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| from argparse import ArgumentParser | |
| from typing import List | |
| import cv2 | |
| import numpy | |
| import scipy | |
| import facefusion.jobs.job_manager | |
| import facefusion.jobs.job_store | |
| import facefusion.processors.core as processors | |
| from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, inference_manager, logger, process_manager, state_manager, wording | |
| from facefusion.common_helper import create_float_metavar, map_float | |
| from facefusion.download import conditional_download_hashes, conditional_download_sources | |
| from facefusion.face_analyser import get_many_faces, get_one_face | |
| from facefusion.face_helper import paste_back, scale_face_landmark_5, warp_face_by_face_landmark_5 | |
| from facefusion.face_masker import create_occlusion_mask, create_static_box_mask | |
| from facefusion.face_selector import find_similar_faces, sort_and_filter_faces | |
| from facefusion.face_store import get_reference_faces | |
| from facefusion.filesystem import in_directory, is_image, is_video, resolve_relative_path, same_file_extension | |
| from facefusion.processors import choices as processors_choices | |
| from facefusion.processors.typing import FaceEditorInputs | |
| from facefusion.program_helper import find_argument_group | |
| from facefusion.thread_helper import thread_semaphore | |
| from facefusion.typing import Args, Expression, Face, FaceLandmark68, InferencePool, ModelOptions, ModelSet, MotionPoints, ProcessMode, QueuePayload, UpdateProgress, VisionFrame | |
| from facefusion.vision import read_image, read_static_image, write_image | |
| MODEL_SET : ModelSet =\ | |
| { | |
| 'live_portrait': | |
| { | |
| 'hashes': | |
| { | |
| 'feature_extractor': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_feature_extractor.hash', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.hash') | |
| }, | |
| 'motion_extractor': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_motion_extractor.hash', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.hash') | |
| }, | |
| 'eye_retargeter': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_eye_retargeter.hash', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_eye_retargeter.hash') | |
| }, | |
| 'lip_retargeter': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_lip_retargeter.hash', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_lip_retargeter.hash') | |
| }, | |
| 'generator': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_generator.hash', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_generator.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'feature_extractor': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_feature_extractor.onnx', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.onnx') | |
| }, | |
| 'motion_extractor': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_motion_extractor.onnx', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.onnx') | |
| }, | |
| 'eye_retargeter': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_eye_retargeter.onnx', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_eye_retargeter.onnx') | |
| }, | |
| 'lip_retargeter': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_lip_retargeter.onnx', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_lip_retargeter.onnx') | |
| }, | |
| 'generator': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_generator.onnx', | |
| 'path': resolve_relative_path('../.assets/models/live_portrait_generator.onnx') | |
| } | |
| }, | |
| 'template': 'ffhq_512', | |
| 'size': (512, 512) | |
| } | |
| } | |
| def get_inference_pool() -> InferencePool: | |
| model_sources = get_model_options().get('sources') | |
| return inference_manager.get_inference_pool(__name__, model_sources) | |
| def clear_inference_pool() -> None: | |
| inference_manager.clear_inference_pool(__name__) | |
| def get_model_options() -> ModelOptions: | |
