Simplify conditional_thread_semaphore

facefusion/content_analyser.py

@@ -72,7 +72,7 @@ def analyse_frame(vision_frame : VisionFrame) -> bool:
 	content_analyser = get_content_analyser()
 	vision_frame = prepare_frame(vision_frame)
 
-	with conditional_thread_semaphore(facefusion.globals.execution_providers):
+	with conditional_thread_semaphore():
 		probability = content_analyser.run(None,
 		{
 			content_analyser.get_inputs()[0].name: vision_frame

facefusion/face_analyser.py

@@ -379,7 +379,7 @@ def calc_embedding(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandma
 	crop_vision_frame = crop_vision_frame[:, :, ::-1].transpose(2, 0, 1).astype(numpy.float32)
 	crop_vision_frame = numpy.expand_dims(crop_vision_frame, axis = 0)
 
-	with conditional_thread_semaphore(facefusion.globals.execution_providers):
+	with conditional_thread_semaphore():
 		embedding = face_recognizer.run(None,
 		{
 			face_recognizer.get_inputs()[0].name: crop_vision_frame
@@ -400,7 +400,7 @@ def detect_face_landmark_68(temp_vision_frame : VisionFrame, bounding_box : Boun
 	crop_vision_frame = cv2.cvtColor(crop_vision_frame, cv2.COLOR_Lab2RGB)
 	crop_vision_frame = crop_vision_frame.transpose(2, 0, 1).astype(numpy.float32) / 255.0
 
-	with conditional_thread_semaphore(facefusion.globals.execution_providers):
+	with conditional_thread_semaphore():
 		face_landmark_68, face_heatmap = face_landmarker.run(None,
 		{
 			face_landmarker.get_inputs()[0].name: [ crop_vision_frame ]
@@ -419,7 +419,7 @@ def expand_face_landmark_68_from_5(face_landmark_5 : FaceLandmark5) -> FaceLandm
 	affine_matrix = estimate_matrix_by_face_landmark_5(face_landmark_5, 'ffhq_512', (1, 1))
 	face_landmark_5 = cv2.transform(face_landmark_5.reshape(1, -1, 2), affine_matrix).reshape(-1, 2)
 
-	with conditional_thread_semaphore(facefusion.globals.execution_providers):
+	with conditional_thread_semaphore():
 		face_landmark_68_5 = face_landmarker.run(None,
 		{
 			face_landmarker.get_inputs()[0].name: [ face_landmark_5 ]
@@ -437,7 +437,7 @@ def detect_gender_age(temp_vision_frame : VisionFrame, bounding_box : BoundingBo
 	crop_vision_frame = crop_vision_frame[:, :, ::-1].transpose(2, 0, 1).astype(numpy.float32)
 	crop_vision_frame = numpy.expand_dims(crop_vision_frame, axis = 0)
 
-	with conditional_thread_semaphore(facefusion.globals.execution_providers):
+	with conditional_thread_semaphore():
 		prediction = gender_age.run(None,
 		{
 			gender_age.get_inputs()[0].name: crop_vision_frame

facefusion/face_masker.py

@@ -120,7 +120,7 @@ def create_occlusion_mask(crop_vision_frame : VisionFrame) -> Mask:
 	prepare_vision_frame = numpy.expand_dims(prepare_vision_frame, axis = 0).astype(numpy.float32) / 255
 	prepare_vision_frame = prepare_vision_frame.transpose(0, 1, 2, 3)
 
-	with conditional_thread_semaphore(facefusion.globals.execution_providers):
+	with conditional_thread_semaphore():
 		occlusion_mask : Mask = face_occluder.run(None,
 		{
 			face_occluder.get_inputs()[0].name: prepare_vision_frame
@@ -137,7 +137,7 @@ def create_region_mask(crop_vision_frame : VisionFrame, face_mask_regions : List
 	prepare_vision_frame = numpy.expand_dims(prepare_vision_frame, axis = 0).astype(numpy.float32)[:, :, ::-1] / 127.5 - 1
 	prepare_vision_frame = prepare_vision_frame.transpose(0, 3, 1, 2)
 
