3.5.1 (#985)

* Fix type for device id

* Fix type for device id

* Fix order

* Remove comma

* Replace Generator typing

* Replace Generator typing

* Conditional kill myself (#984)

* Introduce conditional remove mask

* fix

---------

Co-authored-by: harisreedhar <h4harisreedhar.s.s@gmail.com>

---------

Co-authored-by: harisreedhar <h4harisreedhar.s.s@gmail.com>

facefusion/benchmarker.py

@@ -3,7 +3,7 @@ import os
 import statistics
 import tempfile
 from time import perf_counter
-from typing import Generator, List
+from typing import Iterator, List
 
 import facefusion.choices
 from facefusion import content_analyser, core, state_manager
@@ -31,7 +31,7 @@ def pre_check() -> bool:
 	return True
 
 
-def run() -> Generator[List[BenchmarkCycleSet], None, None]:
+def run() -> Iterator[List[BenchmarkCycleSet]]:
 	benchmark_resolutions = state_manager.get_item('benchmark_resolutions')
 	benchmark_cycle_count = state_manager.get_item('benchmark_cycle_count')
 

facefusion/execution.py

@@ -28,7 +28,7 @@ def get_available_execution_providers() -> List[ExecutionProvider]:
 	return available_execution_providers
 
 
-def create_inference_session_providers(execution_device_id : str, execution_providers : List[ExecutionProvider]) -> List[InferenceSessionProvider]:
+def create_inference_session_providers(execution_device_id : int, execution_providers : List[ExecutionProvider]) -> List[InferenceSessionProvider]:
 	inference_session_providers : List[InferenceSessionProvider] = []
 
 	for execution_provider in execution_providers:
@@ -89,10 +89,10 @@ def resolve_cudnn_conv_algo_search() -> str:
 	return 'EXHAUSTIVE'
 
 
-def resolve_openvino_device_type(execution_device_id : str) -> str:
+def resolve_openvino_device_type(execution_device_id : int) -> str:
-	if execution_device_id == '0':
+	if execution_device_id == 0:
 		return 'GPU'
-	return 'GPU.' + execution_device_id
+	return 'GPU.' + str(execution_device_id)
 
 
 def run_nvidia_smi() -> subprocess.Popen[bytes]:

facefusion/inference_manager.py

@@ -42,7 +42,7 @@ def get_inference_pool(module_name : str, model_names : List[str], model_source_
 	return INFERENCE_POOL_SET.get(app_context).get(current_inference_context)
 
 
-def create_inference_pool(model_source_set : DownloadSet, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferencePool:
+def create_inference_pool(model_source_set : DownloadSet, execution_device_id : int, execution_providers : List[ExecutionProvider]) -> InferencePool:
 	inference_pool : InferencePool = {}
 
 	for model_name in model_source_set.keys():
@@ -67,7 +67,7 @@ def clear_inference_pool(module_name : str, model_names : List[str]) -> None:
 			del INFERENCE_POOL_SET[app_context][inference_context]
 
 
-def create_inference_session(model_path : str, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferenceSession:
+def create_inference_session(model_path : str, execution_device_id : int, execution_providers : List[ExecutionProvider]) -> InferenceSession:
 	model_file_name = get_file_name(model_path)
 	start_time = time()
 
@@ -82,8 +82,8 @@ def create_inference_session(model_path : str, execution_device_id : str, execut
 		fatal_exit(1)
 
 
-def get_inference_context(module_name : str, model_names : List[str], execution_device_id : str, execution_providers : List[ExecutionProvider]) -> str:
+def get_inference_context(module_name : str, model_names : List[str], execution_device_id : int, execution_providers : List[ExecutionProvider]) -> str:
-	inference_context = '.'.join([ module_name ] + model_names + [ execution_device_id ] + list(execution_providers))
+	inference_context = '.'.join([ module_name ] + model_names + [ str(execution_device_id) ] + list(execution_providers))
 	return inference_context
 
