Finalize choices and types

facefusion/benchmarker.py

@@ -3,26 +3,16 @@ import os
 import statistics
 import tempfile
 from time import perf_counter
-from typing import Dict, Generator, List
+from typing import Generator, List
 
+import facefusion.choices
 from facefusion import core, state_manager
 from facefusion.cli_helper import render_table
 from facefusion.download import conditional_download, resolve_download_url
 from facefusion.filesystem import get_file_extension
-from facefusion.types import BenchmarkSet
+from facefusion.types import BenchmarkCycleSet
 from facefusion.vision import count_video_frame_total, detect_video_fps, detect_video_resolution, pack_resolution
 
-BENCHMARKS : Dict[str, str] =\
-{
-	'240p': '.assets/examples/target-240p.mp4',
-	'360p': '.assets/examples/target-360p.mp4',
-	'540p': '.assets/examples/target-540p.mp4',
-	'720p': '.assets/examples/target-720p.mp4',
-	'1080p': '.assets/examples/target-1080p.mp4',
-	'1440p': '.assets/examples/target-1440p.mp4',
-	'2160p': '.assets/examples/target-2160p.mp4'
-}
-
 
 def pre_check() -> bool:
 	conditional_download('.assets/examples',
@@ -40,7 +30,7 @@ def pre_check() -> bool:
 	return True
 
 
-def run() -> Generator[List[BenchmarkSet], None, None]:
+def run() -> Generator[List[BenchmarkCycleSet], None, None]:
 	benchmark_resolutions = state_manager.get_item('benchmark_resolutions')
 	benchmark_cycles = state_manager.get_item('benchmark_cycles')
 
@@ -52,7 +42,7 @@ def run() -> Generator[List[BenchmarkSet], None, None]:
 	state_manager.set_item('video_memory_strategy', 'tolerant')
 
 	benchmarks = []
-	target_paths = [ BENCHMARKS.get(benchmark_resolution) for benchmark_resolution in benchmark_resolutions if benchmark_resolution in BENCHMARKS ]
+	target_paths = [facefusion.choices.benchmark_set.get(benchmark_resolution) for benchmark_resolution in benchmark_resolutions if benchmark_resolution in facefusion.choices.benchmark_set]
 
 	for target_path in target_paths:
 		state_manager.set_item('target_path', target_path)
@@ -61,7 +51,7 @@ def run() -> Generator[List[BenchmarkSet], None, None]:
 		yield benchmarks
 
 
-def cycle(benchmark_cycles : int) -> BenchmarkSet:
+def cycle(benchmark_cycles : int) -> BenchmarkCycleSet:
 	process_times = []
 	video_frame_total = count_video_frame_total(state_manager.get_item('target_path'))
 	output_video_resolution = detect_video_resolution(state_manager.get_item('target_path'))
@@ -112,4 +102,5 @@ def render() -> None:
 	for benchmark in run():
 		benchmarks = benchmark
 
-	render_table(headers, benchmarks)
+	contents = [ list(benchmark_set.values()) for benchmark_set in benchmarks ]
+	render_table(headers, contents)

facefusion/choices.py

@@ -2,7 +2,7 @@ import logging
 from typing import List, Sequence
 
 from facefusion.common_helper import create_float_range, create_int_range
-from facefusion.types import Angle, AudioEncoder, AudioFormat, AudioTypeSet, DownloadProvider, DownloadProviderSet, DownloadScope, EncoderSet, ExecutionProvider, ExecutionProviderSet, FaceDetectorModel, FaceDetectorSet, FaceLandmarkerModel, FaceMaskArea, FaceMaskAreaSet, FaceMaskRegion, FaceMaskRegionSet, FaceMaskType, FaceOccluderModel, FaceParserModel, FaceSelectorMode, FaceSelectorOrder, Gender, ImageFormat, ImageTypeSet, JobStatus, LogLevel, LogLevelSet, Race, Score, TempFrameFormat, UiWorkflow, VideoEncoder, VideoFormat, VideoMemoryStrategy, VideoPreset, VideoTypeSet, WebcamMode
+from facefusion.types import Angle, AudioEncoder, AudioFormat, AudioTypeSet, BenchmarkResolution, BenchmarkSet, DownloadProvider, DownloadProviderSet, DownloadScope, EncoderSet, ExecutionProvider, ExecutionProviderSet, FaceDetectorModel, FaceDetectorSet, FaceLandmarkerModel, FaceMaskArea, FaceMaskAreaSet, FaceMaskRegion, FaceMaskRegionSet, FaceMaskType, FaceOccluderModel, FaceParserModel, FaceSelectorMode, FaceSelectorOrder, Gender, ImageFormat, ImageTypeSet, JobStatus, LogLevel, LogLevelSet, Race, Score, TempFrameFormat, UiWorkflow, VideoEncoder, VideoFormat, VideoMemoryStrategy, VideoPreset, VideoTypeSet, WebcamMode
 
 face_detector_set : FaceDetectorSet =\
 {
@@ -85,6 +85,18 @@ output_video_presets : List[VideoPreset] = [ 'ultrafast', 'superfast', 'veryfast
 image_template_sizes : List[float] = [ 0.25, 0.5, 0.75, 1, 1.5, 2, 2.5, 3, 3.5, 4 ]
 video_template_sizes : List[int] = [ 240, 360, 480, 540, 720, 1080, 1440, 2160, 4320 ]
 