-	with conditional_thread_semaphore(facefusion.globals.execution_providers):
+	with conditional_thread_semaphore():
 		region_mask : Mask = face_parser.run(None,
 		{
 			face_parser.get_inputs()[0].name: prepare_vision_frame

facefusion/processors/frame/modules/face_swapper.py

@@ -275,7 +275,7 @@ def apply_swap(source_face : Face, crop_vision_frame : VisionFrame) -> VisionFra
 		if frame_processor_input.name == 'target':
 			frame_processor_inputs[frame_processor_input.name] = crop_vision_frame
 
-	with conditional_thread_semaphore(facefusion.globals.execution_providers):
+	with conditional_thread_semaphore():
 		crop_vision_frame = frame_processor.run(None, frame_processor_inputs)[0][0]
 	return crop_vision_frame
 

facefusion/processors/frame/modules/frame_colorizer.py

@@ -155,6 +155,7 @@ def post_process() -> None:
 def colorize_frame(temp_vision_frame : VisionFrame) -> VisionFrame:
 	frame_processor = get_frame_processor()
 	prepare_vision_frame = prepare_temp_frame(temp_vision_frame)
+
 	with thread_semaphore():
 		color_vision_frame = frame_processor.run(None,
 		{

facefusion/processors/frame/modules/frame_enhancer.py

@@ -198,7 +198,7 @@ def enhance_frame(temp_vision_frame : VisionFrame) -> VisionFrame:
 	tile_vision_frames, pad_width, pad_height = create_tile_frames(temp_vision_frame, size)
 
 	for index, tile_vision_frame in enumerate(tile_vision_frames):
-		with conditional_thread_semaphore(facefusion.globals.execution_providers):
+		with conditional_thread_semaphore():
 			tile_vision_frame = frame_processor.run(None,
 			{
 				frame_processor.get_inputs()[0].name : prepare_tile_frame(tile_vision_frame)

facefusion/processors/frame/modules/lip_syncer.py

@@ -157,7 +157,7 @@ def sync_lip(target_face : Face, temp_audio_frame : AudioFrame, temp_vision_fram
 	close_vision_frame, close_matrix = warp_face_by_bounding_box(crop_vision_frame, bounding_box, (96, 96))
 	close_vision_frame = prepare_crop_frame(close_vision_frame)
 
-	with conditional_thread_semaphore(facefusion.globals.execution_providers):
+	with conditional_thread_semaphore():
 		close_vision_frame = frame_processor.run(None,
 		{
 			'source': temp_audio_frame,

facefusion/thread_helper.py

@@ -1,7 +1,9 @@
-from typing import List, Union, ContextManager
+from typing import Union, ContextManager
 import threading
 from contextlib import nullcontext
 
+from facefusion.execution import has_execution_provider
+
 THREAD_LOCK : threading.Lock = threading.Lock()
 THREAD_SEMAPHORE : threading.Semaphore = threading.Semaphore()
 NULL_CONTEXT : ContextManager[None] = nullcontext()
@@ -15,7 +17,7 @@ def thread_semaphore() -> threading.Semaphore:
 	return THREAD_SEMAPHORE
 
 
-def conditional_thread_semaphore(execution_providers : List[str]) -> Union[threading.Semaphore, ContextManager[None]]:
-	if 'DmlExecutionProvider' in execution_providers:
+def conditional_thread_semaphore() -> Union[threading.Semaphore, ContextManager[None]]:
+	if has_execution_provider('DmlExecutionProvider'):
 		return THREAD_SEMAPHORE
 	return NULL_CONTEXT

facefusion/voice_extractor.py

@@ -71,6 +71,7 @@ def extract_voice(temp_audio_chunk : AudioChunk) -> AudioChunk:
 	trim_size = 3840
 	temp_audio_chunk, pad_size = prepare_audio_chunk(temp_audio_chunk.T, chunk_size, trim_size)
 	temp_audio_chunk = decompose_audio_chunk(temp_audio_chunk, trim_size)
+
 	with thread_semaphore():
 		temp_audio_chunk = voice_extractor.run(None,
 		{