 

facefusion/metadata.py

@@ -4,7 +4,7 @@ METADATA =\
 {
 	'name': 'FaceFusion',
 	'description': 'Industry leading face manipulation platform',
-	'version': '3.5.0',
+	'version': '3.5.1',
 	'license': 'OpenRAIL-AS',
 	'author': 'Henry Ruhs',
 	'url': 'https://facefusion.io'

facefusion/program.py

@@ -234,7 +234,7 @@ def create_execution_program() -> ArgumentParser:
 	program = ArgumentParser(add_help = False)
 	available_execution_providers = get_available_execution_providers()
 	group_execution = program.add_argument_group('execution')
-	group_execution.add_argument('--execution-device-ids', help = translator.get('help.execution_device_ids'), type = int, default = config.get_str_list('execution', 'execution_device_ids', '0'), nargs = '+', metavar = 'EXECUTION_DEVICE_IDS')
+	group_execution.add_argument('--execution-device-ids', help = translator.get('help.execution_device_ids'), type = int, default = config.get_int_list('execution', 'execution_device_ids', '0'), nargs = '+', metavar = 'EXECUTION_DEVICE_IDS')
 	group_execution.add_argument('--execution-providers', help = translator.get('help.execution_providers').format(choices = ', '.join(available_execution_providers)), default = config.get_str_list('execution', 'execution_providers', get_first(available_execution_providers)), choices = available_execution_providers, nargs = '+', metavar = 'EXECUTION_PROVIDERS')
 	group_execution.add_argument('--execution-thread-count', help = translator.get('help.execution_thread_count'), type = int, default = config.get_int_value('execution', 'execution_thread_count', '8'), choices = facefusion.choices.execution_thread_count_range, metavar = create_int_metavar(facefusion.choices.execution_thread_count_range))
 	job_store.register_job_keys([ 'execution_device_ids', 'execution_providers', 'execution_thread_count' ])

facefusion/streamer.py

@@ -2,7 +2,7 @@ import os
 import subprocess
 from collections import deque
 from concurrent.futures import ThreadPoolExecutor
-from typing import Deque, Generator
+from typing import Deque, Iterator
 
 import cv2
 import numpy
@@ -18,7 +18,7 @@ from facefusion.types import Fps, StreamMode, VisionFrame
 from facefusion.vision import extract_vision_mask, read_static_images
 
 
-def multi_process_capture(camera_capture : cv2.VideoCapture, camera_fps : Fps) -> Generator[VisionFrame, None, None]:
+def multi_process_capture(camera_capture : cv2.VideoCapture, camera_fps : Fps) -> Iterator[VisionFrame]:
 	capture_deque : Deque[VisionFrame] = deque()
 
 	with tqdm(desc = translator.get('streaming'), unit = 'frame', disable = state_manager.get_item('log_level') in [ 'warn', 'error' ]) as progress:

facefusion/types.py

@@ -385,7 +385,7 @@ State = TypedDict('State',
 	'open_browser' : bool,
 	'ui_layouts' : List[str],
 	'ui_workflow' : UiWorkflow,
-	'execution_device_ids' : List[str],
+	'execution_device_ids' : List[int],
 	'execution_providers' : List[ExecutionProvider],
 	'execution_thread_count' : int,
 	'video_memory_strategy' : VideoMemoryStrategy,

facefusion/uis/components/benchmark.py

@@ -1,4 +1,4 @@
-from typing import Any, Generator, List, Optional
+from typing import Any, Iterator, List, Optional
 
 import gradio
 
@@ -44,7 +44,7 @@ def listen() -> None:
 	BENCHMARK_START_BUTTON.click(start, outputs = BENCHMARK_BENCHMARKS_DATAFRAME)
 
 
-def start() -> Generator[List[Any], None, None]:
+def start() -> Iterator[List[Any]]:
 	state_manager.sync_state()
 
 	for benchmark in benchmarker.run():

facefusion/uis/components/preview.py

@@ -18,7 +18,7 @@ from facefusion.types import AudioFrame, Face, Mask, VisionFrame
 from facefusion.uis import choices as uis_choices
 from facefusion.uis.core import get_ui_component, get_ui_components, register_ui_component
 from facefusion.uis.types import ComponentOptions, PreviewMode
-from facefusion.vision import conditional_merge_vision_mask, detect_frame_orientation, extract_vision_mask, fit_cover_frame, obscure_frame, read_static_image, read_static_images, read_video_frame, restrict_frame, unpack_resolution
+from facefusion.vision import detect_frame_orientation, extract_vision_mask, fit_cover_frame, merge_vision_mask, obscure_frame, read_static_image, read_static_images, read_video_frame, restrict_frame, unpack_resolution
 
