Upload folder using huggingface_hub (#2)

- Upload folder using huggingface_hub (b556ac0ef213de8d4a9dfc71aea428366fe3b1b0)

DeepFakeAI/capturer.py

@@ -1,7 +1,7 @@
 from typing import Optional
 import cv2
 
-from facefusion.typing import Frame
+from DeepFakeAI.typing import Frame
 
 
 def get_video_frame(video_path : str, frame_number : int = 0) -> Optional[Frame]:

DeepFakeAI/choices.py

@@ -1,6 +1,6 @@
 from typing import List
 
-from facefusion.typing import FaceRecognition, FaceAnalyserDirection, FaceAnalyserAge, FaceAnalyserGender, TempFrameFormat, OutputVideoEncoder
+from DeepFakeAI.typing import FaceRecognition, FaceAnalyserDirection, FaceAnalyserAge, FaceAnalyserGender, TempFrameFormat, OutputVideoEncoder
 
 face_recognition : List[FaceRecognition] = [ 'reference', 'many' ]
 face_analyser_direction : List[FaceAnalyserDirection] = [ 'left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small']

DeepFakeAI/core.py

@@ -15,12 +15,12 @@ import argparse
 import onnxruntime
 import tensorflow
 
-import facefusion.choices
-import facefusion.globals
-from facefusion import wording, metadata
-from facefusion.predictor import predict_image, predict_video
-from facefusion.processors.frame.core import get_frame_processors_modules
-from facefusion.utilities import is_image, is_video, detect_fps, create_video, extract_frames, get_temp_frame_paths, restore_audio, create_temp, move_temp, clear_temp, normalize_output_path, list_module_names, decode_execution_providers, encode_execution_providers
+import DeepFakeAI.choices
+import DeepFakeAI.globals
+from DeepFakeAI import wording, metadata
+from DeepFakeAI.predictor import predict_image, predict_video
+from DeepFakeAI.processors.frame.core import get_frame_processors_modules
+from DeepFakeAI.utilities import is_image, is_video, detect_fps, create_video, extract_frames, get_temp_frame_paths, restore_audio, create_temp, move_temp, clear_temp, normalize_output_path, list_module_names, decode_execution_providers, encode_execution_providers
 
 warnings.filterwarnings('ignore', category = FutureWarning, module = 'insightface')
 warnings.filterwarnings('ignore', category = UserWarning, module = 'torchvision')
@@ -32,23 +32,23 @@ def parse_args() -> None:
 	program.add_argument('-s', '--source', help = wording.get('source_help'), dest = 'source_path')
 	program.add_argument('-t', '--target', help = wording.get('target_help'), dest = 'target_path')
 	program.add_argument('-o', '--output', help = wording.get('output_help'), dest = 'output_path')
-	program.add_argument('--frame-processors', help = wording.get('frame_processors_help').format(choices = ', '.join(list_module_names('facefusion/processors/frame/modules'))), dest = 'frame_processors', default = ['face_swapper'], nargs='+')
-	program.add_argument('--ui-layouts', help = wording.get('ui_layouts_help').format(choices = ', '.join(list_module_names('facefusion/uis/layouts'))), dest = 'ui_layouts', default = ['default'], nargs='+')
+	program.add_argument('--frame-processors', help = wording.get('frame_processors_help').format(choices = ', '.join(list_module_names('DeepFakeAI/processors/frame/modules'))), dest = 'frame_processors', default = ['face_swapper'], nargs='+')
+	program.add_argument('--ui-layouts', help = wording.get('ui_layouts_help').format(choices = ', '.join(list_module_names('DeepFakeAI/uis/layouts'))), dest = 'ui_layouts', default = ['default'], nargs='+')
 	program.add_argument('--keep-fps', help = wording.get('keep_fps_help'), dest = 'keep_fps', action='store_true')
 	program.add_argument('--keep-temp', help = wording.get('keep_temp_help'), dest = 'keep_temp', action='store_true')
 	program.add_argument('--skip-audio', help = wording.get('skip_audio_help'), dest = 'skip_audio', action='store_true')
-	program.add_argument('--face-recognition', help = wording.get('face_recognition_help'), dest = 'face_recognition', default = 'reference', choices = facefusion.choices.face_recognition)
-	program.add_argument('--face-analyser-direction', help = wording.get('face_analyser_direction_help'), dest = 'face_analyser_direction', default = 'left-right', choices = facefusion.choices.face_analyser_direction)
-	program.add_argument('--face-analyser-age', help = wording.get('face_analyser_age_help'), dest = 'face_analyser_age', choices = facefusion.choices.face_analyser_age)
-	program.add_argument('--face-analyser-gender', help = wording.get('face_analyser_gender_help'), dest = 'face_analyser_gender', choices = facefusion.choices.face_analyser_gender)
+	program.add_argument('--face-recognition', help = wording.get('face_recognition_help'), dest = 'face_recognition', default = 'reference', choices = DeepFakeAI.choices.face_recognition)
+	program.add_argument('--face-analyser-direction', help = wording.get('face_analyser_direction_help'), dest = 'face_analyser_direction', default = 'left-right', choices = DeepFakeAI.choices.face_analyser_direction)
+	program.add_argument('--face-analyser-age', help = wording.get('face_analyser_age_help'), dest = 'face_analyser_age', choices = DeepFakeAI.choices.face_analyser_age)
+	program.add_argument('--face-analyser-gender', help = wording.get('face_analyser_gender_help'), dest = 'face_analyser_gender', choices = DeepFakeAI.choices.face_analyser_gender)
 	program.add_argument('--reference-face-position', help = wording.get('reference_face_position_help'), dest = 'reference_face_position', type = int, default = 0)
 	program.add_argument('--reference-face-distance', help = wording.get('reference_face_distance_help'), dest = 'reference_face_distance', type = float, default = 1.5)
 	program.add_argument('--reference-frame-number', help = wording.get('reference_frame_number_help'), dest = 'reference_frame_number', type = int, default = 0)
 	program.add_argument('--trim-frame-start', help = wording.get('trim_frame_start_help'), dest = 'trim_frame_start', type = int)
 	program.add_argument('--trim-frame-end', help = wording.get('trim_frame_end_help'), dest = 'trim_frame_end', type = int)
-	program.add_argument('--temp-frame-format', help = wording.get('temp_frame_format_help'), dest = 'temp_frame_format', default = 'jpg', choices = facefusion.choices.temp_frame_format)
+	program.add_argument('--temp-frame-format', help = wording.get('temp_frame_format_help'), dest = 'temp_frame_format', default = 'jpg', choices = DeepFakeAI.choices.temp_frame_format)
 	program.add_argument('--temp-frame-quality', help = wording.get('temp_frame_quality_help'), dest = 'temp_frame_quality', type = int, default = 100, choices = range(101), metavar = '[0-100]')
-	program.add_argument('--output-video-encoder', help = wording.get('output_video_encoder_help'), dest = 'output_video_encoder', default = 'libx264', choices = facefusion.choices.output_video_encoder)
+	program.add_argument('--output-video-encoder', help = wording.get('output_video_encoder_help'), dest = 'output_video_encoder', default = 'libx264', choices = DeepFakeAI.choices.output_video_encoder)
 	program.add_argument('--output-video-quality', help = wording.get('output_video_quality_help'), dest = 'output_video_quality', type = int, default = 90, choices = range(101), metavar = '[0-100]')
 	program.add_argument('--max-memory', help = wording.get('max_memory_help'), dest = 'max_memory', type = int)
 	program.add_argument('--execution-providers', help = wording.get('execution_providers_help').format(choices = 'cpu'), dest = 'execution_providers', default = ['cpu'], choices = suggest_execution_providers_choices(), nargs='+')
@@ -58,32 +58,32 @@ def parse_args() -> None:
 