| return MODEL_SET[state_manager.get_item('face_editor_model')] | |
| def register_args(program : ArgumentParser) -> None: | |
| group_processors = find_argument_group(program, 'processors') | |
| if group_processors: | |
| group_processors.add_argument('--face-editor-model', help = wording.get('help.face_editor_model'), default = config.get_str_value('processors.face_editor_model', 'live_portrait'), choices = processors_choices.face_editor_models) | |
| group_processors.add_argument('--face-editor-eyebrow-direction', help = wording.get('help.face_editor_eyebrow_direction'), type = float, default = config.get_float_value('processors.face_editor_eyebrow_direction', '0'), choices = processors_choices.face_editor_eyebrow_direction_range, metavar = create_float_metavar(processors_choices.face_editor_eyebrow_direction_range)) | |
| group_processors.add_argument('--face-editor-eye-gaze-horizontal', help = wording.get('help.face_editor_eye_gaze_horizontal'), type = float, default = config.get_float_value('processors.face_editor_eye_gaze_horizontal', '0'), choices = processors_choices.face_editor_eye_gaze_horizontal_range, metavar = create_float_metavar(processors_choices.face_editor_eye_gaze_horizontal_range)) | |
| group_processors.add_argument('--face-editor-eye-gaze-vertical', help = wording.get('help.face_editor_eye_gaze_vertical'), type = float, default = config.get_float_value('processors.face_editor_eye_gaze_vertical', '0'), choices = processors_choices.face_editor_eye_gaze_vertical_range, metavar = create_float_metavar(processors_choices.face_editor_eye_gaze_vertical_range)) | |
| group_processors.add_argument('--face-editor-eye-open-ratio', help = wording.get('help.face_editor_eye_open_ratio'), type = float, default = config.get_float_value('processors.face_editor_eye_open_ratio', '0'), choices = processors_choices.face_editor_eye_open_ratio_range, metavar = create_float_metavar(processors_choices.face_editor_eye_open_ratio_range)) | |
| group_processors.add_argument('--face-editor-lip-open-ratio', help = wording.get('help.face_editor_lip_open_ratio'), type = float, default = config.get_float_value('processors.face_editor_lip_open_ratio', '0'), choices = processors_choices.face_editor_lip_open_ratio_range, metavar = create_float_metavar(processors_choices.face_editor_lip_open_ratio_range)) | |
| group_processors.add_argument('--face-editor-mouth-grim', help = wording.get('help.face_editor_mouth_grim'), type = float, default = config.get_float_value('processors.face_editor_mouth_grim', '0'), choices = processors_choices.face_editor_mouth_grim_range, metavar = create_float_metavar(processors_choices.face_editor_mouth_grim_range)) | |
| group_processors.add_argument('--face-editor-mouth-pout', help = wording.get('help.face_editor_mouth_pout'), type = float, default = config.get_float_value('processors.face_editor_mouth_pout', '0'), choices = processors_choices.face_editor_mouth_pout_range, metavar = create_float_metavar(processors_choices.face_editor_mouth_pout_range)) | |
| group_processors.add_argument('--face-editor-mouth-purse', help = wording.get('help.face_editor_mouth_purse'), type = float, default = config.get_float_value('processors.face_editor_mouth_purse', '0'), choices = processors_choices.face_editor_mouth_purse_range, metavar = create_float_metavar(processors_choices.face_editor_mouth_purse_range)) | |
| group_processors.add_argument('--face-editor-mouth-smile', help = wording.get('help.face_editor_mouth_smile'), type = float, default = config.get_float_value('processors.face_editor_mouth_smile', '0'), choices = processors_choices.face_editor_mouth_smile_range, metavar = create_float_metavar(processors_choices.face_editor_mouth_smile_range)) | |
