Merge pull request #807 from facefusion/feat/deep-swapper

Feat/deep swapper
2024-11-05 22:14:23 +05:30 · 2024-11-05 22:14:23 +05:30 · fe44a253c1
commit fe44a253c1
parent 56777fb458 fb62ee246c
13 changed files with 329 additions and 8 deletions
--- a/facefusion.ini
+++ b/facefusion.ini
@ -53,6 +53,7 @@ skip_audio =
 processors =
 age_modifier_model =
 age_modifier_direction =
+deep_swapper_model =
 expression_restorer_model =
 expression_restorer_factor =
 face_debugger_items =
--- a/facefusion/processors/choices.py
+++ b/facefusion/processors/choices.py
@ -1,9 +1,10 @@
 from typing import List, Sequence

 from facefusion.common_helper import create_float_range, create_int_range
-from facefusion.processors.typing import AgeModifierModel, ExpressionRestorerModel, FaceDebuggerItem, FaceEditorModel, FaceEnhancerModel, FaceSwapperSet, FrameColorizerModel, FrameEnhancerModel, LipSyncerModel
+from facefusion.processors.typing import AgeModifierModel, DeepSwapperModel, ExpressionRestorerModel, FaceDebuggerItem, FaceEditorModel, FaceEnhancerModel, FaceSwapperSet, FrameColorizerModel, FrameEnhancerModel, LipSyncerModel