 	args = program.parse_args()
 
-	facefusion.globals.source_path = args.source_path
-	facefusion.globals.target_path = args.target_path
-	facefusion.globals.output_path = normalize_output_path(facefusion.globals.source_path, facefusion.globals.target_path, args.output_path)
-	facefusion.globals.headless = facefusion.globals.source_path is not None and facefusion.globals.target_path is not None and facefusion.globals.output_path is not None
-	facefusion.globals.frame_processors = args.frame_processors
-	facefusion.globals.ui_layouts = args.ui_layouts
-	facefusion.globals.keep_fps = args.keep_fps
-	facefusion.globals.keep_temp = args.keep_temp
-	facefusion.globals.skip_audio = args.skip_audio
-	facefusion.globals.face_recognition = args.face_recognition
-	facefusion.globals.face_analyser_direction = args.face_analyser_direction
-	facefusion.globals.face_analyser_age = args.face_analyser_age
-	facefusion.globals.face_analyser_gender = args.face_analyser_gender
-	facefusion.globals.reference_face_position = args.reference_face_position
-	facefusion.globals.reference_frame_number = args.reference_frame_number
-	facefusion.globals.reference_face_distance = args.reference_face_distance
-	facefusion.globals.trim_frame_start = args.trim_frame_start
-	facefusion.globals.trim_frame_end = args.trim_frame_end
-	facefusion.globals.temp_frame_format = args.temp_frame_format
-	facefusion.globals.temp_frame_quality = args.temp_frame_quality
-	facefusion.globals.output_video_encoder = args.output_video_encoder
-	facefusion.globals.output_video_quality = args.output_video_quality
-	facefusion.globals.max_memory = args.max_memory
-	facefusion.globals.execution_providers = decode_execution_providers(args.execution_providers)
-	facefusion.globals.execution_thread_count = args.execution_thread_count
-	facefusion.globals.execution_queue_count = args.execution_queue_count
+	DeepFakeAI.globals.source_path = args.source_path
+	DeepFakeAI.globals.target_path = args.target_path
+	DeepFakeAI.globals.output_path = normalize_output_path(DeepFakeAI.globals.source_path, DeepFakeAI.globals.target_path, args.output_path)
+	DeepFakeAI.globals.headless = DeepFakeAI.globals.source_path is not None and DeepFakeAI.globals.target_path is not None and DeepFakeAI.globals.output_path is not None
+	DeepFakeAI.globals.frame_processors = args.frame_processors
+	DeepFakeAI.globals.ui_layouts = args.ui_layouts
+	DeepFakeAI.globals.keep_fps = args.keep_fps
+	DeepFakeAI.globals.keep_temp = args.keep_temp
+	DeepFakeAI.globals.skip_audio = args.skip_audio
+	DeepFakeAI.globals.face_recognition = args.face_recognition
+	DeepFakeAI.globals.face_analyser_direction = args.face_analyser_direction
+	DeepFakeAI.globals.face_analyser_age = args.face_analyser_age
+	DeepFakeAI.globals.face_analyser_gender = args.face_analyser_gender
+	DeepFakeAI.globals.reference_face_position = args.reference_face_position
+	DeepFakeAI.globals.reference_frame_number = args.reference_frame_number
+	DeepFakeAI.globals.reference_face_distance = args.reference_face_distance
+	DeepFakeAI.globals.trim_frame_start = args.trim_frame_start
+	DeepFakeAI.globals.trim_frame_end = args.trim_frame_end
+	DeepFakeAI.globals.temp_frame_format = args.temp_frame_format
+	DeepFakeAI.globals.temp_frame_quality = args.temp_frame_quality
+	DeepFakeAI.globals.output_video_encoder = args.output_video_encoder
+	DeepFakeAI.globals.output_video_quality = args.output_video_quality
+	DeepFakeAI.globals.max_memory = args.max_memory
+	DeepFakeAI.globals.execution_providers = decode_execution_providers(args.execution_providers)
+	DeepFakeAI.globals.execution_thread_count = args.execution_thread_count
+	DeepFakeAI.globals.execution_queue_count = args.execution_queue_count
 