| group_processors.add_argument('--face-editor-mouth-position-horizontal', help = wording.get('help.face_editor_mouth_position_horizontal'), type = float, default = config.get_float_value('processors.face_editor_mouth_position_horizontal', '0'), choices = processors_choices.face_editor_mouth_position_horizontal_range, metavar = create_float_metavar(processors_choices.face_editor_mouth_position_horizontal_range)) | |
| group_processors.add_argument('--face-editor-mouth-position-vertical', help = wording.get('help.face_editor_mouth_position_vertical'), type = float, default = config.get_float_value('processors.face_editor_mouth_position_vertical', '0'), choices = processors_choices.face_editor_mouth_position_vertical_range, metavar = create_float_metavar(processors_choices.face_editor_mouth_position_vertical_range)) | |
| facefusion.jobs.job_store.register_step_keys([ 'face_editor_model', 'face_editor_eyebrow_direction', 'face_editor_eye_gaze_horizontal', 'face_editor_eye_gaze_vertical', 'face_editor_eye_open_ratio', 'face_editor_lip_open_ratio', 'face_editor_mouth_grim', 'face_editor_mouth_pout', 'face_editor_mouth_purse', 'face_editor_mouth_smile', 'face_editor_mouth_position_horizontal', 'face_editor_mouth_position_vertical' ]) | |
| def apply_args(args : Args) -> None: | |
| state_manager.init_item('face_editor_model', args.get('face_editor_model')) | |
| state_manager.init_item('face_editor_eyebrow_direction', args.get('face_editor_eyebrow_direction')) | |
| state_manager.init_item('face_editor_eye_gaze_horizontal', args.get('face_editor_eye_gaze_horizontal')) | |
| state_manager.init_item('face_editor_eye_gaze_vertical', args.get('face_editor_eye_gaze_vertical')) | |
| state_manager.init_item('face_editor_eye_open_ratio', args.get('face_editor_eye_open_ratio')) | |
| state_manager.init_item('face_editor_lip_open_ratio', args.get('face_editor_lip_open_ratio')) | |
| state_manager.init_item('face_editor_mouth_grim', args.get('face_editor_mouth_grim')) | |
| state_manager.init_item('face_editor_mouth_pout', args.get('face_editor_mouth_pout')) | |
| state_manager.init_item('face_editor_mouth_purse', args.get('face_editor_mouth_purse')) | |
| state_manager.init_item('face_editor_mouth_smile', args.get('face_editor_mouth_smile')) | |
| state_manager.init_item('face_editor_mouth_position_horizontal', args.get('face_editor_mouth_position_horizontal')) | |
| state_manager.init_item('face_editor_mouth_position_vertical', args.get('face_editor_mouth_position_vertical')) | |
| def pre_check() -> bool: | |
| download_directory_path = resolve_relative_path('../.assets/models') | |
| model_hashes = get_model_options().get('hashes') | |
| model_sources = get_model_options().get('sources') | |
| return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) | |
| def pre_process(mode : ProcessMode) -> bool: | |
| if mode in [ 'output', 'preview' ] and not is_image(state_manager.get_item('target_path')) and not is_video(state_manager.get_item('target_path')): | |
| logger.error(wording.get('choose_image_or_video_target') + wording.get('exclamation_mark'), __name__.upper()) | |
| return False | |
| if mode == 'output' and not in_directory(state_manager.get_item('output_path')): | |
| logger.error(wording.get('specify_image_or_video_output') + wording.get('exclamation_mark'), __name__.upper()) | |
| return False | |
| if mode == 'output' and not same_file_extension([ state_manager.get_item('target_path'), state_manager.get_item('output_path') ]): | |
| logger.error(wording.get('match_target_and_output_extension') + wording.get('exclamation_mark'), __name__.upper()) | |
| return False | |
| return True | |
| def post_process() -> None: | |
| read_static_image.cache_clear() | |
| if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]: | |
| clear_inference_pool() | |
| if state_manager.get_item('video_memory_strategy') == 'strict': | |
| content_analyser.clear_inference_pool() | |
| face_classifier.clear_inference_pool() | |
| face_detector.clear_inference_pool() | |
| face_landmarker.clear_inference_pool() | |
| face_masker.clear_inference_pool() | |
| face_recognizer.clear_inference_pool() | |