 PREVIEW_IMAGE : Optional[gradio.Image] = None
 
@@ -197,7 +197,7 @@ def update_preview_image(preview_mode : PreviewMode, preview_resolution : str, f
 		reference_vision_frame = read_static_image(state_manager.get_item('target_path'))
 		target_vision_frame = read_static_image(state_manager.get_item('target_path'), 'rgba')
 		target_vision_mask = extract_vision_mask(target_vision_frame)
-		target_vision_frame = conditional_merge_vision_mask(target_vision_frame, target_vision_mask)
+		target_vision_frame = merge_vision_mask(target_vision_frame, target_vision_mask)
 		preview_vision_frame = process_preview_frame(reference_vision_frame, source_vision_frames, source_audio_frame, source_voice_frame, target_vision_frame, preview_mode, preview_resolution)
 		preview_vision_frame = cv2.cvtColor(preview_vision_frame, cv2.COLOR_BGRA2RGBA)
 		return gradio.Image(value = preview_vision_frame, elem_classes = [ 'image-preview', 'is-' + detect_frame_orientation(preview_vision_frame) ])
@@ -206,7 +206,7 @@ def update_preview_image(preview_mode : PreviewMode, preview_resolution : str, f
 		reference_vision_frame = read_video_frame(state_manager.get_item('target_path'), state_manager.get_item('reference_frame_number'))
 		temp_vision_frame = read_video_frame(state_manager.get_item('target_path'), frame_number)
 		temp_vision_mask = extract_vision_mask(temp_vision_frame)
-		temp_vision_frame = conditional_merge_vision_mask(temp_vision_frame, temp_vision_mask)
+		temp_vision_frame = merge_vision_mask(temp_vision_frame, temp_vision_mask)
 		preview_vision_frame = process_preview_frame(reference_vision_frame, source_vision_frames, source_audio_frame, source_voice_frame, temp_vision_frame, preview_mode, preview_resolution)
 		preview_vision_frame = cv2.cvtColor(preview_vision_frame, cv2.COLOR_BGRA2RGBA)
 		return gradio.Image(value = preview_vision_frame, elem_classes = [ 'image-preview', 'is-' + detect_frame_orientation(preview_vision_frame) ])
@@ -297,6 +297,6 @@ 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_frame = conditional_merge_vision_mask(temp_vision_frame, temp_vision_mask)
+	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

@@ -1,4 +1,4 @@
-from typing import Generator, List, Optional, Tuple
+from typing import Iterator, List, Optional, Tuple
 
 import cv2
 import gradio
@@ -82,7 +82,7 @@ def pre_stop() -> Tuple[gradio.File, gradio.Image, gradio.Button, gradio.Button]
 	return gradio.File(visible = True), gradio.Image(visible = False), gradio.Button(visible = True), gradio.Button(visible = False)
 
 
-def start(webcam_device_id : int, webcam_mode : WebcamMode, webcam_resolution : str, webcam_fps : Fps) -> Generator[VisionFrame, None, None]:
+def start(webcam_device_id : int, webcam_mode : WebcamMode, webcam_resolution : str, webcam_fps : Fps) -> Iterator[VisionFrame]:
 	state_manager.init_item('face_selector_mode', 'one')
 	state_manager.sync_state()
 

facefusion/vision.py

@@ -355,7 +355,11 @@ def extract_vision_mask(vision_frame : VisionFrame) -> Mask:
 	return numpy.full(vision_frame.shape[:2], 255, dtype = numpy.uint8)
 