 
 def suggest_execution_providers_choices() -> List[str]:
@@ -104,10 +104,10 @@ def limit_resources() -> None:
 			tensorflow.config.experimental.VirtualDeviceConfiguration(memory_limit = 1024)
 		])
 	# limit memory usage
-	if facefusion.globals.max_memory:
-		memory = facefusion.globals.max_memory * 1024 ** 3
+	if DeepFakeAI.globals.max_memory:
+		memory = DeepFakeAI.globals.max_memory * 1024 ** 3
 		if platform.system().lower() == 'darwin':
-			memory = facefusion.globals.max_memory * 1024 ** 6
+			memory = DeepFakeAI.globals.max_memory * 1024 ** 6
 		if platform.system().lower() == 'windows':
 			import ctypes
 			kernel32 = ctypes.windll.kernel32 # type: ignore[attr-defined]
@@ -132,69 +132,69 @@ def pre_check() -> bool:
 
 
 def process_image() -> None:
-	if predict_image(facefusion.globals.target_path):
+	if predict_image(DeepFakeAI.globals.target_path):
 		return
-	shutil.copy2(facefusion.globals.target_path, facefusion.globals.output_path)
+	shutil.copy2(DeepFakeAI.globals.target_path, DeepFakeAI.globals.output_path)
 	# process frame
-	for frame_processor_module in get_frame_processors_modules(facefusion.globals.frame_processors):
+	for frame_processor_module in get_frame_processors_modules(DeepFakeAI.globals.frame_processors):
 		update_status(wording.get('processing'), frame_processor_module.NAME)
-		frame_processor_module.process_image(facefusion.globals.source_path, facefusion.globals.output_path, facefusion.globals.output_path)
+		frame_processor_module.process_image(DeepFakeAI.globals.source_path, DeepFakeAI.globals.output_path, DeepFakeAI.globals.output_path)
 		frame_processor_module.post_process()
 	# validate image
-	if is_image(facefusion.globals.target_path):
+	if is_image(DeepFakeAI.globals.target_path):
 		update_status(wording.get('processing_image_succeed'))
 	else:
 		update_status(wording.get('processing_image_failed'))
 
 
 def process_video() -> None:
-	if predict_video(facefusion.globals.target_path):
+	if predict_video(DeepFakeAI.globals.target_path):
 		return
-	fps = detect_fps(facefusion.globals.target_path) if facefusion.globals.keep_fps else 25.0
+	fps = detect_fps(DeepFakeAI.globals.target_path) if DeepFakeAI.globals.keep_fps else 25.0
 	update_status(wording.get('creating_temp'))
-	create_temp(facefusion.globals.target_path)
+	create_temp(DeepFakeAI.globals.target_path)
 	# extract frames
 	update_status(wording.get('extracting_frames_fps').format(fps = fps))
-	extract_frames(facefusion.globals.target_path, fps)
+	extract_frames(DeepFakeAI.globals.target_path, fps)
 	# process frame
-	temp_frame_paths = get_temp_frame_paths(facefusion.globals.target_path)
+	temp_frame_paths = get_temp_frame_paths(DeepFakeAI.globals.target_path)
 	if temp_frame_paths:
-		for frame_processor_module in get_frame_processors_modules(facefusion.globals.frame_processors):
+		for frame_processor_module in get_frame_processors_modules(DeepFakeAI.globals.frame_processors):
 			update_status(wording.get('processing'), frame_processor_module.NAME)
-			frame_processor_module.process_video(facefusion.globals.source_path, temp_frame_paths)
+			frame_processor_module.process_video(DeepFakeAI.globals.source_path, temp_frame_paths)
 			frame_processor_module.post_process()
 	else:
 		update_status(wording.get('temp_frames_not_found'))
 		return
 	# create video
 	update_status(wording.get('creating_video_fps').format(fps = fps))
-	if not create_video(facefusion.globals.target_path, fps):
+	if not create_video(DeepFakeAI.globals.target_path, fps):
 		update_status(wording.get('creating_video_failed'))
 		return
 	# handle audio
-	if facefusion.globals.skip_audio:
+	if DeepFakeAI.globals.skip_audio:
 		update_status(wording.get('skipping_audio'))
-		move_temp(facefusion.globals.target_path, facefusion.globals.output_path)
+		move_temp(DeepFakeAI.globals.target_path, DeepFakeAI.globals.output_path)
 	else:
 		update_status(wording.get('restoring_audio'))
-		restore_audio(facefusion.globals.target_path, facefusion.globals.output_path)
+		restore_audio(DeepFakeAI.globals.target_path, DeepFakeAI.globals.output_path)
 	# clear temp
 	update_status(wording.get('clearing_temp'))
-	clear_temp(facefusion.globals.target_path)
+	clear_temp(DeepFakeAI.globals.target_path)
 	# validate video
-	if is_video(facefusion.globals.target_path):
+	if is_video(DeepFakeAI.globals.target_path):
 		update_status(wording.get('processing_video_succeed'))
 	else:
 		update_status(wording.get('processing_video_failed'))
 