| def edit_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: | |
| model_template = get_model_options().get('template') | |
| model_size = get_model_options().get('size') | |
| face_landmark_5 = scale_face_landmark_5(target_face.landmark_set.get('5/68'), 1.2) | |
| crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, face_landmark_5, model_template, model_size) | |
| box_mask = create_static_box_mask(crop_vision_frame.shape[:2][::-1], state_manager.get_item('face_mask_blur'), (0, 0, 0, 0)) | |
| crop_masks =\ | |
| [ | |
| box_mask | |
| ] | |
| if 'occlusion' in state_manager.get_item('face_mask_types'): | |
| occlusion_mask = create_occlusion_mask(crop_vision_frame) | |
| crop_masks.append(occlusion_mask) | |
| crop_vision_frame = prepare_crop_frame(crop_vision_frame) | |
| crop_vision_frame = apply_edit(crop_vision_frame, target_face.landmark_set.get('68')) | |
| crop_vision_frame = normalize_crop_frame(crop_vision_frame) | |
| crop_mask = numpy.minimum.reduce(crop_masks).clip(0, 1) | |
| temp_vision_frame = paste_back(temp_vision_frame, crop_vision_frame, crop_mask, affine_matrix) | |
| return temp_vision_frame | |
| def apply_edit(crop_vision_frame : VisionFrame, face_landmark_68 : FaceLandmark68) -> VisionFrame: | |
| feature_extractor = get_inference_pool().get('feature_extractor') | |
| motion_extractor = get_inference_pool().get('motion_extractor') | |
| generator = get_inference_pool().get('generator') | |
| with thread_semaphore(): | |
| feature_volume = feature_extractor.run(None, | |
| { | |
| 'input': crop_vision_frame | |
| })[0] | |
| with thread_semaphore(): | |
| pitch, yaw, roll, scale, translation, expression, motion_points = motion_extractor.run(None, | |
| { | |
| 'input': crop_vision_frame | |
| }) | |
| rotation_matrix = scipy.spatial.transform.Rotation.from_euler('xyz', [ pitch, yaw, roll ], degrees = True).as_matrix() | |
| rotation_matrix = rotation_matrix.T.astype(numpy.float32) | |
| motion_points_transform = scale * (motion_points @ rotation_matrix + expression) + translation | |
| expression = edit_eye_gaze(expression) | |
| expression = edit_mouth_grim(expression) | |
| expression = edit_mouth_position(expression) | |
| expression = edit_mouth_pout(expression) | |
| expression = edit_mouth_purse(expression) | |
| expression = edit_mouth_smile(expression) | |
| expression = edit_eyebrow_direction(expression) | |
| motion_points_edit = motion_points @ rotation_matrix | |
| motion_points_edit += expression | |
| motion_points_edit *= scale | |
| motion_points_edit += translation | |
| motion_points_edit += edit_eye_open(motion_points_transform, face_landmark_68) | |
| motion_points_edit += edit_lip_open(motion_points_transform, face_landmark_68) | |
| with thread_semaphore(): | |
| crop_vision_frame = generator.run(None, | |
| { | |
| 'feature_volume': feature_volume, | |
| 'target': motion_points_transform, | |
| 'source': motion_points_edit | |
| })[0][0] | |
| return crop_vision_frame | |
| def edit_eyebrow_direction(expression : Expression) -> Expression: | |
| face_editor_eyebrow = state_manager.get_item('face_editor_eyebrow_direction') | |
| if face_editor_eyebrow > 0: | |
| expression[0, 1, 1] += map_float(face_editor_eyebrow, -1, 1, -0.015, 0.015) | |
| expression[0, 2, 1] -= map_float(face_editor_eyebrow, -1, 1, -0.020, 0.020) | |
| else: | |
| expression[0, 1, 0] -= map_float(face_editor_eyebrow, -1, 1, -0.015, 0.015) | |
| expression[0, 2, 0] += map_float(face_editor_eyebrow, -1, 1, -0.020, 0.020) | |
| expression[0, 1, 1] += map_float(face_editor_eyebrow, -1, 1, -0.005, 0.005) | |
| expression[0, 2, 1] -= map_float(face_editor_eyebrow, -1, 1, -0.005, 0.005) | |
| return expression | |
| def edit_eye_gaze(expression : Expression) -> Expression: | |
| face_editor_eye_gaze_horizontal = state_manager.get_item('face_editor_eye_gaze_horizontal') | |
| face_editor_eye_gaze_vertical = state_manager.get_item('face_editor_eye_gaze_vertical') | |
