__.__name__) # type: ignore
|
||||
logger.trace("Initialized %s", self.__class__.__name__) # type:ignore[attr-defined]
|
||||
|
||||
@property
|
||||
def blurred(self) -> np.ndarray:
|
||||
|
|
@ -930,12 +971,14 @@ class BlurMask(): # pylint:disable=too-few-public-methods
|
|||
for i in range(self._passes):
|
||||
assert isinstance(kwargs["ksize"], tuple)
|
||||
ksize = int(kwargs["ksize"][0])
|
||||
logger.trace("Pass: %s, kernel_size: %s", i + 1, (ksize, ksize)) # type: ignore
|
||||
logger.trace("Pass: %s, kernel_size: %s", # type:ignore[attr-defined]
|
||||
i + 1, (ksize, ksize))
|
||||
blurred = func(blurred, **kwargs)
|
||||
ksize = int(round(ksize * self._multipass_factor))
|
||||
kwargs["ksize"] = self._get_kernel_tuple(ksize)
|
||||
blurred = blurred[..., None]
|
||||
logger.trace("Returning blurred mask. Shape: %s", blurred.shape) # type: ignore
|
||||
logger.trace("Returning blurred mask. Shape: %s", # type:ignore[attr-defined]
|
||||
blurred.shape)
|
||||
return blurred
|
||||
|
||||
@property
|
||||
|
|
@ -991,7 +1034,7 @@ class BlurMask(): # pylint:disable=too-few-public-methods
|
|||
mask_diameter = np.sqrt(np.sum(self._mask))
|
||||
radius = round(max(1., mask_diameter * kernel / 100.))
|
||||
kernel_size = int(radius * 2 + 1)
|
||||
logger.trace("kernel_size: %s", kernel_size) # type: ignore
|
||||
logger.trace("kernel_size: %s", kernel_size) # type:ignore[attr-defined]
|
||||
return kernel_size
|
||||
|
||||
@staticmethod
|
||||
|
|
@ -1010,14 +1053,14 @@ class BlurMask(): # pylint:disable=too-few-public-methods
|
|||
"""
|
||||
kernel_size += 1 if kernel_size % 2 == 0 else 0
|
||||
retval = (kernel_size, kernel_size)
|
||||
logger.trace(retval) # type: ignore
|
||||
logger.trace(retval) # type:ignore[attr-defined]
|
||||
return retval
|
||||
|
||||
def _get_kwargs(self) -> dict[str, int | tuple[int, int]]:
|
||||
""" dict: the valid keyword arguments for the requested :attr:`_blur_type` """
|
||||
retval = {kword: self._kwarg_mapping[kword]
|
||||
for kword in self._kwarg_requirements[self._blur_type]}
|
||||
logger.trace("BlurMask kwargs: %s", retval) # type: ignore
|
||||
logger.trace("BlurMask kwargs: %s", retval) # type:ignore[attr-defined]
|
||||
return retval
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -428,8 +428,10 @@ class _Cache():
|
|||
f"The masks that exist for this face are: {list(detected_face.mask)}")
|
||||
|
||||
mask = detected_face.mask[str(self._config["mask_type"])]
|
||||
assert isinstance(self._config["mask_dilation"], float)
|
||||
assert isinstance(self._config["mask_blur_kernel"], int)
|
||||
assert isinstance(self._config["mask_threshold"], int)
|
||||
mask.set_dilation(self._config["mask_dilation"])
|
||||
mask.set_blur_and_threshold(blur_kernel=self._config["mask_blur_kernel"],
|
||||
threshold=self._config["mask_threshold"])
|
||||
|
||||
|
|
@ -467,7 +469,7 @@ class _Cache():
|
|||
assert isinstance(multiplier, int)
|
||||
if not self._config["penalized_mask_loss"] or multiplier <= 1:
|
||||
return None
|
||||
mask = detected_face.get_landmark_mask(area, self._size // 16, self._size // 32)
|
||||
mask = detected_face.get_landmark_mask(area, self._size // 16, 2.5)
|
||||
logger.trace("Caching localized '%s' mask for: %s %s", # type: ignore
|
||||
area, filename, mask.shape)
|
||||
return mask
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@ msgid ""
|
|||
msgstr ""
|
||||
"Project-Id-Version: PACKAGE VERSION\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2023-08-20 14:54+0100\n"
|
||||
"POT-Creation-Date: 2024-03-26 17:37+0000\n"
|
||||
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
|
||||
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
|
||||
"Language-Team: LANGUAGE <LL@li.org>\n"
|
||||
|
|
@ -539,8 +539,9 @@ msgid ""
|
|||
"attention on the core face area."