 
 def conditional_process() -> None:
-	for frame_processor_module in get_frame_processors_modules(facefusion.globals.frame_processors):
+	for frame_processor_module in get_frame_processors_modules(DeepFakeAI.globals.frame_processors):
 		if not frame_processor_module.pre_process():
 			return
-	if is_image(facefusion.globals.target_path):
+	if is_image(DeepFakeAI.globals.target_path):
 		process_image()
-	if is_video(facefusion.globals.target_path):
+	if is_video(DeepFakeAI.globals.target_path):
 		process_video()
 
 
@@ -204,19 +204,19 @@ def run() -> None:
 	# pre check
 	if not pre_check():
 		return
-	for frame_processor in get_frame_processors_modules(facefusion.globals.frame_processors):
+	for frame_processor in get_frame_processors_modules(DeepFakeAI.globals.frame_processors):
 		if not frame_processor.pre_check():
 			return
 	# process or launch
-	if facefusion.globals.headless:
+	if DeepFakeAI.globals.headless:
 		conditional_process()
 	else:
-		import facefusion.uis.core as ui
+		import DeepFakeAI.uis.core as ui
 
 		ui.launch()
 
 
 def destroy() -> None:
-	if facefusion.globals.target_path:
-		clear_temp(facefusion.globals.target_path)
+	if DeepFakeAI.globals.target_path:
+		clear_temp(DeepFakeAI.globals.target_path)
 	sys.exit()

DeepFakeAI/face_analyser.py

@@ -3,8 +3,8 @@ from typing import Any, Optional, List
 import insightface
 import numpy
 
-import facefusion.globals
-from facefusion.typing import Frame, Face, FaceAnalyserDirection, FaceAnalyserAge, FaceAnalyserGender
+import DeepFakeAI.globals
+from DeepFakeAI.typing import Frame, Face, FaceAnalyserDirection, FaceAnalyserAge, FaceAnalyserGender
 
 FACE_ANALYSER = None
 THREAD_LOCK = threading.Lock()
@@ -15,7 +15,7 @@ def get_face_analyser() -> Any:
 
 	with THREAD_LOCK:
 		if FACE_ANALYSER is None:
-			FACE_ANALYSER = insightface.app.FaceAnalysis(name = 'buffalo_l', providers = facefusion.globals.execution_providers)
+			FACE_ANALYSER = insightface.app.FaceAnalysis(name = 'buffalo_l', providers = DeepFakeAI.globals.execution_providers)
 			FACE_ANALYSER.prepare(ctx_id = 0)
 	return FACE_ANALYSER
 
@@ -39,12 +39,12 @@ def get_one_face(frame : Frame, position : int = 0) -> Optional[Face]:
 def get_many_faces(frame : Frame) -> List[Face]:
 	try:
 		faces = get_face_analyser().get(frame)
-		if facefusion.globals.face_analyser_direction:
-			faces = sort_by_direction(faces, facefusion.globals.face_analyser_direction)
-		if facefusion.globals.face_analyser_age:
-			faces = filter_by_age(faces, facefusion.globals.face_analyser_age)
-		if facefusion.globals.face_analyser_gender:
-			faces = filter_by_gender(faces, facefusion.globals.face_analyser_gender)
+		if DeepFakeAI.globals.face_analyser_direction:
+			faces = sort_by_direction(faces, DeepFakeAI.globals.face_analyser_direction)
+		if DeepFakeAI.globals.face_analyser_age:
+			faces = filter_by_age(faces, DeepFakeAI.globals.face_analyser_age)
+		if DeepFakeAI.globals.face_analyser_gender:
+			faces = filter_by_gender(faces, DeepFakeAI.globals.face_analyser_gender)
 		return faces
 	except (AttributeError, ValueError):
 		return []

DeepFakeAI/face_reference.py

@@ -1,6 +1,6 @@
 from typing import Optional
 
-from facefusion.typing import Face
+from DeepFakeAI.typing import Face
 
 FACE_REFERENCE = None
 

DeepFakeAI/globals.py

@@ -1,6 +1,6 @@
 from typing import List, Optional
 
-from facefusion.typing import FaceRecognition, FaceAnalyserDirection, FaceAnalyserAge, FaceAnalyserGender, TempFrameFormat
+from DeepFakeAI.typing import FaceRecognition, FaceAnalyserDirection, FaceAnalyserAge, FaceAnalyserGender, TempFrameFormat
 
 source_path : Optional[str] = None
 target_path : Optional[str] = None

DeepFakeAI/metadata.py

@@ -5,7 +5,7 @@ METADATA =\
 	'version': '1.0.0',
 	'license': 'MIT',
 	'author': 'Henry Ruhs',
-	'url': 'https://facefusion.io'
+	'url': 'https://DeepFakeAI.io'
 }
 
 

DeepFakeAI/predictor.py

@@ -4,7 +4,7 @@ import opennsfw2
 from PIL import Image
 from keras import Model
 
-from facefusion.typing import Frame
+from DeepFakeAI.typing import Frame
 
 PREDICTOR = None
 THREAD_LOCK = threading.Lock()

