Merge pull request #900 from facefusion/vibe/benchmark-command
Benchmark command
This commit is contained in:
Henry Ruhs
@@ -37,6 +37,7 @@ commands:
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headless-run run the program in headless mode
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batch-run run the program in batch mode
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force-download force automate downloads and exit
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benchmark benchmark the program
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job-list list jobs by status
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job-create create a drafted job
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job-submit submit a drafted job to become a queued job
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@@ -110,6 +110,10 @@ execution_queue_count =
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download_providers =
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download_scope =
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[benchmark]
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benchmark_resolutions =
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benchmark_cycles =
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[memory]
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video_memory_strategy =
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system_memory_limit =
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@@ -125,6 +125,9 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
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# download
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apply_state_item('download_providers', args.get('download_providers'))
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apply_state_item('download_scope', args.get('download_scope'))
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# benchmark
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apply_state_item('benchmark_resolutions', args.get('benchmark_resolutions'))
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apply_state_item('benchmark_cycles', args.get('benchmark_cycles'))
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# memory
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apply_state_item('video_memory_strategy', args.get('video_memory_strategy'))
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apply_state_item('system_memory_limit', args.get('system_memory_limit'))
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106
facefusion/benchmarker.py
Normal file
106
facefusion/benchmarker.py
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@@ -0,0 +1,106 @@
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import hashlib
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import os
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import statistics
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import tempfile
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from time import perf_counter
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from typing import Generator, List
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import facefusion.choices
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from facefusion import core, state_manager
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from facefusion.cli_helper import render_table
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from facefusion.download import conditional_download, resolve_download_url
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from facefusion.filesystem import get_file_extension
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from facefusion.types import BenchmarkCycleSet
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from facefusion.vision import count_video_frame_total, detect_video_fps, detect_video_resolution, pack_resolution
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def pre_check() -> bool:
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conditional_download('.assets/examples',
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[
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resolve_download_url('examples-3.0.0', 'source.jpg'),
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resolve_download_url('examples-3.0.0', 'source.mp3'),
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resolve_download_url('examples-3.0.0', 'target-240p.mp4'),
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resolve_download_url('examples-3.0.0', 'target-360p.mp4'),
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resolve_download_url('examples-3.0.0', 'target-540p.mp4'),
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resolve_download_url('examples-3.0.0', 'target-720p.mp4'),
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resolve_download_url('examples-3.0.0', 'target-1080p.mp4'),
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resolve_download_url('examples-3.0.0', 'target-1440p.mp4'),
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resolve_download_url('examples-3.0.0', 'target-2160p.mp4')
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])
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return True
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def run() -> Generator[List[BenchmarkCycleSet], None, None]:
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benchmark_resolutions = state_manager.get_item('benchmark_resolutions')
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benchmark_cycles = state_manager.get_item('benchmark_cycles')
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state_manager.set_item('source_paths', [ '.assets/examples/source.jpg', '.assets/examples/source.mp3' ])
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state_manager.set_item('face_landmarker_score', 0)
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state_manager.set_item('temp_frame_format', 'bmp')
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state_manager.set_item('output_audio_volume', 0)
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state_manager.set_item('output_video_preset', 'ultrafast')
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state_manager.set_item('video_memory_strategy', 'tolerant')
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benchmarks = []
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target_paths = [facefusion.choices.benchmark_set.get(benchmark_resolution) for benchmark_resolution in benchmark_resolutions if benchmark_resolution in facefusion.choices.benchmark_set]
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for target_path in target_paths:
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state_manager.set_item('target_path', target_path)
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state_manager.set_item('output_path', suggest_output_path(state_manager.get_item('target_path')))
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benchmarks.append(cycle(benchmark_cycles))
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yield benchmarks
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def cycle(benchmark_cycles : int) -> BenchmarkCycleSet:
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process_times = []
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video_frame_total = count_video_frame_total(state_manager.get_item('target_path'))
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output_video_resolution = detect_video_resolution(state_manager.get_item('target_path'))
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state_manager.set_item('output_video_resolution', pack_resolution(output_video_resolution))
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state_manager.set_item('output_video_fps', detect_video_fps(state_manager.get_item('target_path')))
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core.conditional_process()
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for index in range(benchmark_cycles):
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start_time = perf_counter()
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core.conditional_process()
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end_time = perf_counter()
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process_times.append(end_time - start_time)
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average_run = round(statistics.mean(process_times), 2)
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fastest_run = round(min(process_times), 2)
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slowest_run = round(max(process_times), 2)
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relative_fps = round(video_frame_total * benchmark_cycles / sum(process_times), 2)
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return\
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{
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'target_path': state_manager.get_item('target_path'),
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'benchmark_cycles': benchmark_cycles,
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'average_run': average_run,
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'fastest_run': fastest_run,