|
||||
msgstr ""
|
||||
|
||||
#: plugins/train/_config.py:600 plugins/train/_config.py:642
|
||||
#: plugins/train/_config.py:656 plugins/train/_config.py:665
|
||||
#: plugins/train/_config.py:600 plugins/train/_config.py:643
|
||||
#: plugins/train/_config.py:656 plugins/train/_config.py:671
|
||||
#: plugins/train/_config.py:680
|
||||
msgid "mask"
|
||||
msgstr ""
|
||||
|
||||
|
|
@ -582,7 +583,14 @@ msgid ""
|
|||
"performance."
|
||||
msgstr ""
|
||||
|
||||
#: plugins/train/_config.py:644
|
||||
#: plugins/train/_config.py:645
|
||||
msgid ""
|
||||
"Dilate or erode the mask. Negative values erode the mask (make it smaller). "
|
||||
"Positive values dilate the mask (make it larger). The value given is a "
|
||||
"percentage of the total mask size."
|
||||
msgstr ""
|
||||
|
||||
#: plugins/train/_config.py:658
|
||||
msgid ""
|
||||
"Apply gaussian blur to the mask input. This has the effect of smoothing the "
|
||||
"edges of the mask, which can help with poorly calculated masks and give less "
|
||||
|
|
@ -592,13 +600,13 @@ msgid ""
|
|||
"number."
|
||||
msgstr ""
|
||||
|
||||
#: plugins/train/_config.py:658
|
||||
#: plugins/train/_config.py:673
|
||||
msgid ""
|
||||
"Sets pixels that are near white to white and near black to black. Set to 0 "
|
||||
"for off."
|
||||
msgstr ""
|
||||
|
||||
#: plugins/train/_config.py:667
|
||||
#: plugins/train/_config.py:682
|
||||
msgid ""
|
||||
"Dedicate a portion of the model to learning how to duplicate the input mask. "
|
||||
"Increases VRAM usage in exchange for learning a quick ability to try to "
|
||||
|
|
|
|||
Binary file not shown.
|
|
@ -7,15 +7,15 @@ msgid ""
|
|||
msgstr ""
|
||||
"Project-Id-Version: \n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2023-08-20 14:54+0100\n"
|
||||
"PO-Revision-Date: 2023-08-20 14:58+0100\n"
|
||||
"POT-Creation-Date: 2024-03-26 17:37+0000\n"
|
||||
"PO-Revision-Date: 2024-03-26 17:40+0000\n"
|
||||
"Last-Translator: \n"
|
||||
"Language-Team: \n"
|
||||
"Language: ru_RU\n"
|
||||
"MIME-Version: 1.0\n"
|
||||
"Content-Type: text/plain; charset=UTF-8\n"
|
||||
"Content-Transfer-Encoding: 8bit\n"
|
||||
"X-Generator: Poedit 3.3.2\n"
|
||||
"X-Generator: Poedit 3.4.2\n"
|
||||
|
||||
#: plugins/train/_config.py:17
|
||||
msgid ""
|
||||
|
|
@ -851,8 +851,9 @@ msgstr ""
|
|||
"время как область лица с маской является приоритетной. Может повысить общее "
|
||||
"качество за счет концентрации внимания на основной области лица."