DeepFakeAI/processors/frame/core.py

@@ -8,8 +8,8 @@ from types import ModuleType
 from typing import Any, List, Callable
 from tqdm import tqdm
 
-import facefusion.globals
-from facefusion import wording
+import DeepFakeAI.globals
+from DeepFakeAI import wording
 
 FRAME_PROCESSORS_MODULES : List[ModuleType] = []
 FRAME_PROCESSORS_METHODS =\
@@ -28,7 +28,7 @@ FRAME_PROCESSORS_METHODS =\
 
 def load_frame_processor_module(frame_processor : str) -> Any:
 	try:
-		frame_processor_module = importlib.import_module('facefusion.processors.frame.modules.' + frame_processor)
+		frame_processor_module = importlib.import_module('DeepFakeAI.processors.frame.modules.' + frame_processor)
 		for method_name in FRAME_PROCESSORS_METHODS:
 			if not hasattr(frame_processor_module, method_name):
 				raise NotImplementedError
@@ -52,16 +52,16 @@ def get_frame_processors_modules(frame_processors : List[str]) -> List[ModuleTyp
 def clear_frame_processors_modules() -> None:
 	global FRAME_PROCESSORS_MODULES
 
-	for frame_processor_module in get_frame_processors_modules(facefusion.globals.frame_processors):
+	for frame_processor_module in get_frame_processors_modules(DeepFakeAI.globals.frame_processors):
 		frame_processor_module.clear_frame_processor()
 	FRAME_PROCESSORS_MODULES = []
 
 
 def multi_process_frame(source_path : str, temp_frame_paths : List[str], process_frames: Callable[[str, List[str], Any], None], update: Callable[[], None]) -> None:
-	with ThreadPoolExecutor(max_workers = facefusion.globals.execution_thread_count) as executor:
+	with ThreadPoolExecutor(max_workers = DeepFakeAI.globals.execution_thread_count) as executor:
 		futures = []
 		queue = create_queue(temp_frame_paths)
-		queue_per_future = max(len(temp_frame_paths) // facefusion.globals.execution_thread_count * facefusion.globals.execution_queue_count, 1)
+		queue_per_future = max(len(temp_frame_paths) // DeepFakeAI.globals.execution_thread_count * DeepFakeAI.globals.execution_queue_count, 1)
 		while not queue.empty():
 			future = executor.submit(process_frames, source_path, pick_queue(queue, queue_per_future), update)
 			futures.append(future)
@@ -97,17 +97,17 @@ def update_progress(progress : Any = None) -> None:
 	progress.set_postfix(
 	{
 		'memory_usage': '{:.2f}'.format(memory_usage).zfill(5) + 'GB',
-		'execution_providers': facefusion.globals.execution_providers,
-		'execution_thread_count': facefusion.globals.execution_thread_count,
-		'execution_queue_count': facefusion.globals.execution_queue_count
+		'execution_providers': DeepFakeAI.globals.execution_providers,
+		'execution_thread_count': DeepFakeAI.globals.execution_thread_count,
+		'execution_queue_count': DeepFakeAI.globals.execution_queue_count
 	})
 	progress.refresh()
 	progress.update(1)
 
 
 def get_device() -> str:
-	if 'CUDAExecutionProvider' in facefusion.globals.execution_providers:
+	if 'CUDAExecutionProvider' in DeepFakeAI.globals.execution_providers:
 		return 'cuda'
-	if 'CoreMLExecutionProvider' in facefusion.globals.execution_providers:
+	if 'CoreMLExecutionProvider' in DeepFakeAI.globals.execution_providers:
 		return 'mps'
 	return 'cpu'

DeepFakeAI/processors/frame/modules/face_enhancer.py

@@ -3,13 +3,13 @@ import cv2
 import threading
 from gfpgan.utils import GFPGANer
 
-import facefusion.globals
-import facefusion.processors.frame.core as frame_processors
-from facefusion import wording
-from facefusion.core import update_status
-from facefusion.face_analyser import get_many_faces
-from facefusion.typing import Frame, Face
-from facefusion.utilities import conditional_download, resolve_relative_path, is_image, is_video
+import DeepFakeAI.globals
+import DeepFakeAI.processors.frame.core as frame_processors
+from DeepFakeAI import wording
+from DeepFakeAI.core import update_status
+from DeepFakeAI.face_analyser import get_many_faces
+from DeepFakeAI.typing import Frame, Face
+from DeepFakeAI.utilities import conditional_download, resolve_relative_path, is_image, is_video
 
 FRAME_PROCESSOR = None
 THREAD_SEMAPHORE = threading.Semaphore()
@@ -39,12 +39,12 @@ def clear_frame_processor() -> None:
 
 def pre_check() -> bool:
 	download_directory_path = resolve_relative_path('../.assets/models')
-	conditional_download(download_directory_path, ['https://github.com/facefusion/facefusion-assets/releases/download/models/GFPGANv1.4.pth'])
+	conditional_download(download_directory_path, ['https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/models/GFPGANv1.4.pth'])
 	return True
 
 
 def pre_process() -> bool:
-	if not is_image(facefusion.globals.target_path) and not is_video(facefusion.globals.target_path):
+	if not is_image(DeepFakeAI.globals.target_path) and not is_video(DeepFakeAI.globals.target_path):
 		update_status(wording.get('select_image_or_video_target') + wording.get('exclamation_mark'), NAME)
 		return False
 	return True
@@ -97,4 +97,4 @@ def process_image(source_path : str, target_path : str, output_path : str) -> No
 
 
 def process_video(source_path : str, temp_frame_paths : List[str]) -> None:
-	facefusion.processors.frame.core.process_video(None, temp_frame_paths, process_frames)
+	DeepFakeAI.processors.frame.core.process_video(None, temp_frame_paths, process_frames)