 age_modifier_models : List[AgeModifierModel] = [ 'styleganex_age' ]
+deep_swapper_models : List[DeepSwapperModel] = [ 'jackie_chan' ]
 expression_restorer_models : List[ExpressionRestorerModel] = [ 'live_portrait' ]
 face_debugger_items : List[FaceDebuggerItem] = [ 'bounding-box', 'face-landmark-5', 'face-landmark-5/68', 'face-landmark-68', 'face-landmark-68/5', 'face-mask', 'face-detector-score', 'face-landmarker-score', 'age', 'gender', 'race' ]
 face_editor_models : List[FaceEditorModel] = [ 'live_portrait' ]
--- a/facefusion/processors/modules/deep_swapper.py
+++ b/facefusion/processors/modules/deep_swapper.py
@ -0,0 +1,228 @@
+from argparse import ArgumentParser
+from typing import List, Tuple
+
+import cv2
+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.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, 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 DeepSwapperInputs
+from facefusion.program_helper import find_argument_group
+from facefusion.thread_helper import thread_semaphore
+from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, Mask, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.vision import conditional_match_frame_color, read_image, read_static_image, write_image
+
+MODEL_SET : ModelSet =\
+{
+	'jackie_chan':
+	{
+		'hashes':
+		{
+			'deep_swapper':
+			{
+				'url': 'https://huggingface.co/bluefoxcreation/DFM/resolve/main/Jackie_Chan.hash',
+				'path': resolve_relative_path('../.assets/models/Jackie_Chan.hash')
+			}
+		},
+		'sources':
+		{
+			'deep_swapper':
+			{
+				'url': 'https://github.com/iperov/DeepFaceLive/releases/download/JACKIE_CHAN/Jackie_Chan.dfm',
+				'path': resolve_relative_path('../.assets/models/Jackie_Chan.dfm')
+			}
+		},
+		'template': 'arcface_128_v2',
+		'size': (224, 224)
+	}
+}
+
+
+def get_inference_pool() -> InferencePool:
+	model_sources = get_model_options().get('sources')
+	model_context = __name__ + '.' + state_manager.get_item('deep_swapper_model')
+	return inference_manager.get_inference_pool(model_context, model_sources)
+
+
+def clear_inference_pool() -> None:
+	model_context = __name__ + '.' + state_manager.get_item('deep_swapper_model')
+	inference_manager.clear_inference_pool(model_context)
+
+
+def get_model_options() -> ModelOptions:
+	deep_swapper_model = state_manager.get_item('deep_swapper_model')
+	return MODEL_SET.get(deep_swapper_model)
+
+
+def register_args(program : ArgumentParser) -> None:
+	group_processors = find_argument_group(program, 'processors')
+	if group_processors:
+		group_processors.add_argument('--deep-swapper-model', help = wording.get('help.deep_swapper_model'), default = config.get_str_value('processors.deep_swapper_model', 'jackie_chan'), choices = processors_choices.deep_swapper_models)
+		facefusion.jobs.job_store.register_step_keys([ 'deep_swapper_model' ])
+
+
+def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
+	apply_state_item('deep_swapper_model', args.get('deep_swapper_model'))
+
+
+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__)
+		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__)
+		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__)
+		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 swap_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
+	model_template = get_model_options().get('template')
+	model_size = get_model_options().get('size')
+	crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, target_face.landmark_set.get('5/68'), model_template, model_size)
+	crop_vision_frame_raw = crop_vision_frame.copy()
+	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 =\
+	[
+		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, crop_source_mask, crop_target_mask = forward(crop_vision_frame)
+	crop_vision_frame = normalize_crop_frame(crop_vision_frame)
+	crop_vision_frame = conditional_match_frame_color(crop_vision_frame_raw, crop_vision_frame)
+	crop_masks.append(prepare_crop_mask(crop_source_mask, crop_target_mask))
+	crop_mask = numpy.minimum.reduce(crop_masks).clip(0, 1)
+	paste_vision_frame = paste_back(temp_vision_frame, crop_vision_frame, crop_mask, affine_matrix)
+	return paste_vision_frame
+
+
+def forward(crop_vision_frame : VisionFrame) -> Tuple[VisionFrame, Mask, Mask]:
+	deep_swapper = get_inference_pool().get('deep_swapper')
+	deep_swapper_inputs = {}
+
+	for deep_swapper_input in deep_swapper.get_inputs():
+		if deep_swapper_input.name == 'in_face:0':
+			deep_swapper_inputs[deep_swapper_input.name] = crop_vision_frame
+		if deep_swapper_input.name == 'morph_value:0':
+			morph_value = numpy.array([ 1 ]).astype(numpy.float32)
+			deep_swapper_inputs[deep_swapper_input.name] = morph_value
+
+	with thread_semaphore():
+		crop_target_mask, crop_vision_frame, crop_source_mask = deep_swapper.run(None, deep_swapper_inputs)
+
+	return crop_vision_frame[0], crop_source_mask[0], crop_target_mask[0]
+
+
+def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
+	crop_vision_frame = cv2.addWeighted(crop_vision_frame, 1.75, cv2.GaussianBlur(crop_vision_frame, (0, 0), 2), -0.75, 0)
+	crop_vision_frame = crop_vision_frame / 255.0
+	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:
+	crop_vision_frame = (crop_vision_frame * 255.0).clip(0, 255)
+	crop_vision_frame = crop_vision_frame.astype(numpy.uint8)
+	return crop_vision_frame
+
+
+def prepare_crop_mask(crop_source_mask : Mask, crop_target_mask : Mask) -> Mask:
+	model_size = get_model_options().get('size')
+	crop_mask = numpy.maximum.reduce([ crop_source_mask, crop_target_mask ])
+	crop_mask = crop_mask.reshape(model_size).clip(0, 1)
+	crop_mask = cv2.erode(crop_mask, numpy.ones((5, 5), numpy.uint8), iterations = 1)
+	crop_mask = cv2.GaussianBlur(crop_mask, (9, 9), 0)
+	return crop_mask
+
+
+def get_reference_frame(source_face : Face, target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
+	return swap_face(target_face, temp_vision_frame)
+
+
+def process_frame(inputs : DeepSwapperInputs) -> 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 = swap_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(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(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)
--- a/facefusion/processors/typing.py
+++ b/facefusion/processors/typing.py
@ -5,6 +5,7 @@ from numpy._typing import NDArray
 from facefusion.typing import AppContext, AudioFrame, Face, FaceSet, VisionFrame