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'slowest_run': slowest_run,
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'relative_fps': relative_fps
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}
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def suggest_output_path(target_path : str) -> str:
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target_file_extension = get_file_extension(target_path)
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return os.path.join(tempfile.gettempdir(), hashlib.sha1().hexdigest()[:8] + target_file_extension)
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def render() -> None:
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benchmarks = []
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headers =\
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[
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'target_path',
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'benchmark_cycles',
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'average_run',
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'fastest_run',
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'slowest_run',
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'relative_fps'
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]
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for benchmark in run():
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benchmarks = benchmark
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contents = [ list(benchmark_set.values()) for benchmark_set in benchmarks ]
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render_table(headers, contents)
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@@ -2,7 +2,7 @@ import logging
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from typing import List, Sequence
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from facefusion.common_helper import create_float_range, create_int_range
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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
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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
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face_detector_set : FaceDetectorSet =\
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{
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@@ -85,6 +85,18 @@ output_video_presets : List[VideoPreset] = [ 'ultrafast', 'superfast', 'veryfast
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image_template_sizes : List[float] = [ 0.25, 0.5, 0.75, 1, 1.5, 2, 2.5, 3, 3.5, 4 ]
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video_template_sizes : List[int] = [ 240, 360, 480, 540, 720, 1080, 1440, 2160, 4320 ]
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benchmark_set : BenchmarkSet =\
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{
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'240p': '.assets/examples/target-240p.mp4',
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'360p': '.assets/examples/target-360p.mp4',
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'540p': '.assets/examples/target-540p.mp4',
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'720p': '.assets/examples/target-720p.mp4',
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'1080p': '.assets/examples/target-1080p.mp4',
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'1440p': '.assets/examples/target-1440p.mp4',
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'2160p': '.assets/examples/target-2160p.mp4'
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}
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benchmark_resolutions : List[BenchmarkResolution] = list(benchmark_set.keys())
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webcam_modes : List[WebcamMode] = [ 'inline', 'udp', 'v4l2' ]
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webcam_resolutions : List[str] = [ '320x240', '640x480', '800x600', '1024x768', '1280x720', '1280x960', '1920x1080', '2560x1440', '3840x2160' ]
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@@ -136,6 +148,7 @@ log_levels : List[LogLevel] = list(log_level_set.keys())
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ui_workflows : List[UiWorkflow] = [ 'instant_runner', 'job_runner', 'job_manager' ]
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job_statuses : List[JobStatus] = [ 'drafted', 'queued', 'completed', 'failed' ]
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benchmark_cycles_range : Sequence[int] = create_int_range(1, 10, 1)
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execution_thread_count_range : Sequence[int] = create_int_range(1, 32, 1)
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execution_queue_count_range : Sequence[int] = create_int_range(1, 4, 1)
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system_memory_limit_range : Sequence[int] = create_int_range(0, 128, 4)
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@@ -6,7 +6,7 @@ from time import time
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import numpy
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from facefusion import cli_helper, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, logger, process_manager, state_manager, video_manager, voice_extractor, wording
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from facefusion import benchmarker, cli_helper, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, logger, process_manager, state_manager, video_manager, voice_extractor, wording
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from facefusion.args import apply_args, collect_job_args, reduce_job_args, reduce_step_args
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from facefusion.common_helper import get_first
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from facefusion.content_analyser import analyse_image, analyse_video
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@@ -59,6 +59,11 @@ def route(args : Args) -> None:
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error_code = force_download()
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return hard_exit(error_code)
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if state_manager.get_item('command') == 'benchmark':
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if not common_pre_check() or not processors_pre_check() or not benchmarker.pre_check():
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return hard_exit(2)
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benchmarker.render()
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if state_manager.get_item('command') in [ 'job-list', 'job-create', 'job-submit', 'job-submit-all', 'job-delete', 'job-delete-all', 'job-add-step', 'job-remix-step', 'job-insert-step', 'job-remove-step' ]:
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if not job_manager.init_jobs(state_manager.get_item('jobs_path')):
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hard_exit(1)
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@@ -214,6 +214,14 @@ def create_download_providers_program() -> ArgumentParser:
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return program
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def create_benchmark_program() -> ArgumentParser:
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program = ArgumentParser(add_help = False)
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group_benchmark = program.add_argument_group('benchmark')
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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 = '+')
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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)
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return program
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def create_download_scope_program() -> ArgumentParser:
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program = ArgumentParser(add_help = False)
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group_download = program.add_argument_group('download')
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@@ -284,6 +292,7 @@ def create_program() -> ArgumentParser:
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sub_program.add_parser('headless-run', help = wording.get('help.headless_run'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), create_source_paths_program(), create_target_path_program(), create_output_path_program(), collect_step_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
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sub_program.add_parser('batch-run', help = wording.get('help.batch_run'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), create_source_pattern_program(), create_target_pattern_program(), create_output_pattern_program(), collect_step_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
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sub_program.add_parser('force-download', help = wording.get('help.force_download'), parents = [ create_download_providers_program(), create_download_scope_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
