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refactoring

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This commit is contained in:
iperov 2021-11-07 10:03:15 +04:00
commit 30ba51edf7
24 changed files with 663 additions and 459 deletions
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27
xlib/face/FaceWarper.py
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@ -52,9 +52,25 @@ class FaceWarper:
self._rw_grid_tx = rnd_state.uniform(*rw_grid_tx) if isinstance(rw_grid_tx, Iterable) else rw_grid_tx
self._rw_grid_ty = rnd_state.uniform(*rw_grid_ty) if isinstance(rw_grid_ty, Iterable) else rw_grid_ty
self._warp_rnd_mat = Affine2DUniMat.from_transformation(0.5, 0.5, self._rw_grid_rot_deg, 1.0+self._rw_grid_scale, self._rw_grid_tx, self._rw_grid_ty)
self._align_rnd_mat = Affine2DUniMat.from_transformation(0.5, 0.5, self._align_rot_deg, 1.0+self._align_scale, self._align_tx, self._align_ty)
self._rnd_state_state = rnd_state.get_state()
self._cached = {}
def get_aligned_random_transform_mat(self) -> Affine2DUniMat:
"""
returns Affine2DUniMat that represents transformation from aligned face to randomly transformed aligned face
"""
mat1 = self._img_to_face_uni_mat
mat2 = (self._face_to_img_uni_mat * self._align_rnd_mat).invert()
pts = [ [0,0], [1,0], [1,1]]
src_pts = mat1.transform_points(pts)
dst_pts = mat2.transform_points(pts)
return Affine2DUniMat.from_3_pairs(src_pts, dst_pts)
def transform(self, img : np.ndarray, out_res : int, random_warp : bool = True) -> np.ndarray:
"""
transform an image.
@ -91,9 +107,7 @@ class FaceWarper:
face_warp_grid = FaceWarper._gen_random_warp_uni_grid_diff(out_res, self._rw_grid_cell_count, 0.12, rnd_state)
# make a randomly transformable mat to transform face_warp_grid from face to image
face_warp_grid_mat = (self._face_to_img_uni_mat *
Affine2DUniMat.from_transformation(0.5, 0.5, self._rw_grid_rot_deg, 1.0+self._rw_grid_scale, self._rw_grid_tx, self._rw_grid_ty)
)
face_warp_grid_mat = self._face_to_img_uni_mat * self._warp_rnd_mat
# warp face_warp_grid to the space of image and merge with image_grid
image_grid += cv2.warpAffine(face_warp_grid, face_warp_grid_mat.to_exact_mat(out_res,out_res, W, H), (W,H), flags=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
@ -101,9 +115,10 @@ class FaceWarper:
# scale uniform grid from to image size
image_grid *= (H-1, W-1)
# apply random transormations for align mat
img_to_face_rnd_mat = (self._face_to_img_uni_mat * Affine2DMat.from_transformation(0.5, 0.5, self._align_rot_deg, 1.0+self._align_scale, self._align_tx, self._align_ty)
).invert().to_exact_mat(W,H,out_res,out_res)
# apply random transformations for align mat
#img_to_face_rnd_uni_mat = (self._face_to_img_uni_mat * self._align_rnd_mat).invert()
img_to_face_rnd_mat = (self._face_to_img_uni_mat * self._align_rnd_mat).invert().to_exact_mat(W,H,out_res,out_res)
# warp image_grid to face space
image_grid = cv2.warpAffine(image_grid, img_to_face_rnd_mat, (out_res,out_res), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE )