Patch 3.6.1 (#1078)

* Avast intercepts ssl cert and breaks curl

* modernize dependencies

* fix sanitizer for int range

* comment out tests

* disable testing for CI

* disable testing for CI

LICENSE.md

@@ -1,3 +1,3 @@
 OpenRAIL-AS license
 
-Copyright (c) 2025 Henry Ruhs
+Copyright (c) 2026 Henry Ruhs

facefusion.ini

@@ -67,7 +67,8 @@ processors =
 age_modifier_model =
 age_modifier_direction =
 background_remover_model =
-background_remover_color =
+background_remover_fill_color =
+background_remover_despill_color =
 deep_swapper_model =
 deep_swapper_morph =
 expression_restorer_model =

facefusion.py

@@ -4,7 +4,8 @@ import os
 
 os.environ['OMP_NUM_THREADS'] = '1'
 
-from facefusion import core
+from facefusion import conda, core
 
 if __name__ == '__main__':
+	conda.setup()
 	core.cli()

facefusion/conda.py

@@ -0,0 +1,41 @@
+import os
+import sys
+from typing import List
+
+from facefusion.common_helper import is_linux, is_windows
+
+
+def setup() -> None:
+	conda_prefix = os.getenv('CONDA_PREFIX')
+	conda_ready = os.getenv('CONDA_READY')
+
+	if conda_prefix and not conda_ready:
+		if is_linux():
+			python_id = 'python' + str(sys.version_info.major) + '.' + str(sys.version_info.minor)
+			library_paths : List[str] =\
+			[
+				os.path.join(conda_prefix, 'lib'),
+				os.path.join(conda_prefix, 'lib', python_id, 'site-packages', 'tensorrt_libs')
+			]
+			library_paths = list(filter(os.path.exists, library_paths))
+
+			if library_paths:
+				if os.getenv('LD_LIBRARY_PATH'):
+					library_paths.append(os.getenv('LD_LIBRARY_PATH'))
+				os.environ['LD_LIBRARY_PATH'] = os.pathsep.join(library_paths)
+				os.environ['CONDA_READY'] = '1'
+				os.execv(sys.executable, [ sys.executable ] + sys.argv)
+
+		if is_windows():
+			library_paths =\
+			[
+				os.path.join(conda_prefix, 'Lib'),
+				os.path.join(conda_prefix, 'Lib', 'site-packages', 'tensorrt_libs')
+			]
+			library_paths = list(filter(os.path.exists, library_paths))
+
+			if library_paths:
+				if os.getenv('PATH'):
+					library_paths.append(os.getenv('PATH'))
+				os.environ['PATH'] = os.pathsep.join(library_paths)
+				os.environ['CONDA_READY'] = '1'

facefusion/curl_builder.py

@@ -9,7 +9,7 @@ from facefusion.types import Command
 def run(commands : List[Command]) -> List[Command]:
 	user_agent = metadata.get('name') + '/' + metadata.get('version')
 
-	return [ shutil.which('curl'), '--user-agent', user_agent, '--location', '--silent' ] + commands
+	return [ shutil.which('curl'), '--user-agent', user_agent, '--location', '--silent', '--ssl-no-revoke' ] + commands
 
 
 def chain(*commands : List[Command]) -> List[Command]:

facefusion/face_classifier.py

@@ -20,7 +20,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 			'__metadata__':
 			{
 				'vendor': 'dchen236',
-				'license': 'Non-Commercial',
+				'license': 'CC-BY-4.0',
 				'year': 2021
 			},
 			'hashes':

facefusion/installer.py

@@ -19,14 +19,14 @@ LOCALES =\
 }
 ONNXRUNTIME_SET =\
 {
-	'default': ('onnxruntime', '1.24.1')
+	'default': ('onnxruntime', '1.24.4')
 }
 if is_windows() or is_linux():
-	ONNXRUNTIME_SET['cuda'] = ('onnxruntime-gpu', '1.24.3')
+	ONNXRUNTIME_SET['cuda'] = ('onnxruntime-gpu', '1.24.4')
 	ONNXRUNTIME_SET['openvino'] = ('onnxruntime-openvino', '1.24.1')
 if is_windows():
-	ONNXRUNTIME_SET['directml'] = ('onnxruntime-directml', '1.24.3')
+	ONNXRUNTIME_SET['directml'] = ('onnxruntime-directml', '1.24.4')
-	ONNXRUNTIME_SET['qnn'] = ('onnxruntime-qnn', '1.24.3')
+	ONNXRUNTIME_SET['qnn'] = ('onnxruntime-qnn', '1.24.4')
 if is_linux():
 	ONNXRUNTIME_SET['migraphx'] = ('onnxruntime-migraphx', '1.24.2')
 	ONNXRUNTIME_SET['rocm'] = ('onnxruntime-rocm', '1.22.2.post1')
@@ -72,35 +72,3 @@ def run(program : ArgumentParser) -> None:
 	subprocess.call([ shutil.which('pip'), 'uninstall', 'onnxruntime', onnxruntime_name, '-y', '-q' ])
 
 	subprocess.call(commands)
-
-	if args.onnxruntime == 'cuda' and has_conda:
-		library_paths = []
-
-		if is_linux():
-			python_id = 'python' + str(sys.version_info.major) + '.' + str(sys.version_info.minor)
-			library_paths.extend(
-			[
-				os.path.join(os.getenv('CONDA_PREFIX'), 'lib'),
-				os.path.join(os.getenv('CONDA_PREFIX'), 'lib', python_id, 'site-packages', 'tensorrt_libs')
-			])
-
-			if os.getenv('LD_LIBRARY_PATH'):
-				library_paths.extend(os.getenv('LD_LIBRARY_PATH').split(os.pathsep))
-
-			library_paths = list(dict.fromkeys(filter(os.path.exists, library_paths)))
-
-			subprocess.call([ shutil.which('conda'), 'env', 'config', 'vars', 'set', 'LD_LIBRARY_PATH=' + os.pathsep.join(library_paths) ])
-
-		if is_windows():
-			library_paths.extend(
-			[
-				os.path.join(os.getenv('CONDA_PREFIX'), 'Lib'),
-				os.path.join(os.getenv('CONDA_PREFIX'), 'Lib', 'site-packages', 'tensorrt_libs')
-			])
-
-			if os.getenv('PATH'):
-				library_paths.extend(os.getenv('PATH').split(os.pathsep))
-
-			library_paths = list(dict.fromkeys(filter(os.path.exists, library_paths)))
-
-			subprocess.call([ shutil.which('conda'), 'env', 'config', 'vars', 'set', 'PATH=' + os.pathsep.join(library_paths) ])

facefusion/metadata.py

@@ -4,7 +4,7 @@ METADATA =\
 {
 	'name': 'FaceFusion',
 	'description': 'Industry leading face manipulation platform',
-	'version': '3.5.4',
+	'version': '3.6.1',
 	'license': 'OpenRAIL-AS',
 	'author': 'Henry Ruhs',
 	'url': 'https://facefusion.io'

facefusion/processors/modules/age_modifier/core.py

@@ -29,6 +29,41 @@ from facefusion.vision import match_frame_color, read_static_image, read_static_
 def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
+		'fran':
+		{
+			'__metadata__':
+			{
+				'vendor': 'ry-lu',
+				'license': 'mit',
+				'year': 2024
+			},
+			'hashes':
+			{
+				'age_modifier':
+				{
+					'url': resolve_download_url('models-3.6.0', 'fran.hash'),
+					'path': resolve_relative_path('../.assets/models/fran.hash')
+				}
+			},
+			'sources':
+			{
+				'age_modifier':
+				{
+					'url': resolve_download_url('models-3.6.0', 'fran.onnx'),
+					'path': resolve_relative_path('../.assets/models/fran.onnx')
+				}
+			},
+			'templates':
+			{
+				'target': 'ffhq_512',
+			},
+			'sizes':
+			{
+				'target': (1024, 1024),
+			},
+			'mean': [ 0.0, 0.0, 0.0 ],
+			'standard_deviation': [ 1.0, 1.0, 1.0 ]
+		},
 		'styleganex_age':
 		{
 			'__metadata__':
@@ -62,7 +97,9 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 			{
 				'target': (256, 256),
 				'target_with_background': (384, 384)
-			}
+			},
+			'mean': [ 0.5, 0.5, 0.5 ],
+			'standard_deviation': [ 0.5, 0.5, 0.5 ]
 		}
 	}
 
@@ -87,7 +124,7 @@ def get_model_options() -> ModelOptions:
 def register_args(program : ArgumentParser) -> None:
 	group_processors = find_argument_group(program, 'processors')
 	if group_processors:
-		group_processors.add_argument('--age-modifier-model', help = translator.get('help.model', __package__), default = config.get_str_value('processors', 'age_modifier_model', 'styleganex_age'), choices = age_modifier_choices.age_modifier_models)
+		group_processors.add_argument('--age-modifier-model', help = translator.get('help.model', __package__), default = config.get_str_value('processors', 'age_modifier_model', 'fran'), choices = age_modifier_choices.age_modifier_models)
 		group_processors.add_argument('--age-modifier-direction', help = translator.get('help.direction', __package__), type = int, default = config.get_int_value('processors', 'age_modifier_direction', '0'), choices = age_modifier_choices.age_modifier_direction_range, metavar = create_int_metavar(age_modifier_choices.age_modifier_direction_range))
 		facefusion.jobs.job_store.register_step_keys([ 'age_modifier_model', 'age_modifier_direction' ])
 
@@ -137,32 +174,57 @@ def modify_age(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFra
 	model_sizes = get_model_options().get('sizes')
 	face_landmark_5 = target_face.landmark_set.get('5/68').copy()
 	crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, face_landmark_5, model_templates.get('target'), model_sizes.get('target'))
-	extend_face_landmark_5 = scale_face_landmark_5(face_landmark_5, 0.875)
-	extend_vision_frame, extend_affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, extend_face_landmark_5, model_templates.get('target_with_background'), model_sizes.get('target_with_background'))
-	extend_vision_frame_raw = extend_vision_frame.copy()
-	box_mask = create_box_mask(extend_vision_frame, 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'):
+	if state_manager.get_item('age_modifier_model') == 'fran':
-		occlusion_mask = create_occlusion_mask(crop_vision_frame)
+		box_mask = create_box_mask(crop_vision_frame, state_manager.get_item('face_mask_blur'), (0, 0, 0, 0))
-		temp_matrix = merge_matrix([ extend_affine_matrix, cv2.invertAffineTransform(affine_matrix) ])
+		crop_masks =\
-		occlusion_mask = cv2.warpAffine(occlusion_mask, temp_matrix, model_sizes.get('target_with_background'))
+		[
-		crop_masks.append(occlusion_mask)
+			box_mask
+		]
 
-	crop_vision_frame = prepare_vision_frame(crop_vision_frame)
+		if 'occlusion' in state_manager.get_item('face_mask_types'):
-	extend_vision_frame = prepare_vision_frame(extend_vision_frame)
+			occlusion_mask = create_occlusion_mask(crop_vision_frame)
-	age_modifier_direction = numpy.array(numpy.interp(state_manager.get_item('age_modifier_direction'), [ -100, 100 ], [ 2.5, -2.5 ])).astype(numpy.float32)
+			crop_masks.append(occlusion_mask)
-	extend_vision_frame = forward(crop_vision_frame, extend_vision_frame, age_modifier_direction)
+
-	extend_vision_frame = normalize_extend_frame(extend_vision_frame)
+		crop_vision_frame = prepare_vision_frame(crop_vision_frame)
-	extend_vision_frame = match_frame_color(extend_vision_frame_raw, extend_vision_frame)
+		target_age = numpy.mean(target_face.age)
-	extend_affine_matrix *= (model_sizes.get('target')[0] * 4) / model_sizes.get('target_with_background')[0]
+		age_modifier_direction = numpy.array([ target_age, target_age + state_manager.get_item('age_modifier_direction') ], dtype = numpy.float32) / 100
-	crop_mask = numpy.minimum.reduce(crop_masks).clip(0, 1)
+		age_modifier_direction = age_modifier_direction.clip(0, 1)
-	crop_mask = cv2.resize(crop_mask, (model_sizes.get('target')[0] * 4, model_sizes.get('target')[1] * 4))
+		crop_vision_frame = forward(crop_vision_frame, crop_vision_frame, age_modifier_direction)
-	paste_vision_frame = paste_back(temp_vision_frame, extend_vision_frame, crop_mask, extend_affine_matrix)
+		crop_vision_frame = normalize_vision_frame(crop_vision_frame)
-	return paste_vision_frame
+		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
+
+	if state_manager.get_item('age_modifier_model') == 'styleganex_age':
+		extend_face_landmark_5 = scale_face_landmark_5(face_landmark_5, 0.875)
+		extend_vision_frame, extend_affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, extend_face_landmark_5, model_templates.get('target_with_background'), model_sizes.get('target_with_background'))
+		extend_vision_frame_raw = extend_vision_frame.copy()
+		box_mask = create_box_mask(extend_vision_frame, 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)
+			temp_matrix = merge_matrix([ extend_affine_matrix, cv2.invertAffineTransform(affine_matrix) ])
+			occlusion_mask = cv2.warpAffine(occlusion_mask, temp_matrix, model_sizes.get('target_with_background'))
+			crop_masks.append(occlusion_mask)
+
+		crop_vision_frame = prepare_vision_frame(crop_vision_frame)
+		extend_vision_frame = prepare_vision_frame(extend_vision_frame)
+		age_modifier_direction = numpy.array(numpy.interp(state_manager.get_item('age_modifier_direction'), [ -100, 100 ], [ 2.5, -2.5 ])).astype(numpy.float32)
+		extend_vision_frame = forward(crop_vision_frame, extend_vision_frame, age_modifier_direction)
+		extend_vision_frame = normalize_extend_frame(extend_vision_frame)
+		extend_vision_frame = match_frame_color(extend_vision_frame_raw, extend_vision_frame)
+		extend_affine_matrix *= (model_sizes.get('target')[0] * 4) / model_sizes.get('target_with_background')[0]
+		crop_mask = numpy.minimum.reduce(crop_masks).clip(0, 1)
+		crop_mask = cv2.resize(crop_mask, (model_sizes.get('target')[0] * 4, model_sizes.get('target')[1] * 4))
+		paste_vision_frame = paste_back(temp_vision_frame, extend_vision_frame, crop_mask, extend_affine_matrix)
+		return paste_vision_frame
+
+	return temp_vision_frame
 
 
 def forward(crop_vision_frame : VisionFrame, extend_vision_frame : VisionFrame, age_modifier_direction : AgeModifierDirection) -> VisionFrame:
@@ -187,12 +249,24 @@ def forward(crop_vision_frame : VisionFrame, extend_vision_frame : VisionFrame,
 
 
 def prepare_vision_frame(vision_frame : VisionFrame) -> VisionFrame:
+	model_mean = get_model_options().get('mean')
+	model_standard_deviation = get_model_options().get('standard_deviation')
 	vision_frame = vision_frame[:, :, ::-1] / 255.0
-	vision_frame = (vision_frame - 0.5) / 0.5
+	vision_frame = (vision_frame - model_mean) / model_standard_deviation
 	vision_frame = numpy.expand_dims(vision_frame.transpose(2, 0, 1), axis = 0).astype(numpy.float32)
 	return vision_frame
 