| if face_editor_eye_gaze_horizontal > 0: | |
| expression[0, 11, 0] += map_float(face_editor_eye_gaze_horizontal, -1, 1, -0.015, 0.015) | |
| expression[0, 15, 0] += map_float(face_editor_eye_gaze_horizontal, -1, 1, -0.020, 0.020) | |
| else: | |
| expression[0, 11, 0] += map_float(face_editor_eye_gaze_horizontal, -1, 1, -0.020, 0.020) | |
| expression[0, 15, 0] += map_float(face_editor_eye_gaze_horizontal, -1, 1, -0.015, 0.015) | |
| expression[0, 1, 1] += map_float(face_editor_eye_gaze_vertical, -1, 1, -0.0025, 0.0025) | |
| expression[0, 2, 1] -= map_float(face_editor_eye_gaze_vertical, -1, 1, -0.0025, 0.0025) | |
| expression[0, 11, 1] -= map_float(face_editor_eye_gaze_vertical, -1, 1, -0.010, 0.010) | |
| expression[0, 13, 1] -= map_float(face_editor_eye_gaze_vertical, -1, 1, -0.005, 0.005) | |
| expression[0, 15, 1] -= map_float(face_editor_eye_gaze_vertical, -1, 1, -0.010, 0.010) | |
| expression[0, 16, 1] -= map_float(face_editor_eye_gaze_vertical, -1, 1, -0.005, 0.005) | |
| return expression | |
| def edit_eye_open(motion_points : MotionPoints, face_landmark_68 : FaceLandmark68) -> MotionPoints: | |
| eye_retargeter = get_inference_pool().get('eye_retargeter') | |
| face_editor_eye_open_ratio = state_manager.get_item('face_editor_eye_open_ratio') | |
| left_eye_ratio = calc_distance_ratio(face_landmark_68, 37, 40, 39, 36) | |
| right_eye_ratio = calc_distance_ratio(face_landmark_68, 43, 46, 45, 42) | |
| if face_editor_eye_open_ratio < 0: | |
| close_eye_motion_points = numpy.concatenate([ motion_points.ravel(), [ left_eye_ratio, right_eye_ratio, 0.0 ] ]) | |
| close_eye_motion_points = close_eye_motion_points.reshape(1, -1).astype(numpy.float32) | |
| with thread_semaphore(): | |
| close_eye_motion_points = eye_retargeter.run(None, | |
| { | |
| 'input': close_eye_motion_points | |
| })[0] | |
| eye_motion_points = close_eye_motion_points * face_editor_eye_open_ratio * -1 | |
| else: | |
| open_eye_motion_points = numpy.concatenate([ motion_points.ravel(), [ left_eye_ratio, right_eye_ratio, 0.8 ] ]) | |
| open_eye_motion_points = open_eye_motion_points.reshape(1, -1).astype(numpy.float32) | |
| with thread_semaphore(): | |
| open_eye_motion_points = eye_retargeter.run(None, | |
| { | |
| 'input': open_eye_motion_points | |
| })[0] | |
| eye_motion_points = open_eye_motion_points * face_editor_eye_open_ratio | |
| eye_motion_points = eye_motion_points.reshape(-1, 21, 3) | |
| return eye_motion_points | |
| def edit_lip_open(motion_points : MotionPoints, face_landmark_68 : FaceLandmark68) -> MotionPoints: | |
| lip_retargeter = get_inference_pool().get('lip_retargeter') | |
| face_editor_lip_open_ratio = state_manager.get_item('face_editor_lip_open_ratio') | |
| lip_ratio = calc_distance_ratio(face_landmark_68, 62, 66, 54, 48) | |
| if face_editor_lip_open_ratio < 0: | |
| close_lip_motion_points = numpy.concatenate([ motion_points.ravel(), [ lip_ratio, 0.0 ] ]) | |
| close_lip_motion_points = close_lip_motion_points.reshape(1, -1).astype(numpy.float32) | |
| with thread_semaphore(): | |
| close_lip_motion_points = lip_retargeter.run(None, | |
| { | |
| 'input': close_lip_motion_points | |
| })[0] | |
| lip_motion_points = close_lip_motion_points * face_editor_lip_open_ratio * -1 | |
| else: | |
| open_lip_motion_points = numpy.concatenate([ motion_points.ravel(), [ lip_ratio, 1.3 ] ]) | |
| open_lip_motion_points = open_lip_motion_points.reshape(1, -1).astype(numpy.float32) | |
| with thread_semaphore(): | |
| open_lip_motion_points = lip_retargeter.run(None, | |
| { | |
| 'input': open_lip_motion_points | |
| })[0] | |
| lip_motion_points = open_lip_motion_points * face_editor_lip_open_ratio | |
| lip_motion_points = lip_motion_points.reshape(-1, 21, 3) | |
| return lip_motion_points | |
| def edit_mouth_grim(expression : Expression) -> Expression: | |
| face_editor_mouth_grim = state_manager.get_item('face_editor_mouth_grim') | |
| if face_editor_mouth_grim > 0: | |