DeepFakeAI/processors/frame/modules/face_swapper.py

@@ -3,14 +3,14 @@ import cv2
 import insightface
 import threading
 
-import facefusion.globals
-import facefusion.processors.frame.core as frame_processors
-from facefusion import wording
-from facefusion.core import update_status
-from facefusion.face_analyser import get_one_face, get_many_faces, find_similar_faces
-from facefusion.face_reference import get_face_reference, set_face_reference
-from facefusion.typing import Face, Frame
-from facefusion.utilities import conditional_download, resolve_relative_path, is_image, is_video
+import DeepFakeAI.globals
+import DeepFakeAI.processors.frame.core as frame_processors
+from DeepFakeAI import wording
+from DeepFakeAI.core import update_status
+from DeepFakeAI.face_analyser import get_one_face, get_many_faces, find_similar_faces
+from DeepFakeAI.face_reference import get_face_reference, set_face_reference
+from DeepFakeAI.typing import Face, Frame
+from DeepFakeAI.utilities import conditional_download, resolve_relative_path, is_image, is_video
 
 FRAME_PROCESSOR = None
 THREAD_LOCK = threading.Lock()
@@ -23,7 +23,7 @@ def get_frame_processor() -> Any:
 	with THREAD_LOCK:
 		if FRAME_PROCESSOR is None:
 			model_path = resolve_relative_path('../.assets/models/inswapper_128.onnx')
-			FRAME_PROCESSOR = insightface.model_zoo.get_model(model_path, providers = facefusion.globals.execution_providers)
+			FRAME_PROCESSOR = insightface.model_zoo.get_model(model_path, providers = DeepFakeAI.globals.execution_providers)
 	return FRAME_PROCESSOR
 
 
@@ -35,18 +35,18 @@ def clear_frame_processor() -> None:
 
 def pre_check() -> bool:
 	download_directory_path = resolve_relative_path('../.assets/models')
-	conditional_download(download_directory_path, ['https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx'])
+	conditional_download(download_directory_path, ['https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/models/inswapper_128.onnx'])
 	return True
 
 
 def pre_process() -> bool:
-	if not is_image(facefusion.globals.source_path):
+	if not is_image(DeepFakeAI.globals.source_path):
 		update_status(wording.get('select_image_source') + wording.get('exclamation_mark'), NAME)
 		return False
-	elif not get_one_face(cv2.imread(facefusion.globals.source_path)):
+	elif not get_one_face(cv2.imread(DeepFakeAI.globals.source_path)):
 		update_status(wording.get('no_source_face_detected') + wording.get('exclamation_mark'), NAME)
 		return False
-	if not is_image(facefusion.globals.target_path) and not is_video(facefusion.globals.target_path):
+	if not is_image(DeepFakeAI.globals.target_path) and not is_video(DeepFakeAI.globals.target_path):
 		update_status(wording.get('select_image_or_video_target') + wording.get('exclamation_mark'), NAME)
 		return False
 	return True
@@ -61,12 +61,12 @@ def swap_face(source_face : Face, target_face : Face, temp_frame : Frame) -> Fra
 
 
 def process_frame(source_face : Face, reference_face : Face, temp_frame : Frame) -> Frame:
-	if 'reference' in facefusion.globals.face_recognition:
-		similar_faces = find_similar_faces(temp_frame, reference_face, facefusion.globals.reference_face_distance)
+	if 'reference' in DeepFakeAI.globals.face_recognition:
+		similar_faces = find_similar_faces(temp_frame, reference_face, DeepFakeAI.globals.reference_face_distance)
 		if similar_faces:
 			for similar_face in similar_faces:
 				temp_frame = swap_face(source_face, similar_face, temp_frame)
-	if 'many' in facefusion.globals.face_recognition:
+	if 'many' in DeepFakeAI.globals.face_recognition:
 		many_faces = get_many_faces(temp_frame)
 		if many_faces:
 			for target_face in many_faces:
@@ -76,7 +76,7 @@ def process_frame(source_face : Face, reference_face : Face, temp_frame : Frame)
 
 def process_frames(source_path : str, temp_frame_paths : List[str], update: Callable[[], None]) -> None:
 	source_face = get_one_face(cv2.imread(source_path))
-	reference_face = get_face_reference() if 'reference' in facefusion.globals.face_recognition else None
+	reference_face = get_face_reference() if 'reference' in DeepFakeAI.globals.face_recognition else None
 	for temp_frame_path in temp_frame_paths:
 		temp_frame = cv2.imread(temp_frame_path)
 		result_frame = process_frame(source_face, reference_face, temp_frame)
@@ -88,7 +88,7 @@ def process_frames(source_path : str, temp_frame_paths : List[str], update: Call
 def process_image(source_path : str, target_path : str, output_path : str) -> None:
 	source_face = get_one_face(cv2.imread(source_path))
 	target_frame = cv2.imread(target_path)
-	reference_face = get_one_face(target_frame, facefusion.globals.reference_face_position) if 'reference' in facefusion.globals.face_recognition else None
+	reference_face = get_one_face(target_frame, DeepFakeAI.globals.reference_face_position) if 'reference' in DeepFakeAI.globals.face_recognition else None
 	result_frame = process_frame(source_face, reference_face, target_frame)
 	cv2.imwrite(output_path, result_frame)
 