 
+def normalize_vision_frame(vision_frame : VisionFrame) -> VisionFrame:
+	model_mean = get_model_options().get('mean')
+	model_standard_deviation = get_model_options().get('standard_deviation')
+	vision_frame = vision_frame.transpose(1, 2, 0)
+	vision_frame = vision_frame * model_standard_deviation + model_mean
+	vision_frame = vision_frame.clip(0, 1)
+	vision_frame = vision_frame[:, :, ::-1] * 255
+	return vision_frame
+
+
 def normalize_extend_frame(extend_vision_frame : VisionFrame) -> VisionFrame:
 	model_sizes = get_model_options().get('sizes')
 	extend_vision_frame = numpy.clip(extend_vision_frame, -1, 1)

facefusion/processors/modules/age_modifier/types.py

@@ -12,6 +12,6 @@ AgeModifierInputs = TypedDict('AgeModifierInputs',
 	'temp_vision_mask' : Mask
 })
 
-AgeModifierModel = Literal['styleganex_age']
+AgeModifierModel = Literal['fran', 'styleganex_age']
 
 AgeModifierDirection : TypeAlias = NDArray[Any]

facefusion/processors/modules/background_remover/core.py

@@ -8,7 +8,7 @@ import numpy
 import facefusion.jobs.job_manager
 import facefusion.jobs.job_store
 from facefusion import config, content_analyser, inference_manager, logger, state_manager, translator, video_manager
-from facefusion.common_helper import is_macos
+from facefusion.common_helper import is_macos, is_windows
 from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.execution import has_execution_provider
 from facefusion.filesystem import in_directory, is_image, is_video, resolve_relative_path, same_file_extension
@@ -51,6 +51,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/ben_2.onnx')
 				}
 			},
+			'type': 'ben',
 			'size': (1024, 1024),
 			'mean': [ 0.0, 0.0, 0.0 ],
 			'standard_deviation': [ 1.0, 1.0, 1.0 ]
@@ -79,6 +80,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/birefnet_general.onnx')
 				}
 			},
+			'type': 'birefnet',
 			'size': (1024, 1024),
 			'mean': [ 0.0, 0.0, 0.0 ],
 			'standard_deviation': [ 1.0, 1.0, 1.0 ]
@@ -107,10 +109,69 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/birefnet_portrait.onnx')
 				}
 			},
+			'type': 'birefnet',
 			'size': (1024, 1024),
 			'mean': [ 0.0, 0.0, 0.0 ],
 			'standard_deviation': [ 1.0, 1.0, 1.0 ]
 		},
+		'corridor_key_1024':
+		{
+			'__metadata__':
+			{
+				'vendor': 'nikopueringer',
+				'license': 'Non-Commercial',
+				'year': 2025
+			},
+			'hashes':
+			{
+				'background_remover':
+				{
+					'url': resolve_download_url('models-3.6.0', 'corridor_key_1024.hash'),
+					'path': resolve_relative_path('../.assets/models/corridor_key_1024.hash')
+				}
+			},
+			'sources':
+			{
+				'background_remover':
+				{
+					'url': resolve_download_url('models-3.6.0', 'corridor_key_1024.onnx'),
+					'path': resolve_relative_path('../.assets/models/corridor_key_1024.onnx')
+				}
+			},
+			'type': 'corridor_key',
+			'size': (1024, 1024),
+			'mean': [ 0.485, 0.456, 0.406 ],
+			'standard_deviation': [ 0.229, 0.224, 0.225 ]
+		},
+		'corridor_key_2048':
+		{
+			'__metadata__':
+			{
+				'vendor': 'nikopueringer',
+				'license': 'Non-Commercial',
+				'year': 2025
+			},
+			'hashes':
+			{
+				'background_remover':
+				{
+					'url': resolve_download_url('models-3.6.0', 'corridor_key_2048.hash'),
+					'path': resolve_relative_path('../.assets/models/corridor_key_2048.hash')
+				}
+			},
+			'sources':
+			{
+				'background_remover':
+				{
+					'url': resolve_download_url('models-3.6.0', 'corridor_key_2048.onnx'),
+					'path': resolve_relative_path('../.assets/models/corridor_key_2048.onnx')
+				}
+			},
+			'type': 'corridor_key',
+			'size': (2048, 2048),
+			'mean': [ 0.485, 0.456, 0.406 ],
+			'standard_deviation': [ 0.229, 0.224, 0.225 ]
+		},
 		'isnet_general':
 		{
 			'__metadata__':
@@ -135,6 +196,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/isnet_general.onnx')
 				}
 			},
+			'type': 'isnet',
 			'size': (1024, 1024),
 			'mean': [ 0.5, 0.5, 0.5 ],
 			'standard_deviation': [ 1.0, 1.0, 1.0 ]
@@ -163,6 +225,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/modnet.onnx')
 				}
 			},
+			'type': 'modnet',
 			'size': (512, 512),
 			'mean': [ 0.5, 0.5, 0.5 ],
 			'standard_deviation': [ 0.5, 0.5, 0.5 ]
@@ -191,6 +254,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/ormbg.onnx')
 				}
 			},
+			'type': 'ormbg',
 			'size': (1024, 1024),
 			'mean': [ 0.0, 0.0, 0.0 ],
 			'standard_deviation': [ 1.0, 1.0, 1.0 ]
@@ -219,6 +283,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/rmbg_1.4.onnx')
 				}
 			},
+			'type': 'rmbg',
 			'size': (1024, 1024),
 			'mean': [ 0.5, 0.5, 0.5 ],
 			'standard_deviation': [ 1.0, 1.0, 1.0 ]
@@ -247,6 +312,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/rmbg_2.0.onnx')
 				}
 			},
+			'type': 'rmbg',
 			'size': (1024, 1024),
 			'mean': [ 0.485, 0.456, 0.406 ],
 			'standard_deviation': [ 0.229, 0.224, 0.225 ]
@@ -275,6 +341,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/silueta.onnx')
 				}
 			},
+			'type': 'silueta',
 			'size': (320, 320),
 			'mean': [ 0.485, 0.456, 0.406 ],
 			'standard_deviation': [ 0.229, 0.224, 0.225 ]
@@ -303,6 +370,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/u2net_cloth.onnx')
 				}
 			},
+			'type': 'u2net_cloth',
 			'size': (768, 768),
 			'mean': [ 0.485, 0.456, 0.406 ],
 			'standard_deviation': [ 0.229, 0.224, 0.225 ]
@@ -331,6 +399,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/u2net_general.onnx')
 				}
 			},
+			'type': 'u2net',
 			'size': (320, 320),
 			'mean': [ 0.485, 0.456, 0.406 ],
 			'standard_deviation': [ 0.229, 0.224, 0.225 ]
@@ -359,6 +428,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/u2net_human.onnx')
 				}
 			},
+			'type': 'u2net',
 			'size': (320, 320),
 			'mean': [ 0.485, 0.456, 0.406 ],
 			'standard_deviation': [ 0.229, 0.224, 0.225 ]
@@ -387,6 +457,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 					'path': resolve_relative_path('../.assets/models/u2netp.onnx')
 				}
 			},
+			'type': 'u2netp',
 			'size': (320, 320),
 			'mean': [ 0.485, 0.456, 0.406 ],
 			'standard_deviation': [ 0.229, 0.224, 0.225 ]
@@ -407,7 +478,9 @@ def clear_inference_pool() -> None:
 
 
 def resolve_execution_providers() -> List[ExecutionProvider]:
-	if is_macos() and has_execution_provider('coreml'):
+	model_type = get_model_options().get('type')
+
+	if is_macos() and has_execution_provider('coreml') or is_windows() and has_execution_provider('directml') and model_type == 'corridor_key':
 		return [ 'cpu' ]
 	return state_manager.get_item('execution_providers')
 
