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| from argparse import ArgumentParser | |
| from typing import List, Tuple | |
| import numpy | |
| 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 get_first | |
| from facefusion.download import conditional_download_hashes, conditional_download_sources | |
| from facefusion.execution import has_execution_provider | |
| from facefusion.face_analyser import get_average_face, get_many_faces, get_one_face | |
| from facefusion.face_helper import paste_back, warp_face_by_face_landmark_5 | |
| from facefusion.face_masker import create_occlusion_mask, create_region_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 filter_image_paths, has_image, in_directory, is_image, is_video, resolve_relative_path, same_file_extension | |
| from facefusion.inference_manager import get_static_model_initializer | |
| from facefusion.processors import choices as processors_choices | |
| from facefusion.processors.pixel_boost import explode_pixel_boost, implode_pixel_boost | |
| from facefusion.processors.typing import FaceSwapperInputs | |
| from facefusion.program_helper import find_argument_group, suggest_face_swapper_pixel_boost_choices | |
| from facefusion.thread_helper import conditional_thread_semaphore | |
| from facefusion.typing import Args, Embedding, Face, FaceLandmark5, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame | |
| from facefusion.vision import read_image, read_static_image, read_static_images, unpack_resolution, write_image | |
| MODEL_SET : ModelSet =\ | |
| { | |
| 'blendswap_256': | |
| { | |
| 'hashes': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/blendswap_256.hash', | |
| 'path': resolve_relative_path('../.assets/models/blendswap_256.hash') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_w600k_r50.hash', | |
| 'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/blendswap_256.onnx', | |
| 'path': resolve_relative_path('../.assets/models/blendswap_256.onnx') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_w600k_r50.onnx', | |
| 'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.onnx') | |
| } | |
| }, | |
| 'type': 'blendswap', | |
| 'template': 'ffhq_512', | |
| 'size': (256, 256), | |
| 'mean': [ 0.0, 0.0, 0.0 ], | |
| 'standard_deviation': [ 1.0, 1.0, 1.0 ] | |
| }, | |
| 'ghost_256_unet_1': | |
| { | |
| 'hashes': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_256_unet_1.hash', | |
| 'path': resolve_relative_path('../.assets/models/ghost_256_unet_1.hash') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_ghost.hash', | |
| 'path': resolve_relative_path('../.assets/models/arcface_ghost.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_256_unet_1.onnx', | |
| 'path': resolve_relative_path('../.assets/models/ghost_256_unet_1.onnx') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_ghost.onnx', | |
| 'path': resolve_relative_path('../.assets/models/arcface_ghost.onnx') | |
| } | |
| }, | |
| 'type': 'ghost', | |
| 'template': 'arcface_112_v1', | |
| 'size': (256, 256), | |
| 'mean': [ 0.0, 0.0, 0.0 ], | |
| 'standard_deviation': [ 1.0, 1.0, 1.0 ] | |
| }, | |
| 'ghost_256_unet_2': | |
| { | |
| 'hashes': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_256_unet_2.hash', | |
| 'path': resolve_relative_path('../.assets/models/ghost_256_unet_2.hash') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_ghost.hash', | |
| 'path': resolve_relative_path('../.assets/models/arcface_ghost.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_256_unet_2.onnx', | |
| 'path': resolve_relative_path('../.assets/models/ghost_256_unet_2.onnx') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_ghost.onnx', | |
| 'path': resolve_relative_path('../.assets/models/arcface_ghost.onnx') | |
| } | |
| }, | |
| 'type': 'ghost', | |
| 'template': 'arcface_112_v1', | |
| 'size': (256, 256), | |
| 'mean': [ 0.0, 0.0, 0.0 ], | |
| 'standard_deviation': [ 1.0, 1.0, 1.0 ] | |
| }, | |
| 'ghost_256_unet_3': | |
| { | |
| 'hashes': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_256_unet_3.hash', | |
| 'path': resolve_relative_path('../.assets/models/ghost_256_unet_3.hash') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_ghost.hash', | |
| 'path': resolve_relative_path('../.assets/models/arcface_ghost.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_256_unet_3.onnx', | |
| 'path': resolve_relative_path('../.assets/models/ghost_256_unet_3.onnx') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_ghost.onnx', | |
| 'path': resolve_relative_path('../.assets/models/arcface_ghost.onnx') | |
| } | |
| }, | |
| 'type': 'ghost', | |
| 'template': 'arcface_112_v1', | |
| 'size': (256, 256), | |
| 'mean': [ 0.0, 0.0, 0.0 ], | |
| 'standard_deviation': [ 1.0, 1.0, 1.0 ] | |