@@ -99,7 +99,7 @@ def process_video(source_path : str, temp_frame_paths : List[str]) -> None:
 
 
 def conditional_set_face_reference(temp_frame_paths : List[str]) -> None:
-	if 'reference' in facefusion.globals.face_recognition and not get_face_reference():
-		reference_frame = cv2.imread(temp_frame_paths[facefusion.globals.reference_frame_number])
-		reference_face = get_one_face(reference_frame, facefusion.globals.reference_face_position)
+	if 'reference' in DeepFakeAI.globals.face_recognition and not get_face_reference():
+		reference_frame = cv2.imread(temp_frame_paths[DeepFakeAI.globals.reference_frame_number])
+		reference_face = get_one_face(reference_frame, DeepFakeAI.globals.reference_face_position)
 		set_face_reference(reference_face)

DeepFakeAI/processors/frame/modules/frame_enhancer.py

@@ -4,9 +4,9 @@ import threading
 from basicsr.archs.rrdbnet_arch import RRDBNet
 from realesrgan import RealESRGANer
 
-import facefusion.processors.frame.core as frame_processors
-from facefusion.typing import Frame, Face
-from facefusion.utilities import conditional_download, resolve_relative_path
+import DeepFakeAI.processors.frame.core as frame_processors
+from DeepFakeAI.typing import Frame, Face
+from DeepFakeAI.utilities import conditional_download, resolve_relative_path
 
 FRAME_PROCESSOR = None
 THREAD_SEMAPHORE = threading.Semaphore()
@@ -47,7 +47,7 @@ def clear_frame_processor() -> None:
 
 def pre_check() -> bool:
 	download_directory_path = resolve_relative_path('../.assets/models')
-	conditional_download(download_directory_path, ['https://github.com/facefusion/facefusion-assets/releases/download/models/RealESRGAN_x4plus.pth'])
+	conditional_download(download_directory_path, ['https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/models/RealESRGAN_x4plus.pth'])
 	return True
 
 

DeepFakeAI/uis/components/about.py

@@ -1,7 +1,7 @@
 from typing import Optional
 import gradio
 
-from facefusion import metadata
+from DeepFakeAI import metadata
 
 ABOUT_HTML : Optional[gradio.HTML] = None
 

DeepFakeAI/uis/components/benchmark.py

@@ -4,12 +4,12 @@ import tempfile
 import statistics
 import gradio
 
-import facefusion.globals
-from facefusion import wording
-from facefusion.capturer import get_video_frame_total
-from facefusion.core import conditional_process
-from facefusion.uis.typing import Update
-from facefusion.utilities import normalize_output_path, clear_temp
+import DeepFakeAI.globals
+from DeepFakeAI import wording
+from DeepFakeAI.capturer import get_video_frame_total
+from DeepFakeAI.core import conditional_process
+from DeepFakeAI.uis.typing import Update
+from DeepFakeAI.utilities import normalize_output_path, clear_temp
 
 BENCHMARK_RESULT_DATAFRAME : Optional[gradio.Dataframe] = None
 BENCHMARK_CYCLES_SLIDER : Optional[gradio.Button] = None
@@ -65,7 +65,7 @@ def listen() -> None:
 
 
 def update(benchmark_cycles : int) -> Update:
-	facefusion.globals.source_path = '.assets/examples/source.jpg'
+	DeepFakeAI.globals.source_path = '.assets/examples/source.jpg'
 	target_paths =\
 	[
 		'.assets/examples/target-240p.mp4',
@@ -84,9 +84,9 @@ def benchmark(target_path : str, benchmark_cycles : int) -> List[Any]:
 	process_times = []
 	total_fps = 0.0
 	for i in range(benchmark_cycles + 1):
-		facefusion.globals.target_path = target_path
-		facefusion.globals.output_path = normalize_output_path(facefusion.globals.source_path, facefusion.globals.target_path, tempfile.gettempdir())
-		video_frame_total = get_video_frame_total(facefusion.globals.target_path)
+		DeepFakeAI.globals.target_path = target_path
+		DeepFakeAI.globals.output_path = normalize_output_path(DeepFakeAI.globals.source_path, DeepFakeAI.globals.target_path, tempfile.gettempdir())
+		video_frame_total = get_video_frame_total(DeepFakeAI.globals.target_path)
 		start_time = time.perf_counter()
 		conditional_process()
 		end_time = time.perf_counter()
@@ -101,7 +101,7 @@ def benchmark(target_path : str, benchmark_cycles : int) -> List[Any]:
 	relative_fps = round(total_fps / benchmark_cycles, 2)
 	return\
 	[
-		facefusion.globals.target_path,
+		DeepFakeAI.globals.target_path,
 		benchmark_cycles,
 		average_run,
 		fastest_run,
@@ -111,6 +111,6 @@ def benchmark(target_path : str, benchmark_cycles : int) -> List[Any]:
 
 
 def clear() -> Update:
-	if facefusion.globals.target_path:
-		clear_temp(facefusion.globals.target_path)
+	if DeepFakeAI.globals.target_path:
+		clear_temp(DeepFakeAI.globals.target_path)
 	return gradio.update(value = None)

DeepFakeAI/uis/components/execution.py

@@ -2,12 +2,12 @@ from typing import List, Optional
 import gradio
 import onnxruntime
 