@@ -420,14 +493,16 @@ def get_model_options() -> ModelOptions:
 def register_args(program : ArgumentParser) -> None:
 	group_processors = find_argument_group(program, 'processors')
 	if group_processors:
-		group_processors.add_argument('--background-remover-model', help = translator.get('help.model', __package__), default = config.get_str_value('processors', 'background_remover_model', 'rmbg_2.0'), choices = background_remover_choices.background_remover_models)
+		group_processors.add_argument('--background-remover-model', help = translator.get('help.model', __package__), default = config.get_str_value('processors', 'background_remover_model', 'modnet'), choices = background_remover_choices.background_remover_models)
-		group_processors.add_argument('--background-remover-color', help = translator.get('help.color', __package__), type = partial(sanitize_int_range, int_range = background_remover_choices.background_remover_color_range), default = config.get_int_list('processors', 'background_remover_color', '0 0 0 0'), nargs = '+')
+		group_processors.add_argument('--background-remover-fill-color', help = translator.get('help.fill_color', __package__), type = partial(sanitize_int_range, int_range = background_remover_choices.background_remover_color_range), default = config.get_int_list('processors', 'background_remover_fill_color', '0 0 0 0'), nargs = '+')
-		facefusion.jobs.job_store.register_step_keys([ 'background_remover_model', 'background_remover_color' ])
+		group_processors.add_argument('--background-remover-despill-color', help = translator.get('help.despill_color', __package__), type = partial(sanitize_int_range, int_range = background_remover_choices.background_remover_color_range), default = config.get_int_list('processors', 'background_remover_despill_color', '0 0 0 0'), nargs = '+')
+		facefusion.jobs.job_store.register_step_keys([ 'background_remover_model', 'background_remover_fill_color', 'background_remover_despill_color' ])
 
 
 def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('background_remover_model', args.get('background_remover_model'))
-	apply_state_item('background_remover_color', normalize_color(args.get('background_remover_color')))
+	apply_state_item('background_remover_fill_color', normalize_color(args.get('background_remover_fill_color')))
+	apply_state_item('background_remover_despill_color', normalize_color(args.get('background_remover_despill_color')))
 
 
 def pre_check() -> bool:
@@ -461,16 +536,26 @@ def post_process() -> None:
 
 
 def remove_background(temp_vision_frame : VisionFrame) -> Tuple[VisionFrame, Mask]:
-	temp_vision_mask = forward(prepare_temp_frame(temp_vision_frame))
+	model_type = get_model_options().get('type')
-	temp_vision_mask = normalize_vision_mask(temp_vision_mask)
+
-	temp_vision_mask = cv2.resize(temp_vision_mask, temp_vision_frame.shape[:2][::-1])
+	if model_type == 'corridor_key':
-	temp_vision_frame = apply_background_color(temp_vision_frame, temp_vision_mask)
+		remove_vision_mask, remove_vision_frame = forward_corridor_key(prepare_temp_frame(temp_vision_frame))
-	return temp_vision_frame, temp_vision_mask
+		remove_vision_frame = numpy.squeeze(remove_vision_frame).transpose(1, 2, 0)
+		remove_vision_frame = numpy.clip(remove_vision_frame * 255, 0, 255).astype(numpy.uint8)
+		temp_vision_frame = cv2.resize(remove_vision_frame[:, :, ::-1], temp_vision_frame.shape[:2][::-1])
+	else:
+		remove_vision_mask = forward(prepare_temp_frame(temp_vision_frame))
+
+	remove_vision_mask = normalize_vision_mask(remove_vision_mask)
+	remove_vision_mask = cv2.resize(remove_vision_mask, temp_vision_frame.shape[:2][::-1])
+	temp_vision_frame = apply_despill_color(temp_vision_frame)
+	temp_vision_frame = apply_fill_color(temp_vision_frame, remove_vision_mask)
+	return temp_vision_frame, remove_vision_mask
 
 
 def forward(temp_vision_frame : VisionFrame) -> VisionFrame:
 	background_remover = get_inference_pool().get('background_remover')
-	model_name = state_manager.get_item('background_remover_model')
+	model_type = get_model_options().get('type')
 
 	with thread_semaphore():
 		remove_vision_frame = background_remover.run(None,
@@ -478,20 +563,42 @@ def forward(temp_vision_frame : VisionFrame) -> VisionFrame:
 			'input': temp_vision_frame
 		})[0]
 
-		if model_name == 'u2net_cloth':
+		if model_type == 'u2net_cloth':
 			remove_vision_frame = numpy.argmax(remove_vision_frame, axis = 1)
 
 	return remove_vision_frame
 
 
+def forward_corridor_key(temp_vision_frame : VisionFrame) -> Tuple[Mask, VisionFrame]:
+	background_remover = get_inference_pool().get('background_remover')
+
+	with thread_semaphore():
+		remove_vision_mask, remove_vision_frame = background_remover.run(None,
+		{
+			'input': temp_vision_frame
+		})
+
+	return remove_vision_mask, remove_vision_frame
+
+
 def prepare_temp_frame(temp_vision_frame : VisionFrame) -> VisionFrame:
+	model_type = get_model_options().get('type')
 	model_size = get_model_options().get('size')
 	model_mean = get_model_options().get('mean')
 	model_standard_deviation = get_model_options().get('standard_deviation')
 
+	if model_type == 'corridor_key':
+		coarse_color = temp_vision_frame[:, :, ::-1].astype(numpy.float32) / 255.0
+		coarse_bias = coarse_color[:, :, 1] - numpy.maximum(coarse_color[:, :, 0], coarse_color[:, :, 2])
+		coarse_vision_mask = cv2.resize(1.0 - numpy.clip(coarse_bias * 2.0, 0, 1), model_size)[:, :, numpy.newaxis]
+
 	temp_vision_frame = cv2.resize(temp_vision_frame, model_size)
 	temp_vision_frame = temp_vision_frame[:, :, ::-1] / 255.0
 	temp_vision_frame = (temp_vision_frame - model_mean) / model_standard_deviation
+
+	if model_type == 'corridor_key':
+		temp_vision_frame = numpy.concatenate([ temp_vision_frame, coarse_vision_mask ], axis = 2)
+
 	temp_vision_frame = temp_vision_frame.transpose(2, 0, 1)
 	temp_vision_frame = numpy.expand_dims(temp_vision_frame, axis = 0).astype(numpy.float32)
 	return temp_vision_frame
@@ -503,16 +610,32 @@ def normalize_vision_mask(temp_vision_mask : Mask) -> Mask:
 	return temp_vision_mask
 
 
-def apply_background_color(temp_vision_frame : VisionFrame, temp_vision_mask : Mask) -> VisionFrame:
+def apply_fill_color(temp_vision_frame : VisionFrame, temp_vision_mask : Mask) -> VisionFrame:
-	background_remover_color = state_manager.get_item('background_remover_color')
+	background_remover_fill_color = state_manager.get_item('background_remover_fill_color')
 	temp_vision_mask = temp_vision_mask.astype(numpy.float32) / 255
 	temp_vision_mask = numpy.expand_dims(temp_vision_mask, axis = 2)
-	temp_vision_mask = (1 - temp_vision_mask) * background_remover_color[-1] / 255
+	temp_vision_mask = (1 - temp_vision_mask) * background_remover_fill_color[-1] / 255
-	color_frame = numpy.zeros_like(temp_vision_frame)
+	fill_vision_frame = numpy.zeros_like(temp_vision_frame)
-	color_frame[:, :, 0] = background_remover_color[2]
+	fill_vision_frame[:, :, 0] = background_remover_fill_color[2]
-	color_frame[:, :, 1] = background_remover_color[1]
+	fill_vision_frame[:, :, 1] = background_remover_fill_color[1]
-	color_frame[:, :, 2] = background_remover_color[0]
+	fill_vision_frame[:, :, 2] = background_remover_fill_color[0]
-	temp_vision_frame = temp_vision_frame * (1 - temp_vision_mask) + color_frame * temp_vision_mask
+	temp_vision_frame = temp_vision_frame * (1 - temp_vision_mask) + fill_vision_frame * temp_vision_mask
+	temp_vision_frame = temp_vision_frame.astype(numpy.uint8)
+	return temp_vision_frame
+
+
+def apply_despill_color(temp_vision_frame : VisionFrame) -> VisionFrame:
+	background_remover_despill_color = state_manager.get_item('background_remover_despill_color')
+	temp_vision_frame = temp_vision_frame.astype(numpy.float32)
+	color_alpha = background_remover_despill_color[3] / 255.0
+	despill_vision_frame = numpy.zeros_like(temp_vision_frame)
+	despill_vision_frame[:, :, 0] = background_remover_despill_color[2]
+	despill_vision_frame[:, :, 1] = background_remover_despill_color[1]
+	despill_vision_frame[:, :, 2] = background_remover_despill_color[0]
+	color_weight = despill_vision_frame / numpy.maximum(numpy.max(background_remover_despill_color[:3]), 1)
+	color_limit = numpy.roll(temp_vision_frame, 1, 2) + numpy.roll(temp_vision_frame, -1, 2)
+	limit_vision_frame = numpy.minimum(temp_vision_frame, color_limit * 0.5)
+	temp_vision_frame = temp_vision_frame + (limit_vision_frame - temp_vision_frame) * color_alpha * color_weight
 	temp_vision_frame = temp_vision_frame.astype(numpy.uint8)
 	return temp_vision_frame
 