| }, | |
| 'inswapper_128': | |
| { | |
| 'hashes': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/inswapper_128.hash', | |
| 'path': resolve_relative_path('../.assets/models/inswapper_128.hash') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0//arcface_w600k_r50.hash', | |
| 'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/inswapper_128.onnx', | |
| 'path': resolve_relative_path('../.assets/models/inswapper_128.onnx') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_w600k_r50.onnx', | |
| 'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.onnx') | |
| } | |
| }, | |
| 'type': 'inswapper', | |
| 'template': 'arcface_128_v2', | |
| 'size': (128, 128), | |
| 'mean': [ 0.0, 0.0, 0.0 ], | |
| 'standard_deviation': [ 1.0, 1.0, 1.0 ] | |
| }, | |
| 'inswapper_128_fp16': | |
| { | |
| 'hashes': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/inswapper_128_fp16.hash', | |
| 'path': resolve_relative_path('../.assets/models/inswapper_128_fp16.hash') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_w600k_r50.hash', | |
| 'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/inswapper_128_fp16.onnx', | |
| 'path': resolve_relative_path('../.assets/models/inswapper_128_fp16.onnx') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_w600k_r50.onnx', | |
| 'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.onnx') | |
| } | |
| }, | |
| 'type': 'inswapper', | |
| 'template': 'arcface_128_v2', | |
| 'size': (128, 128), | |
| 'mean': [ 0.0, 0.0, 0.0 ], | |
| 'standard_deviation': [ 1.0, 1.0, 1.0 ] | |
| }, | |
| 'simswap_256': | |
| { | |
| 'hashes': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/simswap_256.hash', | |
| 'path': resolve_relative_path('../.assets/models/simswap_256.hash') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_simswap.hash', | |
| 'path': resolve_relative_path('../.assets/models/arcface_simswap.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/simswap_256.onnx', | |
| 'path': resolve_relative_path('../.assets/models/simswap_256.onnx') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_simswap.onnx', | |
| 'path': resolve_relative_path('../.assets/models/arcface_simswap.onnx') | |
| } | |
| }, | |
| 'type': 'simswap', | |
| 'template': 'arcface_112_v1', | |
| 'size': (256, 256), | |
| 'mean': [ 0.485, 0.456, 0.406 ], | |
| 'standard_deviation': [ 0.229, 0.224, 0.225 ] | |
| }, | |
| 'simswap_512_unofficial': | |
| { | |
| 'hashes': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/simswap_512_unofficial.hash', | |
| 'path': resolve_relative_path('../.assets/models/simswap_512_unofficial.hash') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_simswap.hash', | |
| 'path': resolve_relative_path('../.assets/models/arcface_simswap.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/simswap_512_unofficial.onnx', | |
| 'path': resolve_relative_path('../.assets/models/simswap_512_unofficial.onnx') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_simswap.onnx', | |
| 'path': resolve_relative_path('../.assets/models/arcface_simswap.onnx') | |
| } | |
| }, | |
| 'type': 'simswap', | |
| 'template': 'arcface_112_v1', | |
| 'size': (512, 512), | |
| 'mean': [ 0.0, 0.0, 0.0 ], | |
| 'standard_deviation': [ 1.0, 1.0, 1.0 ] | |
| }, | |
| 'uniface_256': | |
| { | |
| 'hashes': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/uniface_256.hash', | |
| 'path': resolve_relative_path('../.assets/models/uniface_256.hash') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_w600k_r50.hash', | |
| 'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.hash') | |
| } | |
| }, | |
| 'sources': | |
| { | |
| 'face_swapper': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/uniface_256.onnx', | |
| 'path': resolve_relative_path('../.assets/models/uniface_256.onnx') | |
| }, | |
| 'face_recognizer': | |
| { | |
| 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_w600k_r50.onnx', | |
| 'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.onnx') | |
| } | |
| }, | |
| 'type': 'uniface', | |
| 'template': 'ffhq_512', | |
| 'size': (256, 256), | |
| 'mean': [ 0.0, 0.0, 0.0 ], | |
| 'standard_deviation': [ 1.0, 1.0, 1.0 ] | |
| } | |
| } | |
| 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: | |
| face_swapper_model = 'inswapper_128' if has_execution_provider('coreml') and state_manager.get_item('face_swapper_model') == 'inswapper_128_fp16' else state_manager.get_item('face_swapper_model') | |
| return MODEL_SET[face_swapper_model] | |
| def register_args(program : ArgumentParser) -> None: | |
| group_processors = find_argument_group(program, 'processors') | |
| if group_processors: | |
| group_processors.add_argument('--face-swapper-model', help = wording.get('help.face_swapper_model'), default = config.get_str_value('processors.face_swapper_model', 'inswapper_128_fp16'), choices = processors_choices.face_swapper_set.keys()) | |