+benchmark_set : BenchmarkSet =\
+{
+	'240p': '.assets/examples/target-240p.mp4',
+	'360p': '.assets/examples/target-360p.mp4',
+	'540p': '.assets/examples/target-540p.mp4',
+	'720p': '.assets/examples/target-720p.mp4',
+	'1080p': '.assets/examples/target-1080p.mp4',
+	'1440p': '.assets/examples/target-1440p.mp4',
+	'2160p': '.assets/examples/target-2160p.mp4'
+}
+benchmark_resolutions : List[BenchmarkResolution] = list(benchmark_set.keys())
+
 webcam_modes : List[WebcamMode] = [ 'inline', 'udp', 'v4l2' ]
 webcam_resolutions : List[str] = [ '320x240', '640x480', '800x600', '1024x768', '1280x720', '1280x960', '1920x1080', '2560x1440', '3840x2160' ]
 
@@ -136,6 +148,7 @@ log_levels : List[LogLevel] = list(log_level_set.keys())
 ui_workflows : List[UiWorkflow] = [ 'instant_runner', 'job_runner', 'job_manager' ]
 job_statuses : List[JobStatus] = [ 'drafted', 'queued', 'completed', 'failed' ]
 
+benchmark_cycles_range : Sequence[int] = create_int_range(1, 10, 1)
 execution_thread_count_range : Sequence[int] = create_int_range(1, 32, 1)
 execution_queue_count_range : Sequence[int] = create_int_range(1, 4, 1)
 system_memory_limit_range : Sequence[int] = create_int_range(0, 128, 4)

facefusion/program.py

@@ -215,11 +215,10 @@ def create_download_providers_program() -> ArgumentParser:
 
 
 def create_benchmark_program() -> ArgumentParser:
-	from facefusion.benchmarker import BENCHMARKS
 	program = ArgumentParser(add_help = False)
 	group_benchmark = program.add_argument_group('benchmark')
-	group_benchmark.add_argument('--benchmark-resolutions', help = wording.get('help.benchmark_resolutions'), default = config.get_str_list('benchmark', 'benchmark_resolutions', '240p'), choices = list(BENCHMARKS.keys()), nargs = '+')
+	group_benchmark.add_argument('--benchmark-resolutions', help = wording.get('help.benchmark_resolutions'), default = config.get_str_list('benchmark', 'benchmark_resolutions', get_first(facefusion.choices.benchmark_resolutions)), choices = facefusion.choices.benchmark_resolutions, nargs = '+')
-	group_benchmark.add_argument('--benchmark-cycles', help = wording.get('help.benchmark_cycles'), type = int, default = config.get_int_value('benchmark', 'benchmark_cycles', '5'), choices = range(1, 11))
+	group_benchmark.add_argument('--benchmark-cycles', help = wording.get('help.benchmark_cycles'), type = int, default = config.get_int_value('benchmark', 'benchmark_cycles', '5'), choices = facefusion.choices.benchmark_cycles_range)
 	return program
 
 

facefusion/types.py

@@ -100,16 +100,6 @@ LogLevelSet : TypeAlias = Dict[LogLevel, int]
 TableHeaders = List[str]
 TableContents = List[List[Any]]
 
-BenchmarkSet = TypedDict('BenchmarkSet',
-{
-	'target_path' : str,
-	'benchmark_cycles' : int,
-	'average_run' : float,
-	'fastest_run' : float,
-	'slowest_run' : float,
-	'relative_fps' : float
-})
-
 FaceDetectorModel = Literal['many', 'retinaface', 'scrfd', 'yolo_face']
 FaceLandmarkerModel = Literal['many', '2dfan4', 'peppa_wutz']
 FaceDetectorSet : TypeAlias = Dict[FaceDetectorModel, List[str]]
@@ -140,6 +130,18 @@ EncoderSet = TypedDict('EncoderSet',
 })
 VideoPreset = Literal['ultrafast', 'superfast', 'veryfast', 'faster', 'fast', 'medium', 'slow', 'slower', 'veryslow']
 
+BenchmarkResolution = Literal['240p', '360p', '540p', '720p', '1080p', '1440p', '2160p']
+BenchmarkSet : TypeAlias = Dict[BenchmarkResolution, str]
+BenchmarkCycleSet = TypedDict('BenchmarkCycleSet',
+{
+	'target_path' : str,
+	'benchmark_cycles' : int,
+	'average_run' : float,
+	'fastest_run' : float,
+	'slowest_run' : float,
+	'relative_fps' : float
+})
+
 WebcamMode = Literal['inline', 'udp', 'v4l2']
 StreamMode = Literal['udp', 'v4l2']