facefusion/processors/modules/background_remover/locales.py

@@ -7,15 +7,20 @@ LOCALES : Locales =\
 		'help':
 		{
 			'model': 'choose the model responsible for removing the background',
-			'color': 'apply red, green blue and alpha values to the background'
+			'fill_color': 'apply red, green, blue and alpha values to the background',
+			'despill_color': 'remove red, green, blue and alpha values from the foreground'
 		},
 		'uis':
 		{
 			'model_dropdown': 'BACKGROUND REMOVER MODEL',
-			'color_red_number': 'BACKGROUND COLOR RED',
+			'fill_color_red_number': 'FILL COLOR RED',
-			'color_green_number': 'BACKGROUND COLOR GREEN',
+			'fill_color_green_number': 'FILL COLOR GREEN',
-			'color_blue_number': 'BACKGROUND COLOR BLUE',
+			'fill_color_blue_number': 'FILL COLOR BLUE',
-			'color_alpha_number': 'BACKGROUND COLOR ALPHA'
+			'fill_color_alpha_number': 'FILL COLOR ALPHA',
+			'despill_color_red_number': 'DESPILL COLOR RED',
+			'despill_color_green_number': 'DESPILL COLOR GREEN',
+			'despill_color_blue_number': 'DESPILL COLOR BLUE',
+			'despill_color_alpha_number': 'DESPILL COLOR ALPHA'
 		}
 	}
 }

facefusion/processors/modules/background_remover/types.py

@@ -9,4 +9,4 @@ BackgroundRemoverInputs = TypedDict('BackgroundRemoverInputs',
 	'temp_vision_mask' : Mask
 })
 
-BackgroundRemoverModel = Literal['ben_2', 'birefnet_general', 'birefnet_portrait', 'isnet_general', 'modnet', 'ormbg', 'rmbg_1.4', 'rmbg_2.0', 'silueta', 'u2net_cloth', 'u2net_general', 'u2net_human', 'u2netp']
+BackgroundRemoverModel = Literal['ben_2', 'birefnet_general', 'birefnet_portrait', 'corridor_key_1024', 'corridor_key_2048', 'isnet_general', 'modnet', 'ormbg', 'rmbg_1.4', 'rmbg_2.0', 'silueta', 'u2net_cloth', 'u2net_general', 'u2net_human', 'u2netp']

facefusion/processors/modules/face_swapper/core.py

@@ -540,8 +540,8 @@ def pre_process(mode : ProcessMode) -> bool:
 		return False
 
 	source_image_paths = filter_image_paths(state_manager.get_item('source_paths'))
-	source_frames = read_static_images(source_image_paths)
+	source_vision_frames = read_static_images(source_image_paths)
-	source_faces = get_many_faces(source_frames)
+	source_faces = get_many_faces(source_vision_frames)
 
 	if not get_one_face(source_faces):
 		logger.error(translator.get('no_source_face_detected') + translator.get('exclamation_mark'), __name__)

facefusion/processors/modules/frame_enhancer/core.py

@@ -56,7 +56,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 			'__metadata__':
 			{
 				'vendor': 'Helaman',
-				'license': 'Non-Commercial',
+				'license': 'CC-BY-4.0',
 				'year': 2023
 			},
 			'hashes':
@@ -83,7 +83,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 			'__metadata__':
 			{
 				'vendor': 'Phhofm',
-				'license': 'Non-Commercial',
+				'license': 'CC-BY-4.0',
 				'year': 2023
 			},
 			'hashes':
@@ -299,7 +299,7 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 			'__metadata__':
 			{
 				'vendor': 'Helaman',
-				'license': 'Non-Commercial',
+				'license': 'CC-BY-4.0',
 				'year': 2024
 			},
 			'hashes':

facefusion/sanitizer.py

@@ -1,5 +1,7 @@
 import hashlib
-from typing import Sequence
+from typing import Any, Sequence
+
+from facefusion.common_helper import cast_int
 
 
 def sanitize_job_id(job_id : str) -> str:
@@ -10,7 +12,9 @@ def sanitize_job_id(job_id : str) -> str:
 	return hashlib.sha1(job_id.encode()).hexdigest()
 
 
-def sanitize_int_range(value : int, int_range : Sequence[int]) -> int:
+def sanitize_int_range(value : Any, int_range : Sequence[int]) -> int:
+	value = cast_int(value)
+
 	if value in int_range:
 		return value
 	return int_range[0]

facefusion/streamer.py

@@ -26,17 +26,17 @@ def multi_process_capture(camera_capture : cv2.VideoCapture, camera_fps : Fps) -
 			futures = []
 
 			while camera_capture and camera_capture.isOpened():
-				_, capture_frame = camera_capture.read()
+				_, capture_vision_frame = camera_capture.read()
-				if analyse_stream(capture_frame, camera_fps):
+				if analyse_stream(capture_vision_frame, camera_fps):
 					camera_capture.release()
 
-				if numpy.any(capture_frame):
+				if numpy.any(capture_vision_frame):
-					future = executor.submit(process_stream_frame, capture_frame)
+					future = executor.submit(process_stream_frame, capture_vision_frame)
 					futures.append(future)
 
 				for future_done in [ future for future in futures if future.done() ]:
-					capture_frame = future_done.result()
+					capture_vision_frame = future_done.result()
-					capture_deque.append(capture_frame)
+					capture_deque.append(capture_vision_frame)
 					futures.remove(future_done)
 
 				while capture_deque:

facefusion/uis/choices.py

@@ -14,7 +14,7 @@ preview_resolutions : List[str] = [ '512x512', '768x768', '1024x1024' ]
 webcam_modes : List[WebcamMode] = [ 'inline', 'udp', 'v4l2' ]
 webcam_resolutions : List[str] = [ '320x240', '640x480', '800x600', '1024x768', '1280x720', '1280x960', '1920x1080' ]
 
-background_remover_colors : Dict[str, Color] =\
+background_remover_fill_colors : Dict[str, Color] =\
 {
 	'red' : (255, 0, 0, 255),
 	'green' : (0, 255, 0, 255),

facefusion/uis/components/background_remover_options.py

@@ -11,82 +11,132 @@ from facefusion.sanitizer import sanitize_int_range
 from facefusion.uis.core import get_ui_component, register_ui_component
 
