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| from typing import Any, List, Literal | |
| from argparse import ArgumentParser | |
| import cv2 | |
| import numpy | |
| import facefusion.globals | |
| import facefusion.processors.frame.core as frame_processors | |
| from facefusion import wording | |
| from facefusion.face_analyser import get_one_face, get_average_face, get_many_faces, find_similar_faces, clear_face_analyser | |
| from facefusion.face_store import get_reference_faces | |
| from facefusion.content_analyser import clear_content_analyser | |
| from facefusion.typing import Face, FaceSet, Frame, Update_Process, ProcessMode | |
| from facefusion.vision import read_image, read_static_image, read_static_images, write_image | |
| from facefusion.face_helper import warp_face | |
| from facefusion.face_masker import create_static_box_mask, create_occlusion_mask, create_region_mask, clear_face_occluder, clear_face_parser | |
| from facefusion.processors.frame import globals as frame_processors_globals, choices as frame_processors_choices | |
| NAME = __name__.upper() | |
| def get_frame_processor() -> None: | |
| pass | |
| def clear_frame_processor() -> None: | |
| pass | |
| def get_options(key : Literal['model']) -> None: | |
| pass | |
| def set_options(key : Literal['model'], value : Any) -> None: | |
| pass | |
| def register_args(program : ArgumentParser) -> None: | |
| program.add_argument('--face-debugger-items', help = wording.get('face_debugger_items_help').format(choices = ', '.join(frame_processors_choices.face_debugger_items)), default = [ 'kps', 'face-mask' ], choices = frame_processors_choices.face_debugger_items, nargs = '+', metavar = 'FACE_DEBUGGER_ITEMS') | |
| def apply_args(program : ArgumentParser) -> None: | |
| args = program.parse_args() | |
| frame_processors_globals.face_debugger_items = args.face_debugger_items | |
| def pre_check() -> bool: | |
| return True | |
| def pre_process(mode : ProcessMode) -> bool: | |
| return True | |
| def post_process() -> None: | |
| clear_frame_processor() | |
| clear_face_analyser() | |
| clear_content_analyser() | |
| clear_face_occluder() | |
| clear_face_parser() | |
| read_static_image.cache_clear() | |
| def debug_face(source_face : Face, target_face : Face, temp_frame : Frame) -> Frame: | |
| primary_color = (0, 0, 255) | |
| secondary_color = (0, 255, 0) | |
| bounding_box = target_face.bbox.astype(numpy.int32) | |
| if 'bbox' in frame_processors_globals.face_debugger_items: | |
| cv2.rectangle(temp_frame, (bounding_box[0], bounding_box[1]), (bounding_box[2], bounding_box[3]), secondary_color, 2) | |
| if 'face-mask' in frame_processors_globals.face_debugger_items: | |
| crop_frame, affine_matrix = warp_face(temp_frame, target_face.kps, 'arcface_128_v2', (128, 512)) | |
| inverse_matrix = cv2.invertAffineTransform(affine_matrix) | |
| temp_frame_size = temp_frame.shape[:2][::-1] | |
| crop_mask_list = [] | |
| if 'box' in facefusion.globals.face_mask_types: | |
| crop_mask_list.append(create_static_box_mask(crop_frame.shape[:2][::-1], 0, facefusion.globals.face_mask_padding)) | |
| if 'occlusion' in facefusion.globals.face_mask_types: | |
| crop_mask_list.append(create_occlusion_mask(crop_frame)) | |
| if 'region' in facefusion.globals.face_mask_types: | |
| crop_mask_list.append(create_region_mask(crop_frame, facefusion.globals.face_mask_regions)) | |
| crop_mask = numpy.minimum.reduce(crop_mask_list).clip(0, 1) | |
| crop_mask = (crop_mask * 255).astype(numpy.uint8) | |
| inverse_mask_frame = cv2.warpAffine(crop_mask, inverse_matrix, temp_frame_size) | |
| inverse_mask_frame_edges = cv2.threshold(inverse_mask_frame, 100, 255, cv2.THRESH_BINARY)[1] | |
| inverse_mask_frame_edges[inverse_mask_frame_edges > 0] = 255 | |
| inverse_mask_contours = cv2.findContours(inverse_mask_frame_edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)[0] | |
| cv2.drawContours(temp_frame, inverse_mask_contours, -1, primary_color, 2) | |
| if bounding_box[3] - bounding_box[1] > 60 and bounding_box[2] - bounding_box[0] > 60: | |
| if 'kps' in frame_processors_globals.face_debugger_items: | |
| kps = target_face.kps.astype(numpy.int32) | |
| for index in range(kps.shape[0]): | |
| cv2.circle(temp_frame, (kps[index][0], kps[index][1]), 3, primary_color, -1) | |
| if 'score' in frame_processors_globals.face_debugger_items: | |
| score_text = str(round(target_face.score, 2)) | |
| score_position = (bounding_box[0] + 10, bounding_box[1] + 20) | |
| cv2.putText(temp_frame, score_text, score_position, cv2.FONT_HERSHEY_SIMPLEX, 0.5, secondary_color, 2) | |
| return temp_frame | |
| def get_reference_frame(source_face : Face, target_face : Face, temp_frame : Frame) -> Frame: | |
| pass | |
| def process_frame(source_face : Face, reference_faces : FaceSet, temp_frame : Frame) -> Frame: | |
| if 'reference' in facefusion.globals.face_selector_mode: | |
| similar_faces = find_similar_faces(temp_frame, reference_faces, facefusion.globals.reference_face_distance) | |
| if similar_faces: | |
| for similar_face in similar_faces: | |
| temp_frame = debug_face(source_face, similar_face, temp_frame) | |
| if 'one' in facefusion.globals.face_selector_mode: | |
| target_face = get_one_face(temp_frame) | |
| if target_face: | |
| temp_frame = debug_face(source_face, target_face, temp_frame) | |
| if 'many' in facefusion.globals.face_selector_mode: | |
| many_faces = get_many_faces(temp_frame) | |
| if many_faces: | |
| for target_face in many_faces: | |
| temp_frame = debug_face(source_face, target_face, temp_frame) | |
| return temp_frame | |
| def process_frames(source_paths : List[str], temp_frame_paths : List[str], update_progress : Update_Process) -> None: | |
| source_frames = read_static_images(source_paths) | |
| source_face = get_average_face(source_frames) | |
| reference_faces = get_reference_faces() if 'reference' in facefusion.globals.face_selector_mode else None | |
| for temp_frame_path in temp_frame_paths: | |
| temp_frame = read_image(temp_frame_path) | |
| result_frame = process_frame(source_face, reference_faces, temp_frame) | |
| write_image(temp_frame_path, result_frame) | |
| update_progress() | |
| def process_image(source_paths : List[str], target_path : str, output_path : str) -> None: | |
| source_frames = read_static_images(source_paths) | |
| source_face = get_average_face(source_frames) | |
| target_frame = read_static_image(target_path) | |
| reference_faces = get_reference_faces() if 'reference' in facefusion.globals.face_selector_mode else None | |
| result_frame = process_frame(source_face, reference_faces, target_frame) | |
| write_image(output_path, result_frame) | |
| def process_video(source_paths : List[str], temp_frame_paths : List[str]) -> None: | |
| frame_processors.multi_process_frames(source_paths, temp_frame_paths, process_frames) | |