 
+def merge_vision_mask(vision_frame : VisionFrame, vision_mask : Mask) -> VisionFrame:
+	return numpy.dstack((vision_frame[:, :, :3], vision_mask))
+
+
 def conditional_merge_vision_mask(vision_frame : VisionFrame, vision_mask : Mask) -> VisionFrame:
 	if numpy.any(vision_mask < 255):
-		return numpy.dstack((vision_frame[:, :, :3], vision_mask))
+		return merge_vision_mask(vision_frame, vision_mask)
 	return vision_frame

facefusion/workflows/image_to_image.py

@@ -19,7 +19,7 @@ def process(start_time : float) -> ErrorCode:
 		setup,
 		prepare_image,
 		process_image,
-		partial(finalize_image, start_time),
+		partial(finalize_image, start_time)
 	]
 	process_manager.start()
 

facefusion/workflows/image_to_video.py

@@ -152,18 +152,6 @@ def restore_audio() -> ErrorCode:
 	return 0
 
 
-def finalize_video(start_time : float) -> ErrorCode:
-	logger.debug(translator.get('clearing_temp'), __name__)
-	clear_temp_directory(state_manager.get_item('target_path'))
-
-	if is_video(state_manager.get_item('output_path')):
-		logger.info(translator.get('processing_video_succeeded').format(seconds = calculate_end_time(start_time)), __name__)
-	else:
-		logger.error(translator.get('processing_video_failed'), __name__)
-		return 1
-	return 0
-
-
 def process_temp_frame(temp_frame_path : str, frame_number : int) -> bool:
 	reference_vision_frame = read_static_video_frame(state_manager.get_item('target_path'), state_manager.get_item('reference_frame_number'))
 	source_vision_frames = read_static_images(state_manager.get_item('source_paths'))
@@ -195,3 +183,15 @@ def process_temp_frame(temp_frame_path : str, frame_number : int) -> bool:
 
 	temp_vision_frame = conditional_merge_vision_mask(temp_vision_frame, temp_vision_mask)
 	return write_image(temp_frame_path, temp_vision_frame)
+
+
+def finalize_video(start_time : float) -> ErrorCode:
+	logger.debug(translator.get('clearing_temp'), __name__)
+	clear_temp_directory(state_manager.get_item('target_path'))
+
+	if is_video(state_manager.get_item('output_path')):
+		logger.info(translator.get('processing_video_succeeded').format(seconds = calculate_end_time(start_time)), __name__)
+	else:
+		logger.error(translator.get('processing_video_failed'), __name__)
+		return 1
+	return 0

tests/test_execution.py

@@ -15,10 +15,10 @@ def test_create_inference_session_providers() -> None:
 	[
 		('CUDAExecutionProvider',
 		{
-			'device_id': '1',
+			'device_id': 1,
 			'cudnn_conv_algo_search': 'EXHAUSTIVE'
 		}),
 		'CPUExecutionProvider'
 	]
 
-	assert create_inference_session_providers('1', [ 'cpu', 'cuda' ]) == inference_session_providers
+	assert create_inference_session_providers(1, [ 'cpu', 'cuda' ]) == inference_session_providers

tests/test_face_analyser.py

@@ -18,7 +18,7 @@ def before_all() -> None:
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('source.jpg'), '-vf', 'crop=iw*0.8:ih*0.8', get_test_example_file('source-80crop.jpg') ])
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('source.jpg'), '-vf', 'crop=iw*0.7:ih*0.7', get_test_example_file('source-70crop.jpg') ])
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('source.jpg'), '-vf', 'crop=iw*0.6:ih*0.6', get_test_example_file('source-60crop.jpg') ])
-	state_manager.init_item('execution_device_ids', [ '0' ])
+	state_manager.init_item('execution_device_ids', [ 0 ])
 	state_manager.init_item('execution_providers', [ 'cpu' ])
 	state_manager.init_item('download_providers', [ 'github' ])
 	state_manager.init_item('face_detector_angles', [ 0 ])

tests/test_inference_manager.py

@@ -9,7 +9,7 @@ from facefusion.inference_manager import INFERENCE_POOL_SET, get_inference_pool
 
 @pytest.fixture(scope = 'module', autouse = True)
 def before_all() -> None:
-	state_manager.init_item('execution_device_ids', [ '0' ])
+	state_manager.init_item('execution_device_ids', [ 0 ])
 	state_manager.init_item('execution_providers', [ 'cpu' ])
 	state_manager.init_item('download_providers', [ 'github' ])
 	content_analyser.pre_check()