def _warp_template(self, template, group, reference_shape, scale_index,
prefix, verbose):
reference_frame = build_patch_reference_frame(
reference_shape, patch_shape=self.patch_shape[scale_index])
shape = template.landmarks[group].lms
return warp_images([template], [shape], reference_frame, self.transform,
prefix=prefix, verbose=verbose)
def _warp_template(self, template, group, reference_shape, scale_index,
prefix, verbose):
reference_frame = build_patch_reference_frame(
reference_shape, patch_shape=self.patch_shape[scale_index])
shape = template.landmarks[group]
return warp_images([template], [shape], reference_frame, self.transform,
prefix=prefix, verbose=verbose)
def _instance(self, shape_instance, template):
landmarks = template.landmarks["source"].lms
reference_frame = build_patch_reference_frame(shape_instance, patch_shape=self.patch_shape)
transform = self.transform(reference_frame.landmarks["source"].lms, landmarks)
return template.as_unmasked().warp_to_mask(reference_frame.mask, transform, warp_landmarks=True)
def _build_shape_model(self, shapes, scale_index):
mean_aligned_shape = mean_pointcloud(align_shapes(shapes))
self.n_landmarks = mean_aligned_shape.n_points
self.reference_frame = build_patch_reference_frame(
mean_aligned_shape, patch_shape=self.patch_shape[scale_index])
dense_shapes = densify_shapes(shapes, self.reference_frame,
self.transform)
# build dense shape model
shape_model = build_shape_model(dense_shapes)
return shape_model
def _build_shape_model(self, shapes, scale_index):
mean_aligned_shape = mean_pointcloud(align_shapes(shapes))
self.n_landmarks = mean_aligned_shape.n_points
self.reference_frame = build_patch_reference_frame(
mean_aligned_shape, patch_shape=self.patch_shape[scale_index]
)
dense_shapes = densify_shapes(shapes, self.reference_frame, self.transform)
# Build dense shape model
max_sc = self.max_shape_components[scale_index]
return self._shape_model_cls[scale_index](dense_shapes, max_n_components=max_sc)
def _build_shape_model(self, shapes, scale_index):
mean_aligned_shape = mean_pointcloud(align_shapes(shapes))
self.n_landmarks = mean_aligned_shape.n_points
self.reference_frame = build_patch_reference_frame(
mean_aligned_shape, patch_shape=self.patch_shape[scale_index])
dense_shapes = densify_shapes(shapes, self.reference_frame,
self.transform)
# Build dense shape model
max_sc = self.max_shape_components[scale_index]
return self._shape_model_cls[scale_index](dense_shapes,
max_n_components=max_sc)
def _instance(self, shape_instance, template):
landmarks = template.landmarks['source']
reference_frame = build_patch_reference_frame(
shape_instance, patch_shape=self.patch_shape)
transform = self.transform(
reference_frame.landmarks['source'], landmarks)
return template.as_unmasked().warp_to_mask(
reference_frame.mask, transform, warp_landmarks=True)
def _instance(self, scale_index, shape_instance, appearance_instance):
template = self.appearance_models[scale_index].mean()
landmarks = template.landmarks['source'].lms
reference_frame = build_patch_reference_frame(
shape_instance, patch_shape=self.patch_shape[scale_index])
transform = self.transform(
reference_frame.landmarks['source'].lms, landmarks)
return appearance_instance.as_unmasked().warp_to_mask(
reference_frame.mask, transform, warp_landmarks=True)
def _instance(self, scale_index, shape_instance, appearance_instance):
template = self.appearance_models[scale_index].mean()
landmarks = template.landmarks['source'].lms
reference_frame = build_patch_reference_frame(
shape_instance, patch_shape=self.patch_shape[scale_index])
transform = self.transform(
reference_frame.landmarks['source'].lms, landmarks)
return appearance_instance.as_unmasked(copy=False).warp_to_mask(
reference_frame.mask, transform, warp_landmarks=True)
def _warp_images(self, images, shapes, reference_shape, scale_index,
prefix, verbose):
reference_frame = build_patch_reference_frame(
reference_shape, patch_shape=self.patch_shape[scale_index])
return warp_images(images, shapes, reference_frame, self.transform,
prefix=prefix, verbose=verbose)
def _warp_images(self, images, shapes, reference_shape, scale_index,
prefix, verbose):
reference_frame = build_patch_reference_frame(
reference_shape, patch_shape=self.patch_shape[scale_index])
return warp_images(images, shapes, reference_frame, self.transform,
prefix=prefix, verbose=verbose)