| expression[0, 17, 2] -= map_float(face_editor_mouth_grim, -1, 1, -0.005, 0.005) | |
| expression[0, 19, 2] += map_float(face_editor_mouth_grim, -1, 1, -0.01, 0.01) | |
| expression[0, 20, 1] -= map_float(face_editor_mouth_grim, -1, 1, -0.06, 0.06) | |
| expression[0, 20, 2] -= map_float(face_editor_mouth_grim, -1, 1, -0.03, 0.03) | |
| else: | |
| expression[0, 19, 1] -= map_float(face_editor_mouth_grim, -1, 1, -0.05, 0.05) | |
| expression[0, 19, 2] -= map_float(face_editor_mouth_grim, -1, 1, -0.02, 0.02) | |
| expression[0, 20, 2] -= map_float(face_editor_mouth_grim, -1, 1, -0.03, 0.03) | |
| return expression | |
| def edit_mouth_position(expression : Expression) -> Expression: | |
| face_editor_mouth_position_horizontal = state_manager.get_item('face_editor_mouth_position_horizontal') | |
| face_editor_mouth_position_vertical = state_manager.get_item('face_editor_mouth_position_vertical') | |
| expression[0, 19, 0] += map_float(face_editor_mouth_position_horizontal, -1, 1, -0.05, 0.05) | |
| expression[0, 20, 0] += map_float(face_editor_mouth_position_horizontal, -1, 1, -0.04, 0.04) | |
| if face_editor_mouth_position_vertical > 0: | |
| expression[0, 19, 1] -= map_float(face_editor_mouth_position_vertical, -1, 1, -0.04, 0.04) | |
| expression[0, 20, 1] -= map_float(face_editor_mouth_position_vertical, -1, 1, -0.02, 0.02) | |
| else: | |
| expression[0, 19, 1] -= map_float(face_editor_mouth_position_vertical, -1, 1, -0.05, 0.05) | |
| expression[0, 20, 1] -= map_float(face_editor_mouth_position_vertical, -1, 1, -0.04, 0.04) | |
| return expression | |
| def edit_mouth_pout(expression : Expression) -> Expression: | |
| face_editor_mouth_pout = state_manager.get_item('face_editor_mouth_pout') | |
| if face_editor_mouth_pout > 0: | |
| expression[0, 19, 1] -= map_float(face_editor_mouth_pout, -1, 1, -0.022, 0.022) | |
| expression[0, 19, 2] += map_float(face_editor_mouth_pout, -1, 1, -0.025, 0.025) | |
| expression[0, 20, 2] -= map_float(face_editor_mouth_pout, -1, 1, -0.002, 0.002) | |
| else: | |
| expression[0, 19, 1] += map_float(face_editor_mouth_pout, -1, 1, -0.022, 0.022) | |
| expression[0, 19, 2] += map_float(face_editor_mouth_pout, -1, 1, -0.025, 0.025) | |
| expression[0, 20, 2] -= map_float(face_editor_mouth_pout, -1, 1, -0.002, 0.002) | |
| return expression | |
| def edit_mouth_purse(expression : Expression) -> Expression: | |
| face_editor_mouth_purse = state_manager.get_item('face_editor_mouth_purse') | |
| if face_editor_mouth_purse > 0: | |
| expression[0, 19, 1] -= map_float(face_editor_mouth_purse, -1, 1, -0.04, 0.04) | |
| expression[0, 19, 2] -= map_float(face_editor_mouth_purse, -1, 1, -0.02, 0.02) | |
| else: | |
| expression[0, 14, 1] -= map_float(face_editor_mouth_purse, -1, 1, -0.02, 0.02) | |
| expression[0, 17, 2] += map_float(face_editor_mouth_purse, -1, 1, -0.01, 0.01) | |
| expression[0, 19, 2] -= map_float(face_editor_mouth_purse, -1, 1, -0.015, 0.015) | |
| expression[0, 20, 2] -= map_float(face_editor_mouth_purse, -1, 1, -0.002, 0.002) | |
| return expression | |
| def edit_mouth_smile(expression : Expression) -> Expression: | |
| face_editor_mouth_smile = state_manager.get_item('face_editor_mouth_smile') | |
| if face_editor_mouth_smile > 0: | |
| expression[0, 20, 1] -= map_float(face_editor_mouth_smile, -1, 1, -0.015, 0.015) | |
| expression[0, 14, 1] -= map_float(face_editor_mouth_smile, -1, 1, -0.025, 0.025) | |
| expression[0, 17, 1] += map_float(face_editor_mouth_smile, -1, 1, -0.01, 0.01) | |
| expression[0, 17, 2] += map_float(face_editor_mouth_smile, -1, 1, -0.004, 0.004) | |
| expression[0, 3, 1] -= map_float(face_editor_mouth_smile, -1, 1, -0.0045, 0.0045) | |
| expression[0, 7, 1] -= map_float(face_editor_mouth_smile, -1, 1, -0.0045, 0.0045) | |
| else: | |
| expression[0, 14, 1] -= map_float(face_editor_mouth_smile, -1, 1, -0.02, 0.02) | |
| expression[0, 17, 1] += map_float(face_editor_mouth_smile, -1, 1, -0.003, 0.003) | |