 BACKGROUND_REMOVER_MODEL_DROPDOWN : Optional[gradio.Dropdown] = None
-BACKGROUND_REMOVER_COLOR_WRAPPER : Optional[gradio.Group] = None
+BACKGROUND_REMOVER_FILL_COLOR_WRAPPER : Optional[gradio.Group] = None
-BACKGROUND_REMOVER_COLOR_RED_NUMBER : Optional[gradio.Number] = None
+BACKGROUND_REMOVER_FILL_COLOR_RED_NUMBER : Optional[gradio.Number] = None
-BACKGROUND_REMOVER_COLOR_GREEN_NUMBER : Optional[gradio.Number] = None
+BACKGROUND_REMOVER_FILL_COLOR_GREEN_NUMBER : Optional[gradio.Number] = None
-BACKGROUND_REMOVER_COLOR_BLUE_NUMBER : Optional[gradio.Number] = None
+BACKGROUND_REMOVER_FILL_COLOR_BLUE_NUMBER : Optional[gradio.Number] = None
-BACKGROUND_REMOVER_COLOR_ALPHA_NUMBER : Optional[gradio.Number] = None
+BACKGROUND_REMOVER_FILL_COLOR_ALPHA_NUMBER : Optional[gradio.Number] = None
+BACKGROUND_REMOVER_DESPILL_COLOR_WRAPPER : Optional[gradio.Group] = None
+BACKGROUND_REMOVER_DESPILL_COLOR_RED_NUMBER : Optional[gradio.Number] = None
+BACKGROUND_REMOVER_DESPILL_COLOR_GREEN_NUMBER : Optional[gradio.Number] = None
+BACKGROUND_REMOVER_DESPILL_COLOR_BLUE_NUMBER : Optional[gradio.Number] = None
+BACKGROUND_REMOVER_DESPILL_COLOR_ALPHA_NUMBER : Optional[gradio.Number] = None
 
 
 def render() -> None:
 	global BACKGROUND_REMOVER_MODEL_DROPDOWN
-	global BACKGROUND_REMOVER_COLOR_WRAPPER
+	global BACKGROUND_REMOVER_FILL_COLOR_WRAPPER
-	global BACKGROUND_REMOVER_COLOR_RED_NUMBER
+	global BACKGROUND_REMOVER_FILL_COLOR_RED_NUMBER
-	global BACKGROUND_REMOVER_COLOR_GREEN_NUMBER
+	global BACKGROUND_REMOVER_FILL_COLOR_GREEN_NUMBER
-	global BACKGROUND_REMOVER_COLOR_BLUE_NUMBER
+	global BACKGROUND_REMOVER_FILL_COLOR_BLUE_NUMBER
-	global BACKGROUND_REMOVER_COLOR_ALPHA_NUMBER
+	global BACKGROUND_REMOVER_FILL_COLOR_ALPHA_NUMBER
+	global BACKGROUND_REMOVER_DESPILL_COLOR_WRAPPER
+	global BACKGROUND_REMOVER_DESPILL_COLOR_RED_NUMBER
+	global BACKGROUND_REMOVER_DESPILL_COLOR_GREEN_NUMBER
+	global BACKGROUND_REMOVER_DESPILL_COLOR_BLUE_NUMBER
+	global BACKGROUND_REMOVER_DESPILL_COLOR_ALPHA_NUMBER
 
 	has_background_remover = 'background_remover' in state_manager.get_item('processors')
-	background_remover_color = state_manager.get_item('background_remover_color')
+	background_remover_fill_color = state_manager.get_item('background_remover_fill_color')
+	background_remover_despill_color = state_manager.get_item('background_remover_despill_color')
 	BACKGROUND_REMOVER_MODEL_DROPDOWN = gradio.Dropdown(
 		label = translator.get('uis.model_dropdown', 'facefusion.processors.modules.background_remover'),
 		choices = background_remover_choices.background_remover_models,
 		value = state_manager.get_item('background_remover_model'),
 		visible = has_background_remover
 	)
-	with gradio.Group(visible = has_background_remover) as BACKGROUND_REMOVER_COLOR_WRAPPER:
+	with gradio.Group(visible = has_background_remover) as BACKGROUND_REMOVER_FILL_COLOR_WRAPPER:
 		with gradio.Row():
-			BACKGROUND_REMOVER_COLOR_RED_NUMBER = gradio.Number(
+			BACKGROUND_REMOVER_FILL_COLOR_RED_NUMBER = gradio.Number(
-				label = translator.get('uis.color_red_number', 'facefusion.processors.modules.background_remover'),
+				label = translator.get('uis.fill_color_red_number', 'facefusion.processors.modules.background_remover'),
-				value = background_remover_color[0],
+				value = background_remover_fill_color[0],
 				minimum = background_remover_choices.background_remover_color_range[0],
 				maximum = background_remover_choices.background_remover_color_range[-1],
 				step = calculate_int_step(background_remover_choices.background_remover_color_range)
 			)
-			BACKGROUND_REMOVER_COLOR_GREEN_NUMBER = gradio.Number(
+			BACKGROUND_REMOVER_FILL_COLOR_GREEN_NUMBER = gradio.Number(
-				label = translator.get('uis.color_green_number', 'facefusion.processors.modules.background_remover'),
+				label = translator.get('uis.fill_color_green_number', 'facefusion.processors.modules.background_remover'),
-				value = background_remover_color[1],
+				value = background_remover_fill_color[1],
 				minimum = background_remover_choices.background_remover_color_range[0],
 				maximum = background_remover_choices.background_remover_color_range[-1],
 				step = calculate_int_step(background_remover_choices.background_remover_color_range)
 			)
 		with gradio.Row():
-			BACKGROUND_REMOVER_COLOR_BLUE_NUMBER = gradio.Number(
+			BACKGROUND_REMOVER_FILL_COLOR_BLUE_NUMBER = gradio.Number(
-				label = translator.get('uis.color_blue_number', 'facefusion.processors.modules.background_remover'),
+				label = translator.get('uis.fill_color_blue_number', 'facefusion.processors.modules.background_remover'),
-				value = background_remover_color[2],
+				value = background_remover_fill_color[2],
 				minimum = background_remover_choices.background_remover_color_range[0],
 				maximum = background_remover_choices.background_remover_color_range[-1],
 				step = calculate_int_step(background_remover_choices.background_remover_color_range)
 			)
-			BACKGROUND_REMOVER_COLOR_ALPHA_NUMBER = gradio.Number(
+			BACKGROUND_REMOVER_FILL_COLOR_ALPHA_NUMBER = gradio.Number(
-				label = translator.get('uis.color_alpha_number', 'facefusion.processors.modules.background_remover'),
+				label = translator.get('uis.fill_color_alpha_number', 'facefusion.processors.modules.background_remover'),
-				value = background_remover_color[3],
+				value = background_remover_fill_color[3],
+				minimum = background_remover_choices.background_remover_color_range[0],
+				maximum = background_remover_choices.background_remover_color_range[-1],
+				step = calculate_int_step(background_remover_choices.background_remover_color_range)
+			)
+	with gradio.Group(visible = has_background_remover) as BACKGROUND_REMOVER_DESPILL_COLOR_WRAPPER:
+		with gradio.Row():
+			BACKGROUND_REMOVER_DESPILL_COLOR_RED_NUMBER = gradio.Number(
+				label = translator.get('uis.despill_color_red_number', 'facefusion.processors.modules.background_remover'),
+				value = background_remover_despill_color[0],
+				minimum = background_remover_choices.background_remover_color_range[0],
+				maximum = background_remover_choices.background_remover_color_range[-1],
+				step = calculate_int_step(background_remover_choices.background_remover_color_range)
+			)
+			BACKGROUND_REMOVER_DESPILL_COLOR_GREEN_NUMBER = gradio.Number(
+				label = translator.get('uis.despill_color_green_number', 'facefusion.processors.modules.background_remover'),
+				value = background_remover_despill_color[1],
+				minimum = background_remover_choices.background_remover_color_range[0],
+				maximum = background_remover_choices.background_remover_color_range[-1],
+				step = calculate_int_step(background_remover_choices.background_remover_color_range)
+			)
+		with gradio.Row():
+			BACKGROUND_REMOVER_DESPILL_COLOR_BLUE_NUMBER = gradio.Number(
+				label = translator.get('uis.despill_color_blue_number', 'facefusion.processors.modules.background_remover'),
+				value = background_remover_despill_color[2],
+				minimum = background_remover_choices.background_remover_color_range[0],
+				maximum = background_remover_choices.background_remover_color_range[-1],
+				step = calculate_int_step(background_remover_choices.background_remover_color_range)
+			)
+			BACKGROUND_REMOVER_DESPILL_COLOR_ALPHA_NUMBER = gradio.Number(
+				label = translator.get('uis.despill_color_alpha_number', 'facefusion.processors.modules.background_remover'),
+				value = background_remover_despill_color[3],
 				minimum = background_remover_choices.background_remover_color_range[0],
 				maximum = background_remover_choices.background_remover_color_range[-1],
 				step = calculate_int_step(background_remover_choices.background_remover_color_range)
 			)
 	register_ui_component('background_remover_model_dropdown', BACKGROUND_REMOVER_MODEL_DROPDOWN)
-	register_ui_component('background_remover_color_red_number', BACKGROUND_REMOVER_COLOR_RED_NUMBER)
+	register_ui_component('background_remover_fill_color_red_number', BACKGROUND_REMOVER_FILL_COLOR_RED_NUMBER)
-	register_ui_component('background_remover_color_green_number', BACKGROUND_REMOVER_COLOR_GREEN_NUMBER)
+	register_ui_component('background_remover_fill_color_green_number', BACKGROUND_REMOVER_FILL_COLOR_GREEN_NUMBER)
-	register_ui_component('background_remover_color_blue_number', BACKGROUND_REMOVER_COLOR_BLUE_NUMBER)
+	register_ui_component('background_remover_fill_color_blue_number', BACKGROUND_REMOVER_FILL_COLOR_BLUE_NUMBER)
-	register_ui_component('background_remover_color_alpha_number', BACKGROUND_REMOVER_COLOR_ALPHA_NUMBER)
+	register_ui_component('background_remover_fill_color_alpha_number', BACKGROUND_REMOVER_FILL_COLOR_ALPHA_NUMBER)
+	register_ui_component('background_remover_despill_color_red_number', BACKGROUND_REMOVER_DESPILL_COLOR_RED_NUMBER)
+	register_ui_component('background_remover_despill_color_green_number', BACKGROUND_REMOVER_DESPILL_COLOR_GREEN_NUMBER)
+	register_ui_component('background_remover_despill_color_blue_number', BACKGROUND_REMOVER_DESPILL_COLOR_BLUE_NUMBER)
+	register_ui_component('background_remover_despill_color_alpha_number', BACKGROUND_REMOVER_DESPILL_COLOR_ALPHA_NUMBER)
 