| face_swapper_pixel_boost_choices = suggest_face_swapper_pixel_boost_choices(program) | |
| group_processors.add_argument('--face-swapper-pixel-boost', help = wording.get('help.face_swapper_pixel_boost'), default = config.get_str_value('processors.face_swapper_pixel_boost', get_first(face_swapper_pixel_boost_choices)), choices = face_swapper_pixel_boost_choices) | |
| facefusion.jobs.job_store.register_step_keys([ 'face_swapper_model', 'face_swapper_pixel_boost' ]) | |
| def apply_args(args : Args) -> None: | |
| state_manager.init_item('face_swapper_model', args.get('face_swapper_model')) | |
| state_manager.init_item('face_swapper_pixel_boost', args.get('face_swapper_pixel_boost')) | |
| 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 not has_image(state_manager.get_item('source_paths')): | |
| logger.error(wording.get('choose_image_source') + wording.get('exclamation_mark'), __name__.upper()) | |
| return False | |
| source_image_paths = filter_image_paths(state_manager.get_item('source_paths')) | |
| source_frames = read_static_images(source_image_paths) | |
| source_faces = get_many_faces(source_frames) | |
| if not get_one_face(source_faces): | |
| logger.error(wording.get('no_source_face_detected') + wording.get('exclamation_mark'), __name__.upper()) | |
| return False | |
| 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() | |
| get_static_model_initializer.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 swap_face(source_face : Face, target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: | |
| model_template = get_model_options().get('template') | |
| model_size = get_model_options().get('size') | |
| pixel_boost_size = unpack_resolution(state_manager.get_item('face_swapper_pixel_boost')) | |
| pixel_boost_total = pixel_boost_size[0] // model_size[0] | |
| crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, target_face.landmark_set.get('5/68'), model_template, pixel_boost_size) | |
| crop_masks = [] | |
| temp_vision_frames = [] | |
| if 'box' in state_manager.get_item('face_mask_types'): | |
| box_mask = create_static_box_mask(crop_vision_frame.shape[:2][::-1], state_manager.get_item('face_mask_blur'), state_manager.get_item('face_mask_padding')) | |
| crop_masks.append(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) | |
| pixel_boost_vision_frames = implode_pixel_boost(crop_vision_frame, pixel_boost_total, model_size) | |
| for pixel_boost_vision_frame in pixel_boost_vision_frames: | |
| pixel_boost_vision_frame = prepare_crop_frame(pixel_boost_vision_frame) | |
| pixel_boost_vision_frame = apply_swap(source_face, pixel_boost_vision_frame) | |
| pixel_boost_vision_frame = normalize_crop_frame(pixel_boost_vision_frame) | |
| temp_vision_frames.append(pixel_boost_vision_frame) | |
| crop_vision_frame = explode_pixel_boost(temp_vision_frames, pixel_boost_total, model_size, pixel_boost_size) | |
| if 'region' in state_manager.get_item('face_mask_types'): | |
| region_mask = create_region_mask(crop_vision_frame, state_manager.get_item('face_mask_regions')) | |
| crop_masks.append(region_mask) | |
| 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_swap(source_face : Face, crop_vision_frame : VisionFrame) -> VisionFrame: | |
| face_swapper = get_inference_pool().get('face_swapper') | |
| model_type = get_model_options().get('type') | |
| face_swapper_inputs = {} | |
| for face_swapper_input in face_swapper.get_inputs(): | |
| if face_swapper_input.name == 'source': | |
| if model_type == 'blendswap' or model_type == 'uniface': | |
| face_swapper_inputs[face_swapper_input.name] = prepare_source_frame(source_face) | |
| else: | |
| face_swapper_inputs[face_swapper_input.name] = prepare_source_embedding(source_face) | |
| if face_swapper_input.name == 'target': | |
| face_swapper_inputs[face_swapper_input.name] = crop_vision_frame | |
| with conditional_thread_semaphore(): | |
| crop_vision_frame = face_swapper.run(None, face_swapper_inputs)[0][0] | |
| return crop_vision_frame | |
| def prepare_source_frame(source_face : Face) -> VisionFrame: | |
| model_type = get_model_options().get('type') | |
| source_vision_frame = read_static_image(get_first(state_manager.get_item('source_paths'))) | |
| if model_type == 'blendswap': | |
| source_vision_frame, _ = warp_face_by_face_landmark_5(source_vision_frame, source_face.landmark_set.get('5/68'), 'arcface_112_v2', (112, 112)) | |
| if model_type == 'uniface': | |
| source_vision_frame, _ = warp_face_by_face_landmark_5(source_vision_frame, source_face.landmark_set.get('5/68'), 'ffhq_512', (256, 256)) | |
| source_vision_frame = source_vision_frame[:, :, ::-1] / 255.0 | |