 AgeModifierModel = Literal['styleganex_age']
+DeepSwapperModel = Literal['jackie_chan']
 ExpressionRestorerModel = Literal['live_portrait']
 FaceDebuggerItem = Literal['bounding-box', 'face-landmark-5', 'face-landmark-5/68', 'face-landmark-68', 'face-landmark-68/5', 'face-mask', 'face-detector-score', 'face-landmarker-score', 'age', 'gender', 'race']
 FaceEditorModel = Literal['live_portrait']
@ -21,6 +22,11 @@ AgeModifierInputs = TypedDict('AgeModifierInputs',
 	'reference_faces' : FaceSet,
 	'target_vision_frame' : VisionFrame
 })
+DeepSwapperInputs = TypedDict('DeepSwapperInputs',
+{
+	'reference_faces' : FaceSet,
+	'target_vision_frame' : VisionFrame
+})
 ExpressionRestorerInputs = TypedDict('ExpressionRestorerInputs',
 {
 	'reference_faces' : FaceSet,
@ -67,6 +73,7 @@ ProcessorStateKey = Literal\
 [
 	'age_modifier_model',
 	'age_modifier_direction',
+	'deep_swapper_model',
 	'expression_restorer_model',
 	'expression_restorer_factor',
 	'face_debugger_items',
@ -100,6 +107,7 @@ ProcessorState = TypedDict('ProcessorState',
 {
 	'age_modifier_model' : AgeModifierModel,
 	'age_modifier_direction' : int,
+	'deep_swapper_model' : DeepSwapperModel,
 	'expression_restorer_model' : ExpressionRestorerModel,
 	'expression_restorer_factor' : int,
 	'face_debugger_items' : List[FaceDebuggerItem],
--- a/facefusion/uis/components/deep_swapper_options.py
+++ b/facefusion/uis/components/deep_swapper_options.py
@ -0,0 +1,46 @@
+from typing import List, Optional
+
+import gradio
+
+from facefusion import state_manager, wording
+from facefusion.processors import choices as processors_choices
+from facefusion.processors.core import load_processor_module
+from facefusion.processors.typing import DeepSwapperModel
+from facefusion.uis.core import get_ui_component, register_ui_component
+
+DEEP_SWAPPER_MODEL_DROPDOWN : Optional[gradio.Dropdown] = None
+
+
+def render() -> None:
+	global DEEP_SWAPPER_MODEL_DROPDOWN
+
+	DEEP_SWAPPER_MODEL_DROPDOWN = gradio.Dropdown(
+		label = wording.get('uis.deep_swapper_model_dropdown'),
+		choices = processors_choices.deep_swapper_models,
+		value = state_manager.get_item('deep_swapper_model'),
+		visible = 'deep_swapper' in state_manager.get_item('processors')
+	)
+	register_ui_component('deep_swapper_model_dropdown', DEEP_SWAPPER_MODEL_DROPDOWN)
+
+
+def listen() -> None:
+	DEEP_SWAPPER_MODEL_DROPDOWN.change(update_deep_swapper_model, inputs = DEEP_SWAPPER_MODEL_DROPDOWN, outputs = DEEP_SWAPPER_MODEL_DROPDOWN)
+
+	processors_checkbox_group = get_ui_component('processors_checkbox_group')
+	if processors_checkbox_group:
+		processors_checkbox_group.change(remote_update, inputs = processors_checkbox_group, outputs = DEEP_SWAPPER_MODEL_DROPDOWN)
+
+
+def remote_update(processors : List[str]) -> gradio.Dropdown:
+	has_deep_swapper = 'deep_swapper' in processors
+	return gradio.Dropdown(visible = has_deep_swapper)
+
+
+def update_deep_swapper_model(deep_swapper_model : DeepSwapperModel) -> gradio.Dropdown:
+	deep_swapper_module = load_processor_module('deep_swapper')
+	deep_swapper_module.clear_inference_pool()
+	state_manager.set_item('deep_swapper_model', deep_swapper_model)
+
+	if deep_swapper_module.pre_check():
+		return gradio.Dropdown(value = state_manager.get_item('deep_swapper_model'))
+	return gradio.Dropdown()
--- a/facefusion/uis/components/preview.py
+++ b/facefusion/uis/components/preview.py
@ -142,6 +142,7 @@ def listen() -> None:
 	for ui_component in get_ui_components(
 	[
 		'age_modifier_model_dropdown',
+		'deep_swapper_model_dropdown',
 		'expression_restorer_model_dropdown',
 		'processors_checkbox_group',
 		'face_editor_model_dropdown',
--- a/facefusion/uis/layouts/benchmark.py
+++ b/facefusion/uis/layouts/benchmark.py
@ -2,7 +2,7 @@ import gradio