|
||||
|
||||
#: plugins/train/_config.py:600 plugins/train/_config.py:642
|
||||
#: plugins/train/_config.py:656 plugins/train/_config.py:665
|
||||
#: plugins/train/_config.py:600 plugins/train/_config.py:643
|
||||
#: plugins/train/_config.py:656 plugins/train/_config.py:671
|
||||
#: plugins/train/_config.py:680
|
||||
msgid "mask"
|
||||
msgstr "маска"
|
||||
|
||||
|
|
@ -928,7 +929,16 @@ msgstr ""
|
|||
"сообщества и для дальнейшего описания нуждается в тестировании. Профильные "
|
||||
"лица могут иметь низкую производительность."
|
||||
|
||||
#: plugins/train/_config.py:644
|
||||
#: plugins/train/_config.py:645
|
||||
msgid ""
|
||||
"Dilate or erode the mask. Negative values erode the mask (make it smaller). "
|
||||
"Positive values dilate the mask (make it larger). The value given is a "
|
||||
"percentage of the total mask size."
|
||||
msgstr ""
|
||||
"Расширяет или сужает маску. Отрицательные значения сужают маску (делают её "
|
||||
"меньше). Положительные значения расширяют маску (делают её больше). "
|
||||
|
||||
#: plugins/train/_config.py:658
|
||||
msgid ""
|
||||
"Apply gaussian blur to the mask input. This has the effect of smoothing the "
|
||||
"edges of the mask, which can help with poorly calculated masks and give less "
|
||||
|
|
@ -944,7 +954,7 @@ msgstr ""
|
|||
"должно быть нечетным, если передано четное число, то оно будет округлено до "
|
||||
"следующего нечетного числа."
|
||||
|
||||
#: plugins/train/_config.py:658
|
||||
#: plugins/train/_config.py:673
|
||||
msgid ""
|
||||
"Sets pixels that are near white to white and near black to black. Set to 0 "
|
||||
"for off."
|
||||
|
|
@ -952,7 +962,7 @@ msgstr ""
|
|||
"Устанавливает пиксели, которые почти белые - в белые и которые почти черные "
|
||||
"- в черные. Установите 0, чтобы выключить."
|
||||
|
||||
#: plugins/train/_config.py:667
|
||||
#: plugins/train/_config.py:682
|
||||
msgid ""
|
||||
"Dedicate a portion of the model to learning how to duplicate the input mask. "
|
||||
"Increases VRAM usage in exchange for learning a quick ability to try to "
|
||||
|
|
|
|||
|
|
@ -632,6 +632,19 @@ class Config(FaceswapConfig):
|
|||
"faces. The mask model has been trained by community members and will need "
|
||||
"testing for further description. Profile faces may result in sub-par "
|
||||
"performance."))
|
||||
self.add_item(
|
||||
section=section,
|
||||
title="mask_dilation",
|
||||
datatype=float,
|
||||
min_max=(-5.0, 5.0),
|
||||
rounding=1,
|
||||
default=0,
|
||||
fixed=False,
|
||||
group=_("mask"),
|
||||
info=_(
|
||||
"Dilate or erode the mask. Negative values erode the mask (make it smaller). "
|
||||
"Positive values dilate the mask (make it larger). The value given is a "
|
||||
"percentage of the total mask size."))
|
||||
self.add_item(
|
||||
section=section,
|
||||
title="mask_blur_kernel",
|
||||
|
|
@ -639,6 +652,7 @@ class Config(FaceswapConfig):
|
|||
min_max=(0, 9),
|
||||
rounding=1,
|
||||
default=3,
|
||||
fixed=False,
|
||||
group=_("mask"),
|
||||
info=_(
|
||||
"Apply gaussian blur to the mask input. This has the effect of smoothing the "
|
||||
|
|
@ -653,6 +667,7 @@ class Config(FaceswapConfig):
|
|||
default=4,
|
||||
min_max=(0, 50),
|
||||
rounding=1,
|
||||
fixed=False,
|
||||
group=_("mask"),
|
||||
info=_(
|
||||
"Sets pixels that are near white to white and near black to black. Set to 0 for "
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue