mirror of
https://github.com/deepfakes/faceswap
synced 2025-06-08 03:26:47 -04:00
2783c27e00
* Add dimensions to alignments + refactor * Add frame_dims + funcs to DetectFaces. Add alignments lib * Convert Adjust working * Refactor and tidy up
112 lines
4.2 KiB
Python
112 lines
4.2 KiB
Python
#!/usr/bin python3
|
|
""" Face and landmarks detection for faceswap.py """
|
|
|
|
from dlib import rectangle as d_rectangle # pylint: disable=no-name-in-module
|
|
from lib.aligner import Extract as AlignerExtract, get_align_mat
|
|
|
|
|
|
class DetectedFace():
|
|
""" Detected face and landmark information """
|
|
def __init__(self, image=None, x=None, w=None, y=None, h=None,
|
|
frame_dims=None, landmarksXY=None):
|
|
self.image = image
|
|
self.x = x
|
|
self.w = w
|
|
self.y = y
|
|
self.h = h
|
|
self.frame_dims = frame_dims
|
|
self.landmarksXY = landmarksXY
|
|
|
|
self.aligned = dict()
|
|
|
|
def landmarks_as_xy(self):
|
|
""" Landmarks as XY """
|
|
return self.landmarksXY
|
|
|
|
def to_dlib_rect(self):
|
|
""" Return Bounding Box as Dlib Rectangle """
|
|
left = self.x
|
|
top = self.y
|
|
right = self.x + self.w
|
|
bottom = self.y + self.h
|
|
return d_rectangle(left, top, right, bottom)
|
|
|
|
def from_dlib_rect(self, d_rect):
|
|
""" Set Bounding Box from a Dlib Rectangle """
|
|
if not isinstance(d_rect, d_rectangle):
|
|
raise ValueError("Supplied Bounding Box is not a dlib.rectangle.")
|
|
self.x = d_rect.left()
|
|
self.w = d_rect.right() - d_rect.left()
|
|
self.y = d_rect.top()
|
|
self.h = d_rect.bottom() - d_rect.top()
|
|
|
|
def image_to_face(self, image):
|
|
""" Crop an image around bounding box to the face
|
|
and capture it's dimensions """
|
|
self.image = image[self.y: self.y + self.h,
|
|
self.x: self.x + self.w]
|
|
|
|
def to_alignment(self):
|
|
""" Convert a detected face to alignment dict """
|
|
alignment = dict()
|
|
alignment["x"] = self.x
|
|
alignment["w"] = self.w
|
|
alignment["y"] = self.y
|
|
alignment["h"] = self.h
|
|
alignment["frame_dims"] = self.frame_dims
|
|
alignment["landmarksXY"] = self.landmarksXY
|
|
return alignment
|
|
|
|
def from_alignment(self, alignment, image=None):
|
|
""" Convert a face alignment to detected face object """
|
|
self.x = alignment["x"]
|
|
self.w = alignment["w"]
|
|
self.y = alignment["y"]
|
|
self.h = alignment["h"]
|
|
self.frame_dims = alignment["frame_dims"]
|
|
self.landmarksXY = alignment["landmarksXY"]
|
|
if image.any():
|
|
self.image_to_face(image)
|
|
|
|
# <<< Aligned Face methods and properties >>> #
|
|
def load_aligned(self, image, size=256, padding=48, align_eyes=False):
|
|
""" No need to load aligned information for all uses of this
|
|
class, so only call this to load the information for easy
|
|
reference to aligned properties for this face """
|
|
self.aligned["size"] = size
|
|
self.aligned["padding"] = padding
|
|
self.aligned["align_eyes"] = align_eyes
|
|
self.aligned["matrix"] = get_align_mat(self, size, align_eyes)
|
|
self.aligned["face"] = AlignerExtract().transform(
|
|
image,
|
|
self.aligned["matrix"],
|
|
size,
|
|
padding)
|
|
|
|
@property
|
|
def original_roi(self):
|
|
""" Return the square aligned box location on the original
|
|
image """
|
|
return AlignerExtract().get_original_roi(self.aligned["matrix"],
|
|
self.aligned["size"],
|
|
self.aligned["padding"])
|
|
|
|
@property
|
|
def aligned_landmarks(self):
|
|
""" Return the landmarks location transposed to extracted face """
|
|
return AlignerExtract().transform_points(self.landmarksXY,
|
|
self.aligned["matrix"],
|
|
self.aligned["size"],
|
|
self.aligned["padding"])
|
|
|
|
@property
|
|
def aligned_face(self):
|
|
""" Return aligned detected face """
|
|
return self.aligned["face"]
|
|
|
|
@property
|
|
def adjusted_matrix(self):
|
|
""" Return adjusted matrix for size/padding combination """
|
|
return AlignerExtract().transform_matrix(self.aligned["matrix"],
|
|
self.aligned["size"],
|
|
self.aligned["padding"])
|