 from facefusion import state_manager
 from facefusion.download import conditional_download
-from facefusion.uis.components import about, age_modifier_options, benchmark, benchmark_options, execution, execution_queue_count, execution_thread_count, expression_restorer_options, face_debugger_options, face_editor_options, face_enhancer_options, face_swapper_options, frame_colorizer_options, frame_enhancer_options, lip_syncer_options, memory, processors
+from facefusion.uis.components import about, age_modifier_options, benchmark, benchmark_options, deep_swapper_options, execution, execution_queue_count, execution_thread_count, expression_restorer_options, face_debugger_options, face_editor_options, face_enhancer_options, face_swapper_options, frame_colorizer_options, frame_enhancer_options, lip_syncer_options, memory, processors


 def pre_check() -> bool:
@ -33,6 +33,8 @@ def render() -> gradio.Blocks:
 					processors.render()
 				with gradio.Blocks():
 					age_modifier_options.render()
+				with gradio.Blocks():
+					deep_swapper_options.render()
 				with gradio.Blocks():
 					expression_restorer_options.render()
 				with gradio.Blocks():
@ -66,6 +68,7 @@ def render() -> gradio.Blocks:
 def listen() -> None:
 	processors.listen()
 	age_modifier_options.listen()
+	deep_swapper_options.listen()
 	expression_restorer_options.listen()
 	face_debugger_options.listen()
 	face_editor_options.listen()
--- a/facefusion/uis/layouts/default.py
+++ b/facefusion/uis/layouts/default.py
@ -1,7 +1,7 @@
 import gradio

 from facefusion import state_manager
-from facefusion.uis.components import about, age_modifier_options, common_options, execution, execution_queue_count, execution_thread_count, expression_restorer_options, face_debugger_options, face_detector, face_editor_options, face_enhancer_options, face_landmarker, face_masker, face_selector, face_swapper_options, frame_colorizer_options, frame_enhancer_options, instant_runner, job_manager, job_runner, lip_syncer_options, memory, output, output_options, preview, processors, source, target, temp_frame, terminal, trim_frame, ui_workflow
+from facefusion.uis.components import about, age_modifier_options, common_options, deep_swapper_options, execution, execution_queue_count, execution_thread_count, expression_restorer_options, face_debugger_options, face_detector, face_editor_options, face_enhancer_options, face_landmarker, face_masker, face_selector, face_swapper_options, frame_colorizer_options, frame_enhancer_options, instant_runner, job_manager, job_runner, lip_syncer_options, memory, output, output_options, preview, processors, source, target, temp_frame, terminal, trim_frame, ui_workflow


 def pre_check() -> bool:
@ -18,6 +18,8 @@ def render() -> gradio.Blocks:
 					processors.render()
 				with gradio.Blocks():
 					age_modifier_options.render()
+				with gradio.Blocks():
+					deep_swapper_options.render()
 				with gradio.Blocks():
 					expression_restorer_options.render()
 				with gradio.Blocks():
@ -79,6 +81,7 @@ def render() -> gradio.Blocks:
 def listen() -> None:
 	processors.listen()
 	age_modifier_options.listen()
+	deep_swapper_options.listen()
 	expression_restorer_options.listen()
 	face_debugger_options.listen()
 	face_editor_options.listen()
--- a/facefusion/uis/layouts/webcam.py
+++ b/facefusion/uis/layouts/webcam.py
@ -1,7 +1,7 @@
 import gradio

