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This commit is contained in:
harisreedhar 2024-11-13 16:07:14 +05:30
parent 18244da99f
commit 0b6dd6c8b1
2 changed files with 40 additions and 12 deletions
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50
facefusion/face_helper.py
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@ -5,7 +5,7 @@ import cv2
import numpy
from cv2.typing import Size
from facefusion.typing import Anchors, Angle, BoundingBox, Direction, Distance, FaceDetectorModel, FaceLandmark5, FaceLandmark68, Mask, Matrix, Points, Scale, Score, Translation, VisionFrame, WarpTemplate, WarpTemplateSet
from facefusion.typing import Anchors, Angle, BoundingBox, Direction, Distance, FaceDetectorModel, FaceLandmark5, FaceLandmark68, Mask, Matrix, Points, PolygonTemplate, PolygonTemplateSet, Scale, Score, Translation, VisionFrame, WarpTemplate, WarpTemplateSet
WARP_TEMPLATES : WarpTemplateSet =\
{
@ -66,6 +66,28 @@ WARP_TEMPLATES : WarpTemplateSet =\
[ 0.72610437, 0.78023333 ]
])
}
POLYGON_TEMPLATES : PolygonTemplateSet =\
{
'square': numpy.array(
[
[ 0, 0 ],
[ 1, 0 ],
[ 1, 1 ],
[ 0, 1 ]
]),
'triangle_orthogonal': numpy.array(
[
[ 0, 0 ],
[ 1, 0 ],
[ 0, 1 ]
]),
'triangle_skew': numpy.array(
[
[ 0, 0 ],
[ 1, 0 ],
[ 1, 1 ]
])
}
def estimate_matrix_by_face_landmark_5(face_landmark_5 : FaceLandmark5, warp_template : WarpTemplate, crop_size : Size) -> Matrix:
@ -74,6 +96,12 @@ def estimate_matrix_by_face_landmark_5(face_landmark_5 : FaceLandmark5, warp_tem
return affine_matrix
def estimate_matrix_by_points(source_points : Points, polygon_template : PolygonTemplate, crop_size : Size) -> Matrix:
target_points = POLYGON_TEMPLATES.get(polygon_template) * crop_size
affine_matrix = cv2.getAffineTransform(source_points, target_points.astype(numpy.float32))
return affine_matrix
def warp_face_by_face_landmark_5(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmark5, warp_template : WarpTemplate, crop_size : Size) -> Tuple[VisionFrame, Matrix]:
affine_matrix = estimate_matrix_by_face_landmark_5(face_landmark_5, warp_template, crop_size)
crop_vision_frame = cv2.warpAffine(temp_vision_frame, affine_matrix, crop_size, borderMode = cv2.BORDER_REPLICATE, flags = cv2.INTER_AREA)
@ -82,7 +110,7 @@ def warp_face_by_face_landmark_5(temp_vision_frame : VisionFrame, face_landmark_
def warp_face_for_deepfacelive(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmark5, crop_size : Size, coverage : float, x_shift : float, y_shift : float) -> Tuple[VisionFrame, Matrix]:
affine_matrix = estimate_matrix_by_face_landmark_5(face_landmark_5, 'deep_face_live', (1, 1))
square_points = numpy.array([ (0, 0), (1, 0), (1, 1), (0, 1) ]).astype(numpy.float32)
square_points = POLYGON_TEMPLATES.get('square').astype(numpy.float32)
square_points = transform_points(square_points, cv2.invertAffineTransform(affine_matrix))
center_point = square_points.mean(axis = 0)
center_point += x_shift * numpy.subtract(square_points[1], square_points[0])
@ -91,22 +119,14 @@ def warp_face_for_deepfacelive(temp_vision_frame : VisionFrame, face_landmark_5
top_bottom_direction = calc_points_direction(square_points[0], square_points[2]) * scale
bottom_top_direction = calc_points_direction(square_points[3], square_points[1]) * scale
source_points = numpy.array([ center_point - top_bottom_direction, center_point + bottom_top_direction, center_point + top_bottom_direction ]).astype(numpy.float32)
target_points = numpy.array([ (0, 0), (1, 0), (1, 1) ]).astype(numpy.float32) * crop_size[0]
affine_matrix = cv2.getAffineTransform(source_points, target_points)
affine_matrix = estimate_matrix_by_points(source_points, 'triangle_skew', crop_size)
crop_vision_frame = cv2.warpAffine(temp_vision_frame, affine_matrix, crop_size, flags = cv2.INTER_CUBIC)
return crop_vision_frame, affine_matrix
def calc_points_direction(start_point : Points, end_point : Points) -> Direction:
direction = end_point - start_point
direction /= numpy.linalg.norm(direction)
return direction
def warp_face_by_bounding_box(temp_vision_frame : VisionFrame, bounding_box : BoundingBox, crop_size : Size) -> Tuple[VisionFrame, Matrix]:
source_points = numpy.array([ [ bounding_box[0], bounding_box[1] ], [bounding_box[2], bounding_box[1] ], [ bounding_box[0], bounding_box[3] ] ]).astype(numpy.float32)
target_points = numpy.array([ [ 0, 0 ], [ crop_size[0], 0 ], [ 0, crop_size[1] ] ]).astype(numpy.float32)
affine_matrix = cv2.getAffineTransform(source_points, target_points)
affine_matrix = estimate_matrix_by_points(source_points, 'triangle_orthogonal', crop_size)
if bounding_box[2] - bounding_box[0] > crop_size[0] or bounding_box[3] - bounding_box[1] > crop_size[1]:
interpolation_method = cv2.INTER_AREA
else:
@ -133,6 +153,12 @@ def paste_back(temp_vision_frame : VisionFrame, crop_vision_frame : VisionFrame,
return paste_vision_frame
def calc_points_direction(start_point : Points, end_point : Points) -> Direction:
direction = end_point - start_point
direction /= numpy.linalg.norm(direction)
return direction
@lru_cache(maxsize = None)
def create_static_anchors(feature_stride : int, anchor_total : int, stride_height : int, stride_width : int) -> Anchors:
y, x = numpy.mgrid[:stride_height, :stride_width][::-1]

2
facefusion/typing.py
View File

@ -88,6 +88,8 @@ Content = Dict[str, Any]
WarpTemplate = Literal['arcface_112_v1', 'arcface_112_v2', 'arcface_128_v2', 'ffhq_512', 'mtcnn_512', 'styleganex_384', 'deep_face_live']
WarpTemplateSet = Dict[WarpTemplate, NDArray[Any]]
PolygonTemplate = Literal['square', 'triangle_orthogonal', 'triangle_skew']
PolygonTemplateSet = Dict[PolygonTemplate, NDArray[Any]]
ProcessMode = Literal['output', 'preview', 'stream']
ErrorCode = Literal[0, 1, 2, 3, 4]