| from typing import List | |
| import numpy | |
| from facefusion import state_manager | |
| from facefusion.types import Face, FaceSelectorOrder, FaceSet, Gender, Race | |
| def find_similar_faces(faces : List[Face], reference_faces : FaceSet, face_distance : float) -> List[Face]: | |
| similar_faces : List[Face] = [] | |
| if faces and reference_faces: | |
| for reference_set in reference_faces: | |
| if not similar_faces: | |
| for reference_face in reference_faces[reference_set]: | |
| for face in faces: | |
| if compare_faces(face, reference_face, face_distance): | |
| similar_faces.append(face) | |
| return similar_faces | |
| def compare_faces(face : Face, reference_face : Face, face_distance : float) -> bool: | |
| current_face_distance = calc_face_distance(face, reference_face) | |
| current_face_distance = float(numpy.interp(current_face_distance, [ 0, 2 ], [ 0, 1 ])) | |
| return current_face_distance < face_distance | |
| def calc_face_distance(face : Face, reference_face : Face) -> float: | |
| if hasattr(face, 'normed_embedding') and hasattr(reference_face, 'normed_embedding'): | |
| return 1 - numpy.dot(face.normed_embedding, reference_face.normed_embedding) | |
| return 0 | |
| def sort_and_filter_faces(faces : List[Face]) -> List[Face]: | |
| if faces: | |
| if state_manager.get_item('face_selector_order'): | |
| faces = sort_faces_by_order(faces, state_manager.get_item('face_selector_order')) | |
| if state_manager.get_item('face_selector_gender'): | |
| faces = filter_faces_by_gender(faces, state_manager.get_item('face_selector_gender')) | |
| if state_manager.get_item('face_selector_race'): | |
| faces = filter_faces_by_race(faces, state_manager.get_item('face_selector_race')) | |
| if state_manager.get_item('face_selector_age_start') or state_manager.get_item('face_selector_age_end'): | |
| faces = filter_faces_by_age(faces, state_manager.get_item('face_selector_age_start'), state_manager.get_item('face_selector_age_end')) | |
| return faces | |
| def sort_faces_by_order(faces : List[Face], order : FaceSelectorOrder) -> List[Face]: | |
| if order == 'left-right': | |
| return sorted(faces, key = lambda face: face.bounding_box[0]) | |
| if order == 'right-left': | |
| return sorted(faces, key = lambda face: face.bounding_box[0], reverse = True) | |
| if order == 'top-bottom': | |
| return sorted(faces, key = lambda face: face.bounding_box[1]) | |
| if order == 'bottom-top': | |
| return sorted(faces, key = lambda face: face.bounding_box[1], reverse = True) | |
| if order == 'small-large': | |
| return sorted(faces, key = lambda face: (face.bounding_box[2] - face.bounding_box[0]) * (face.bounding_box[3] - face.bounding_box[1])) | |
| if order == 'large-small': | |
| return sorted(faces, key = lambda face: (face.bounding_box[2] - face.bounding_box[0]) * (face.bounding_box[3] - face.bounding_box[1]), reverse = True) | |
| if order == 'best-worst': | |
| return sorted(faces, key = lambda face: face.score_set.get('detector'), reverse = True) | |
| if order == 'worst-best': | |
| return sorted(faces, key = lambda face: face.score_set.get('detector')) | |
| return faces | |
| def filter_faces_by_gender(faces : List[Face], gender : Gender) -> List[Face]: | |
| filter_faces = [] | |
| for face in faces: | |
| if face.gender == gender: | |
| filter_faces.append(face) | |
| return filter_faces | |
| def filter_faces_by_age(faces : List[Face], face_selector_age_start : int, face_selector_age_end : int) -> List[Face]: | |
| filter_faces = [] | |
| age = range(face_selector_age_start, face_selector_age_end) | |
| for face in faces: | |
| if set(face.age) & set(age): | |
| filter_faces.append(face) | |
| return filter_faces | |
| def filter_faces_by_race(faces : List[Face], race : Race) -> List[Face]: | |
| filter_faces = [] | |
| for face in faces: | |
| if face.race == race: | |
| filter_faces.append(face) | |
| return filter_faces | |