 from facefusion import state_manager
-from facefusion.uis.components import about, age_modifier_options, execution, execution_thread_count, expression_restorer_options, face_debugger_options, face_editor_options, face_enhancer_options, face_swapper_options, frame_colorizer_options, frame_enhancer_options, lip_syncer_options, processors, source, webcam, webcam_options
+from facefusion.uis.components import about, age_modifier_options, deep_swapper_options, execution, execution_thread_count, expression_restorer_options, face_debugger_options, face_editor_options, face_enhancer_options, face_swapper_options, frame_colorizer_options, frame_enhancer_options, lip_syncer_options, processors, source, webcam, webcam_options


 def pre_check() -> bool:
@ -18,6 +18,8 @@ def render() -> gradio.Blocks:
 					processors.render()
 				with gradio.Blocks():
 					age_modifier_options.render()
+				with gradio.Blocks():
+					deep_swapper_options.render()
 				with gradio.Blocks():
 					expression_restorer_options.render()
 				with gradio.Blocks():
@ -50,6 +52,7 @@ def render() -> gradio.Blocks:
 def listen() -> None:
 	processors.listen()
 	age_modifier_options.listen()
+	deep_swapper_options.listen()
 	expression_restorer_options.listen()
 	face_debugger_options.listen()
 	face_editor_options.listen()
--- a/facefusion/uis/typing.py
+++ b/facefusion/uis/typing.py
@ -9,6 +9,7 @@ ComponentName = Literal\
 	'age_modifier_model_dropdown',
 	'benchmark_cycles_slider',
 	'benchmark_runs_checkbox_group',
+	'deep_swapper_model_dropdown',
 	'expression_restorer_factor_slider',
 	'expression_restorer_model_dropdown',
 	'face_debugger_items_checkbox_group',
--- a/facefusion/vision.py
+++ b/facefusion/vision.py
@ -210,6 +210,12 @@ def normalize_frame_color(vision_frame : VisionFrame) -> VisionFrame:
 	return cv2.cvtColor(vision_frame, cv2.COLOR_BGR2RGB)


+def conditional_match_frame_color(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame) -> VisionFrame:
+	histogram_factor = calc_histogram_difference(source_vision_frame, target_vision_frame)
+	target_vision_frame = blend_vision_frames(target_vision_frame, match_frame_color(source_vision_frame, target_vision_frame), histogram_factor)
+	return target_vision_frame
+
+
 def match_frame_color(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame) -> VisionFrame:
 	color_difference_sizes = numpy.linspace(16, target_vision_frame.shape[0], 3, endpoint = False)

@ -228,6 +234,18 @@ def equalize_frame_color(source_vision_frame : VisionFrame, target_vision_frame
 	return target_vision_frame