 
 def listen() -> None:
 	BACKGROUND_REMOVER_MODEL_DROPDOWN.change(update_background_remover_model, inputs = BACKGROUND_REMOVER_MODEL_DROPDOWN, outputs = BACKGROUND_REMOVER_MODEL_DROPDOWN)
-	background_remover_color_inputs = [ BACKGROUND_REMOVER_COLOR_RED_NUMBER, BACKGROUND_REMOVER_COLOR_GREEN_NUMBER, BACKGROUND_REMOVER_COLOR_BLUE_NUMBER, BACKGROUND_REMOVER_COLOR_ALPHA_NUMBER ]
+	background_remover_fill_color_inputs = [ BACKGROUND_REMOVER_FILL_COLOR_RED_NUMBER, BACKGROUND_REMOVER_FILL_COLOR_GREEN_NUMBER, BACKGROUND_REMOVER_FILL_COLOR_BLUE_NUMBER, BACKGROUND_REMOVER_FILL_COLOR_ALPHA_NUMBER ]
+	background_remover_despill_color_inputs = [ BACKGROUND_REMOVER_DESPILL_COLOR_RED_NUMBER, BACKGROUND_REMOVER_DESPILL_COLOR_GREEN_NUMBER, BACKGROUND_REMOVER_DESPILL_COLOR_BLUE_NUMBER, BACKGROUND_REMOVER_DESPILL_COLOR_ALPHA_NUMBER ]
 
-	for background_remover_color_input in background_remover_color_inputs:
+	for background_remover_fill_color_input in background_remover_fill_color_inputs:
-		background_remover_color_input.change(update_background_remover_color, inputs = background_remover_color_inputs)
+		background_remover_fill_color_input.change(update_background_remover_fill_color, inputs = background_remover_fill_color_inputs)
+
+	for background_remover_despill_color_input in background_remover_despill_color_inputs:
+		background_remover_despill_color_input.change(update_background_remover_despill_color, inputs = background_remover_despill_color_inputs)
 
 	processors_checkbox_group = get_ui_component('processors_checkbox_group')
 	if processors_checkbox_group:
-		processors_checkbox_group.change(remote_update, inputs = processors_checkbox_group, outputs = [ BACKGROUND_REMOVER_MODEL_DROPDOWN, BACKGROUND_REMOVER_COLOR_WRAPPER ])
+		processors_checkbox_group.change(remote_update, inputs = processors_checkbox_group, outputs = [ BACKGROUND_REMOVER_MODEL_DROPDOWN, BACKGROUND_REMOVER_FILL_COLOR_WRAPPER, BACKGROUND_REMOVER_DESPILL_COLOR_WRAPPER ])
 
 
-def remote_update(processors : List[str]) -> Tuple[gradio.Dropdown, gradio.Group]:
+def remote_update(processors : List[str]) -> Tuple[gradio.Dropdown, gradio.Group, gradio.Group]:
 	has_background_remover = 'background_remover' in processors
-	return gradio.Dropdown(visible = has_background_remover), gradio.Group(visible = has_background_remover)
+	return gradio.Dropdown(visible = has_background_remover), gradio.Group(visible = has_background_remover), gradio.Group(visible = has_background_remover)
 
 
 def update_background_remover_model(background_remover_model : BackgroundRemoverModel) -> gradio.Dropdown:
@@ -99,9 +149,17 @@ def update_background_remover_model(background_remover_model : BackgroundRemover
 	return gradio.Dropdown()
 
 
-def update_background_remover_color(red : int, green : int, blue : int, alpha : int) -> None:
+def update_background_remover_fill_color(red : int, green : int, blue : int, alpha : int) -> None:
 	red = sanitize_int_range(red, background_remover_choices.background_remover_color_range)
 	green = sanitize_int_range(green, background_remover_choices.background_remover_color_range)
 	blue = sanitize_int_range(blue, background_remover_choices.background_remover_color_range)
 	alpha = sanitize_int_range(alpha, background_remover_choices.background_remover_color_range)
-	state_manager.set_item('background_remover_color', (red, green, blue, alpha))
+	state_manager.set_item('background_remover_fill_color', (red, green, blue, alpha))
+
+
+def update_background_remover_despill_color(red : int, green : int, blue : int, alpha : int) -> None:
+	red = sanitize_int_range(red, background_remover_choices.background_remover_color_range)
+	green = sanitize_int_range(green, background_remover_choices.background_remover_color_range)
+	blue = sanitize_int_range(blue, background_remover_choices.background_remover_color_range)
+	alpha = sanitize_int_range(alpha, background_remover_choices.background_remover_color_range)
+	state_manager.set_item('background_remover_despill_color', (red, green, blue, alpha))

facefusion/uis/components/preview.py

@@ -90,10 +90,14 @@ def listen() -> None:
 
 	for ui_component in get_ui_components(
 	[
-		'background_remover_color_red_number',
+		'background_remover_fill_color_red_number',
-		'background_remover_color_green_number',
+		'background_remover_fill_color_green_number',
-		'background_remover_color_blue_number',
+		'background_remover_fill_color_blue_number',
-		'background_remover_color_alpha_number',
+		'background_remover_fill_color_alpha_number',
+		'background_remover_despill_color_red_number',
+		'background_remover_despill_color_green_number',
+		'background_remover_despill_color_blue_number',
+		'background_remover_despill_color_alpha_number',
 		'face_debugger_items_checkbox_group',
 		'frame_colorizer_size_dropdown',
 		'face_mask_types_checkbox_group',
@@ -296,7 +300,7 @@ def extract_crop_frame(vision_frame : VisionFrame, face : Face) -> Optional[Visi
 
 
 def prepare_output_frame(target_vision_frame : VisionFrame, temp_vision_frame : VisionFrame, temp_vision_mask : Mask) -> VisionFrame:
-	temp_vision_mask = temp_vision_mask.clip(state_manager.get_item('background_remover_color')[-1], 255)
+	temp_vision_mask = temp_vision_mask.clip(state_manager.get_item('background_remover_fill_color')[-1], 255)
 	temp_vision_frame = merge_vision_mask(temp_vision_frame, temp_vision_mask)
 	temp_vision_frame = cv2.resize(temp_vision_frame, target_vision_frame.shape[1::-1])
 	return temp_vision_frame

facefusion/uis/components/webcam.py

@@ -98,15 +98,15 @@ def start(webcam_device_id : int, webcam_mode : WebcamMode, webcam_resolution :
 		camera_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, webcam_height)
 		camera_capture.set(cv2.CAP_PROP_FPS, webcam_fps)
 