-import facefusion.globals
-from facefusion import wording
-from facefusion.face_analyser import clear_face_analyser
-from facefusion.processors.frame.core import clear_frame_processors_modules
-from facefusion.uis.typing import Update
-from facefusion.utilities import encode_execution_providers, decode_execution_providers
+import DeepFakeAI.globals
+from DeepFakeAI import wording
+from DeepFakeAI.face_analyser import clear_face_analyser
+from DeepFakeAI.processors.frame.core import clear_frame_processors_modules
+from DeepFakeAI.uis.typing import Update
+from DeepFakeAI.utilities import encode_execution_providers, decode_execution_providers
 
 EXECUTION_PROVIDERS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
 EXECUTION_THREAD_COUNT_SLIDER : Optional[gradio.Slider] = None
@@ -23,18 +23,18 @@ def render() -> None:
 		EXECUTION_PROVIDERS_CHECKBOX_GROUP = gradio.CheckboxGroup(
 			label = wording.get('execution_providers_checkbox_group_label'),
 			choices = encode_execution_providers(onnxruntime.get_available_providers()),
-			value = encode_execution_providers(facefusion.globals.execution_providers)
+			value = encode_execution_providers(DeepFakeAI.globals.execution_providers)
 		)
 		EXECUTION_THREAD_COUNT_SLIDER = gradio.Slider(
 			label = wording.get('execution_thread_count_slider_label'),
-			value = facefusion.globals.execution_thread_count,
+			value = DeepFakeAI.globals.execution_thread_count,
 			step = 1,
 			minimum = 1,
 			maximum = 128
 		)
 		EXECUTION_QUEUE_COUNT_SLIDER = gradio.Slider(
 			label = wording.get('execution_queue_count_slider_label'),
-			value = facefusion.globals.execution_queue_count,
+			value = DeepFakeAI.globals.execution_queue_count,
 			step = 1,
 			minimum = 1,
 			maximum = 16
@@ -50,15 +50,15 @@ def listen() -> None:
 def update_execution_providers(execution_providers : List[str]) -> Update:
 	clear_face_analyser()
 	clear_frame_processors_modules()
-	facefusion.globals.execution_providers = decode_execution_providers(execution_providers)
+	DeepFakeAI.globals.execution_providers = decode_execution_providers(execution_providers)
 	return gradio.update(value = execution_providers)
 
 
 def update_execution_thread_count(execution_thread_count : int = 1) -> Update:
-	facefusion.globals.execution_thread_count = execution_thread_count
+	DeepFakeAI.globals.execution_thread_count = execution_thread_count
 	return gradio.update(value = execution_thread_count)
 
 
 def update_execution_queue_count(execution_queue_count : int = 1) -> Update:
-	facefusion.globals.execution_queue_count = execution_queue_count
+	DeepFakeAI.globals.execution_queue_count = execution_queue_count
 	return gradio.update(value = execution_queue_count)

DeepFakeAI/uis/components/face_analyser.py

@@ -2,11 +2,11 @@ from typing import Optional
 
 import gradio
 
-import facefusion.choices
-import facefusion.globals
-from facefusion import wording
-from facefusion.uis import core as ui
-from facefusion.uis.typing import Update
+import DeepFakeAI.choices
+import DeepFakeAI.globals
+from DeepFakeAI import wording
+from DeepFakeAI.uis import core as ui
+from DeepFakeAI.uis.typing import Update
 
 FACE_ANALYSER_DIRECTION_DROPDOWN : Optional[gradio.Dropdown] = None
 FACE_ANALYSER_AGE_DROPDOWN : Optional[gradio.Dropdown] = None
@@ -22,18 +22,18 @@ def render() -> None:
 		with gradio.Row():
 			FACE_ANALYSER_DIRECTION_DROPDOWN = gradio.Dropdown(
 				label = wording.get('face_analyser_direction_dropdown_label'),
-				choices = facefusion.choices.face_analyser_direction,
-				value = facefusion.globals.face_analyser_direction
+				choices = DeepFakeAI.choices.face_analyser_direction,
+				value = DeepFakeAI.globals.face_analyser_direction
 			)
 			FACE_ANALYSER_AGE_DROPDOWN = gradio.Dropdown(
 				label = wording.get('face_analyser_age_dropdown_label'),
-				choices = ['none'] + facefusion.choices.face_analyser_age,
-				value = facefusion.globals.face_analyser_age or 'none'
+				choices = ['none'] + DeepFakeAI.choices.face_analyser_age,
+				value = DeepFakeAI.globals.face_analyser_age or 'none'
 			)
 			FACE_ANALYSER_GENDER_DROPDOWN = gradio.Dropdown(
 				label = wording.get('face_analyser_gender_dropdown_label'),
-				choices = ['none'] + facefusion.choices.face_analyser_gender,
-				value = facefusion.globals.face_analyser_gender or 'none'
+				choices = ['none'] + DeepFakeAI.choices.face_analyser_gender,
+				value = DeepFakeAI.globals.face_analyser_gender or 'none'
 			)
 		ui.register_component('face_analyser_direction_dropdown', FACE_ANALYSER_DIRECTION_DROPDOWN)
 		ui.register_component('face_analyser_age_dropdown', FACE_ANALYSER_AGE_DROPDOWN)
@@ -48,7 +48,7 @@ def listen() -> None:
 
 def update_dropdown(name : str, value : str) -> Update:
 	if value == 'none':
-		setattr(facefusion.globals, name, None)
+		setattr(DeepFakeAI.globals, name, None)
 	else:
-		setattr(facefusion.globals, name, value)
+		setattr(DeepFakeAI.globals, name, value)
 	return gradio.update(value = value)