+def calc_histogram_difference(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame) -> float:
+	histogram_source = cv2.calcHist([cv2.cvtColor(source_vision_frame, cv2.COLOR_BGR2HSV)], [ 0, 1 ], None, [ 50, 60 ], [ 0, 180, 0, 256 ])
+	histogram_target = cv2.calcHist([cv2.cvtColor(target_vision_frame, cv2.COLOR_BGR2HSV)], [ 0, 1 ], None, [ 50, 60 ], [ 0, 180, 0, 256 ])
+	histogram_differnce = float(numpy.interp(cv2.compareHist(histogram_source, histogram_target, cv2.HISTCMP_CORREL), [ -1, 1 ], [ 0, 1 ]))
+	return histogram_differnce
+
+
+def blend_vision_frames(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame, blend_factor : float) -> VisionFrame:
+	blend_vision_frame = cv2.addWeighted(source_vision_frame, 1 - blend_factor, target_vision_frame, blend_factor, 0)
+	return blend_vision_frame
+
+
 def create_tile_frames(vision_frame : VisionFrame, size : Size) -> Tuple[List[VisionFrame], int, int]:
 	vision_frame = numpy.pad(vision_frame, ((size[1], size[1]), (size[1], size[1]), (0, 0)))
 	tile_width = size[0] - 2 * size[2]
--- a/facefusion/wording.py
+++ b/facefusion/wording.py
@ -143,6 +143,7 @@ WORDING : Dict[str, Any] =\
 		'processors': 'load a single or multiple processors (choices: {choices}, ...)',
 		'age_modifier_model': 'choose the model responsible for aging the face',
 		'age_modifier_direction': 'specify the direction in which the age should be modified',
+		'deep_swapper_model': 'choose the model responsible for swapping the face',
 		'expression_restorer_model': 'choose the model responsible for restoring the expression',
 		'expression_restorer_factor': 'restore factor of expression from the target face',
 		'face_debugger_items': 'load a single or multiple processors (choices: {choices})',
@ -226,6 +227,7 @@ WORDING : Dict[str, Any] =\
 		'benchmark_runs_checkbox_group': 'BENCHMARK RUNS',
 		'clear_button': 'CLEAR',
 		'common_options_checkbox_group': 'OPTIONS',
+		'deep_swapper_model_dropdown': 'DEEP SWAPPER MODEL',
 		'execution_providers_checkbox_group': 'EXECUTION PROVIDERS',
 		'execution_queue_count_slider': 'EXECUTION QUEUE COUNT',
 		'execution_thread_count_slider': 'EXECUTION THREAD COUNT',
--- a/tests/test_vision.py
+++ b/tests/test_vision.py
@ -4,7 +4,7 @@ import cv2
 import pytest

 from facefusion.download import conditional_download
-from facefusion.vision import count_video_frame_total, create_image_resolutions, create_video_resolutions, detect_image_resolution, detect_video_duration, detect_video_fps, detect_video_resolution, get_video_frame, match_frame_color, normalize_resolution, pack_resolution, read_image, restrict_image_resolution, restrict_video_fps, restrict_video_resolution, unpack_resolution
+from facefusion.vision import calc_histogram_difference, count_video_frame_total, create_image_resolutions, create_video_resolutions, detect_image_resolution, detect_video_duration, detect_video_fps, detect_video_resolution, get_video_frame, match_frame_color, normalize_resolution, pack_resolution, read_image, restrict_image_resolution, restrict_video_fps, restrict_video_resolution, unpack_resolution
 from .helper import get_test_example_file, get_test_examples_directory


@ -117,11 +117,17 @@ def test_unpack_resolution() -> None:
 	assert unpack_resolution('2x2') == (2, 2)


+def test_calc_histogram_difference() -> None:
+	source_vision_frame = read_image(get_test_example_file('target-1080p.jpg'))
+	target_vision_frame = cv2.cvtColor(cv2.cvtColor(source_vision_frame, cv2.COLOR_BGR2GRAY), cv2.COLOR_GRAY2BGR)
+
+	assert calc_histogram_difference(source_vision_frame, source_vision_frame) == 1.0
+	assert calc_histogram_difference(source_vision_frame, target_vision_frame) < 0.5
+
+
 def test_match_frame_color() -> None:
 	source_vision_frame = read_image(get_test_example_file('target-1080p.jpg'))
 	target_vision_frame = cv2.cvtColor(cv2.cvtColor(source_vision_frame, cv2.COLOR_BGR2GRAY), cv2.COLOR_GRAY2BGR)
 	output_vision_frame = match_frame_color(source_vision_frame, target_vision_frame)
-	histogram_source = cv2.calcHist([ cv2.cvtColor(source_vision_frame, cv2.COLOR_BGR2HSV) ], [ 0, 1 ], None, [ 50, 60 ], [ 0, 180, 0, 256 ])
-	histogram_output = cv2.calcHist([ cv2.cvtColor(output_vision_frame, cv2.COLOR_BGR2HSV) ], [ 0, 1 ], None, [ 50, 60 ], [ 0, 180, 0, 256 ])

-	assert cv2.compareHist(histogram_source, histogram_output, cv2.HISTCMP_CORREL) > 0.5
+	assert calc_histogram_difference(source_vision_frame, output_vision_frame) > 0.5