| expression[0, 19, 1] += map_float(face_editor_mouth_smile, -1, 1, -0.02, 0.02) | |
| expression[0, 19, 2] -= map_float(face_editor_mouth_smile, -1, 1, -0.005, 0.005) | |
| expression[0, 20, 2] += map_float(face_editor_mouth_smile, -1, 1, -0.01, 0.01) | |
| expression[0, 3, 1] += map_float(face_editor_mouth_smile, -1, 1, -0.0045, 0.0045) | |
| expression[0, 7, 1] += map_float(face_editor_mouth_smile, -1, 1, -0.0045, 0.0045) | |
| return expression | |
| def calc_distance_ratio(face_landmark_68 : FaceLandmark68, top_index : int, bottom_index : int, left_index : int, right_index : int) -> float: | |
| vertical_direction = face_landmark_68[top_index] - face_landmark_68[bottom_index] | |
| horizontal_direction = face_landmark_68[left_index] - face_landmark_68[right_index] | |
| distance_ratio = float(numpy.linalg.norm(vertical_direction) / (numpy.linalg.norm(horizontal_direction) + 1e-6)) | |
| return distance_ratio | |
| def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame: | |
| crop_vision_frame = cv2.resize(crop_vision_frame, (256, 256), interpolation = cv2.INTER_AREA) | |
| crop_vision_frame = crop_vision_frame[:, :, ::-1] / 255.0 | |
| crop_vision_frame = numpy.expand_dims(crop_vision_frame.transpose(2, 0, 1), axis = 0).astype(numpy.float32) | |
| return crop_vision_frame | |
| def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame: | |
| crop_vision_frame = crop_vision_frame.transpose(1, 2, 0).clip(0, 1) | |
| crop_vision_frame = (crop_vision_frame * 255.0) | |
| crop_vision_frame = crop_vision_frame.astype(numpy.uint8)[:, :, ::-1] | |
| return crop_vision_frame | |
| def get_reference_frame(source_face : Face, target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: | |
| pass | |
| def process_frame(inputs : FaceEditorInputs) -> VisionFrame: | |
| reference_faces = inputs.get('reference_faces') | |
| target_vision_frame = inputs.get('target_vision_frame') | |
| many_faces = sort_and_filter_faces(get_many_faces([ target_vision_frame ])) | |
| if state_manager.get_item('face_selector_mode') == 'many': | |
| if many_faces: | |
| for target_face in many_faces: | |
| target_vision_frame = edit_face(target_face, target_vision_frame) | |
| if state_manager.get_item('face_selector_mode') == 'one': | |
| target_face = get_one_face(many_faces) | |
| if target_face: | |
| target_vision_frame = edit_face(target_face, target_vision_frame) | |
| if state_manager.get_item('face_selector_mode') == 'reference': | |
| similar_faces = find_similar_faces(many_faces, reference_faces, state_manager.get_item('reference_face_distance')) | |
| if similar_faces: | |
| for similar_face in similar_faces: | |
| target_vision_frame = edit_face(similar_face, target_vision_frame) | |
| return target_vision_frame | |
| def process_frames(source_path : List[str], queue_payloads : List[QueuePayload], update_progress : UpdateProgress) -> None: | |
| reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None | |
| for queue_payload in process_manager.manage(queue_payloads): | |
| target_vision_path = queue_payload['frame_path'] | |
| target_vision_frame = read_image(target_vision_path) | |
| output_vision_frame = process_frame( | |
| { | |
| 'reference_faces': reference_faces, | |
| 'target_vision_frame': target_vision_frame | |
| }) | |
| write_image(target_vision_path, output_vision_frame) | |
| update_progress(1) | |
| def process_image(source_path : str, target_path : str, output_path : str) -> None: | |
| reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None | |
| target_vision_frame = read_static_image(target_path) | |
| output_vision_frame = process_frame( | |
| { | |
| 'reference_faces': reference_faces, | |
| 'target_vision_frame': target_vision_frame | |
| }) | |
| write_image(output_path, output_vision_frame) | |
| def process_video(source_paths : List[str], temp_frame_paths : List[str]) -> None: | |
| processors.multi_process_frames(None, temp_frame_paths, process_frames) | |