| source_vision_frame = source_vision_frame.transpose(2, 0, 1) | |
| source_vision_frame = numpy.expand_dims(source_vision_frame, axis = 0).astype(numpy.float32) | |
| return source_vision_frame | |
| def prepare_source_embedding(source_face : Face) -> Embedding: | |
| model_type = get_model_options().get('type') | |
| source_vision_frame = read_static_image(get_first(state_manager.get_item('source_paths'))) | |
| source_embedding, source_normed_embedding = calc_embedding(source_vision_frame, source_face.landmark_set.get('5/68')) | |
| if model_type == 'ghost': | |
| source_embedding = source_embedding.reshape(1, -1) | |
| elif model_type == 'inswapper': | |
| model_path = get_model_options().get('sources').get('face_swapper').get('path') | |
| model_initializer = get_static_model_initializer(model_path) | |
| source_embedding = source_embedding.reshape((1, -1)) | |
| source_embedding = numpy.dot(source_embedding, model_initializer) / numpy.linalg.norm(source_embedding) | |
| else: | |
| source_embedding = source_normed_embedding.reshape(1, -1) | |
| return source_embedding | |
| def calc_embedding(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmark5) -> Tuple[Embedding, Embedding]: | |
| face_recognizer = get_inference_pool().get('face_recognizer') | |
| crop_vision_frame, matrix = warp_face_by_face_landmark_5(temp_vision_frame, face_landmark_5, 'arcface_112_v2', (112, 112)) | |
| crop_vision_frame = crop_vision_frame / 127.5 - 1 | |
| crop_vision_frame = crop_vision_frame[:, :, ::-1].transpose(2, 0, 1).astype(numpy.float32) | |
| crop_vision_frame = numpy.expand_dims(crop_vision_frame, axis = 0) | |
| with conditional_thread_semaphore(): | |
| embedding = face_recognizer.run(None, | |
| { | |
| 'input': crop_vision_frame | |
| })[0] | |
| embedding = embedding.ravel() | |
| normed_embedding = embedding / numpy.linalg.norm(embedding) | |
| return embedding, normed_embedding | |
| def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame: | |
| model_type = get_model_options().get('type') | |
| model_mean = get_model_options().get('mean') | |
| model_standard_deviation = get_model_options().get('standard_deviation') | |
| if model_type == 'ghost': | |
| crop_vision_frame = crop_vision_frame[:, :, ::-1] / 127.5 - 1 | |
| else: | |
| crop_vision_frame = crop_vision_frame[:, :, ::-1] / 255.0 | |
| crop_vision_frame = (crop_vision_frame - model_mean) / model_standard_deviation | |
| crop_vision_frame = crop_vision_frame.transpose(2, 0, 1) | |
| crop_vision_frame = numpy.expand_dims(crop_vision_frame, axis = 0).astype(numpy.float32) | |
| return crop_vision_frame | |
| def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame: | |
| model_template = get_model_options().get('type') | |
| crop_vision_frame = crop_vision_frame.transpose(1, 2, 0) | |
| if model_template == 'ghost': | |
| crop_vision_frame = (crop_vision_frame * 127.5 + 127.5).round() | |
| else: | |
| crop_vision_frame = (crop_vision_frame * 255.0).round() | |
| crop_vision_frame = crop_vision_frame[:, :, ::-1] | |
| return crop_vision_frame | |
| def get_reference_frame(source_face : Face, target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: | |
| return swap_face(source_face, target_face, temp_vision_frame) | |
| def process_frame(inputs : FaceSwapperInputs) -> VisionFrame: | |
| reference_faces = inputs.get('reference_faces') | |
| source_face = inputs.get('source_face') | |
| 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 = swap_face(source_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 = swap_face(source_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 = swap_face(source_face, similar_face, target_vision_frame) | |
| return target_vision_frame | |
| def process_frames(source_paths : 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 | |
| source_frames = read_static_images(source_paths) | |
| source_faces = get_many_faces(source_frames) | |
| source_face = get_average_face(source_faces) | |
| 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, | |
| 'source_face': source_face, | |
| 'target_vision_frame': target_vision_frame | |
| }) | |
| write_image(target_vision_path, output_vision_frame) | |
| update_progress(1) | |
| def process_image(source_paths : List[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 | |
| source_frames = read_static_images(source_paths) | |
| source_faces = get_many_faces(source_frames) | |
| source_face = get_average_face(source_faces) | |
| target_vision_frame = read_static_image(target_path) | |
| output_vision_frame = process_frame( | |
| { | |
| 'reference_faces': reference_faces, | |
| 'source_face': source_face, | |
| '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(source_paths, temp_frame_paths, process_frames) | |