-		for capture_frame in multi_process_capture(camera_capture, webcam_fps):
+		for capture_vision_frame in multi_process_capture(camera_capture, webcam_fps):
-			capture_frame = cv2.cvtColor(capture_frame, cv2.COLOR_BGR2RGB)
+			capture_vision_frame = cv2.cvtColor(capture_vision_frame, cv2.COLOR_BGR2RGB)
-			capture_frame = fit_cover_frame(capture_frame, (webcam_width, webcam_height))
+			capture_vision_frame = fit_cover_frame(capture_vision_frame, (webcam_width, webcam_height))
 
 			if webcam_mode == 'inline':
-				yield capture_frame
+				yield capture_vision_frame
 			if webcam_mode in [ 'udp', 'v4l2' ]:
 				try:
-					stream.stdin.write(capture_frame.tobytes())
+					stream.stdin.write(capture_vision_frame.tobytes())
 				except Exception:
 					pass
 

facefusion/uis/types.py

@@ -6,10 +6,14 @@ ComponentName = Literal\
 	'age_modifier_direction_slider',
 	'age_modifier_model_dropdown',
 	'background_remover_model_dropdown',
-	'background_remover_color_red_number',
+	'background_remover_fill_color_red_number',
-	'background_remover_color_green_number',
+	'background_remover_fill_color_green_number',
-	'background_remover_color_blue_number',
+	'background_remover_fill_color_blue_number',
-	'background_remover_color_alpha_number',
+	'background_remover_fill_color_alpha_number',
+	'background_remover_despill_color_red_number',
+	'background_remover_despill_color_green_number',
+	'background_remover_despill_color_blue_number',
+	'background_remover_despill_color_alpha_number',
 	'deep_swapper_model_dropdown',
 	'deep_swapper_morph_slider',
 	'expression_restorer_factor_slider',

facefusion/voice_extractor.py

@@ -69,8 +69,8 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 		{
 			'__metadata__':
 			{
-				'vendor': 'Unknown',
+				'vendor': 'Anjok07',
-				'license': 'Non-Commercial',
+				'license': 'MIT',
 				'year': 2023
 			},
 			'hashes':

requirements.txt

@@ -1,8 +1,8 @@
 gradio-rangeslider==0.0.8
 gradio==5.44.1
 numpy==2.2.1
-onnx==1.20.1
+onnx==1.21.0
-onnxruntime==1.24.3
+onnxruntime==1.24.4
 opencv-python==4.13.0.92
 tqdm==4.67.3
 scipy==1.17.1

tests/test_curl_builder.py

@@ -7,7 +7,7 @@ from facefusion.curl_builder import chain, ping, run, set_timeout
 def test_run() -> None:
 	user_agent = metadata.get('name') + '/' + metadata.get('version')
 
-	assert run([]) == [ which('curl'), '--user-agent', user_agent, '--location', '--silent' ]
+	assert run([]) == [ which('curl'), '--user-agent', user_agent, '--location', '--silent', '--ssl-no-revoke' ]
 
 
 def test_chain() -> None:

tests/test_face_analyser.py

@@ -5,6 +5,7 @@ import pytest
 from facefusion import face_classifier, face_detector, face_landmarker, face_recognizer, state_manager
 from facefusion.download import conditional_download
 from facefusion.face_analyser import get_many_faces
+from facefusion.face_store import clear_static_faces
 from facefusion.vision import read_static_image
 from .helper import get_test_example_file, get_test_examples_directory
 
@@ -37,6 +38,7 @@ def before_each() -> None:
 	face_detector.clear_inference_pool()
 	face_landmarker.clear_inference_pool()
 	face_recognizer.clear_inference_pool()
+	clear_static_faces()
 
 
 def test_get_one_face_with_retinaface() -> None:
@@ -62,7 +64,7 @@ def test_get_one_face_with_retinaface() -> None:
 
 def test_get_one_face_with_scrfd() -> None:
 	state_manager.init_item('face_detector_model', 'scrfd')
-	state_manager.init_item('face_detector_size', '640x640')
+	state_manager.init_item('face_detector_size', '320x320')
 	state_manager.init_item('face_detector_margin', (0, 0, 0, 0))
 	face_detector.pre_check()
 
@@ -82,7 +84,7 @@ def test_get_one_face_with_scrfd() -> None:
 
 
 def test_get_one_face_with_yoloface() -> None:
-	state_manager.init_item('face_detector_model', 'yoloface')
+	state_manager.init_item('face_detector_model', 'yolo_face')
 	state_manager.init_item('face_detector_size', '640x640')
 	state_manager.init_item('face_detector_margin', (0, 0, 0, 0))
 	face_detector.pre_check()

tests/test_vision.py

@@ -1,7 +1,9 @@
+import os
 import subprocess
 
 import pytest
 
+from facefusion.common_helper import is_linux
 from facefusion.download import conditional_download
 from facefusion.vision import calculate_histogram_difference, count_trim_frame_total, count_video_frame_total, detect_image_resolution, detect_video_duration, detect_video_fps, detect_video_resolution, match_frame_color, normalize_resolution, pack_resolution, predict_video_frame_total, read_image, read_video_frame, restrict_image_resolution, restrict_trim_frame, restrict_video_fps, restrict_video_resolution, scale_resolution, unpack_resolution, write_image
 from .helper import get_test_example_file, get_test_examples_directory, get_test_output_file, prepare_test_output_directory
@@ -92,11 +94,13 @@ def test_restrict_video_fps() -> None:
 	assert restrict_video_fps(get_test_example_file('target-1080p.mp4'), 60.0) == 25.0
 
 
+@pytest.mark.skipif(os.environ.get('CI') and is_linux(), reason = 'h264 codec not present')
 def test_detect_video_duration() -> None:
 	assert detect_video_duration(get_test_example_file('target-240p.mp4')) == 10.8
 	assert detect_video_duration('invalid') == 0
 
 
+@pytest.mark.skipif(os.environ.get('CI') and is_linux(), reason = 'h264 codec not present')
 def test_count_trim_frame_total() -> None:
 	assert count_trim_frame_total(get_test_example_file('target-240p.mp4'), 0, 200) == 200
 	assert count_trim_frame_total(get_test_example_file('target-240p.mp4'), 70, 270) == 200
@@ -107,6 +111,7 @@ def test_count_trim_frame_total() -> None:
 	assert count_trim_frame_total(get_test_example_file('target-240p.mp4'), None, None) == 270
 
 
+@pytest.mark.skipif(os.environ.get('CI') and is_linux(), reason = 'h264 codec not present')
 def test_restrict_trim_frame() -> None:
 	assert restrict_trim_frame(get_test_example_file('target-240p.mp4'), 0, 200) == (0, 200)
 	assert restrict_trim_frame(get_test_example_file('target-240p.mp4'), 70, 270) == (70, 270)
@@ -117,6 +122,7 @@ def test_restrict_trim_frame() -> None:
 	assert restrict_trim_frame(get_test_example_file('target-240p.mp4'), None, None) == (0, 270)
 
 
+@pytest.mark.skipif(os.environ.get('CI') and is_linux(), reason = 'h264 codec not present')
 def test_detect_video_resolution() -> None:
 	assert detect_video_resolution(get_test_example_file('target-240p.mp4')) == (426, 226)
 	assert detect_video_resolution(get_test_example_file('target-240p-90deg.mp4')) == (226, 426)