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sub_program.add_parser('benchmark', help = wording.get('help.benchmark'), parents = [ create_temp_path_program(), create_benchmark_program(), collect_step_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
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# job manager
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sub_program.add_parser('job-list', help = wording.get('help.job_list'), parents = [ create_job_status_program(), create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
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sub_program.add_parser('job-create', help = wording.get('help.job_create'), parents = [ create_job_id_program(), create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
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@@ -130,6 +130,18 @@ EncoderSet = TypedDict('EncoderSet',
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})
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VideoPreset = Literal['ultrafast', 'superfast', 'veryfast', 'faster', 'fast', 'medium', 'slow', 'slower', 'veryslow']
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BenchmarkResolution = Literal['240p', '360p', '540p', '720p', '1080p', '1440p', '2160p']
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BenchmarkSet : TypeAlias = Dict[BenchmarkResolution, str]
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BenchmarkCycleSet = TypedDict('BenchmarkCycleSet',
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{
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'target_path' : str,
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'benchmark_cycles' : int,
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'average_run' : float,
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'fastest_run' : float,
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'slowest_run' : float,
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'relative_fps' : float
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})
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WebcamMode = Literal['inline', 'udp', 'v4l2']
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StreamMode = Literal['udp', 'v4l2']
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@@ -238,6 +250,10 @@ StateKey = Literal\
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'source_pattern',
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'target_pattern',
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'output_pattern',
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'download_providers',
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'download_scope',
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'benchmark_resolutions',
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'benchmark_cycles',
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'face_detector_model',
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'face_detector_size',
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'face_detector_angles',
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@@ -282,8 +298,6 @@ StateKey = Literal\
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'execution_providers',
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'execution_thread_count',
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'execution_queue_count',
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'download_providers',
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'download_scope',
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'video_memory_strategy',
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'system_memory_limit',
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'log_level',
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@@ -304,6 +318,10 @@ State = TypedDict('State',
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'source_pattern' : str,
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'target_pattern' : str,
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'output_pattern' : str,
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'download_providers': List[DownloadProvider],
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'download_scope': DownloadScope,
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'benchmark_resolutions': List[BenchmarkResolution],
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'benchmark_cycles': int,
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'face_detector_model' : FaceDetectorModel,
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'face_detector_size' : str,
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'face_detector_angles' : List[Angle],
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@@ -348,8 +366,6 @@ State = TypedDict('State',
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'execution_providers' : List[ExecutionProvider],
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'execution_thread_count' : int,
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'execution_queue_count' : int,
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'download_providers' : List[DownloadProvider],
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'download_scope' : DownloadScope,
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'video_memory_strategy' : VideoMemoryStrategy,
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'system_memory_limit' : int,
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'log_level' : LogLevel,
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@@ -1,31 +1,13 @@
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import hashlib
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import os
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import statistics
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import tempfile
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from time import perf_counter
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from typing import Any, Dict, Generator, List, Optional
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from typing import Any, Generator, List, Optional
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import gradio
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from facefusion import state_manager, wording
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from facefusion.core import conditional_process
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from facefusion.filesystem import get_file_extension, is_video
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from facefusion.memory import limit_system_memory
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from facefusion import benchmarker, state_manager, wording
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from facefusion.types import BenchmarkResolution
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from facefusion.uis.core import get_ui_component
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from facefusion.vision import count_video_frame_total, detect_video_fps, detect_video_resolution, pack_resolution
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BENCHMARK_BENCHMARKS_DATAFRAME : Optional[gradio.Dataframe] = None
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BENCHMARK_START_BUTTON : Optional[gradio.Button] = None
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BENCHMARKS : Dict[str, str] =\
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{
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'240p': '.assets/examples/target-240p.mp4',
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'360p': '.assets/examples/target-360p.mp4',
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'540p': '.assets/examples/target-540p.mp4',
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'720p': '.assets/examples/target-720p.mp4',
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'1080p': '.assets/examples/target-1080p.mp4',
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'1440p': '.assets/examples/target-1440p.mp4',
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'2160p': '.assets/examples/target-2160p.mp4'
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}
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def render() -> None:
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@@ -61,72 +43,19 @@ def render() -> None:
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def listen() -> None:
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benchmark_runs_checkbox_group = get_ui_component('benchmark_runs_checkbox_group')
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benchmark_resolutions_checkbox_group = get_ui_component('benchmark_resolutions_checkbox_group')
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benchmark_cycles_slider = get_ui_component('benchmark_cycles_slider')
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if benchmark_runs_checkbox_group and benchmark_cycles_slider:
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BENCHMARK_START_BUTTON.click(start, inputs = [ benchmark_runs_checkbox_group, benchmark_cycles_slider ], outputs = BENCHMARK_BENCHMARKS_DATAFRAME)
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if benchmark_resolutions_checkbox_group and benchmark_cycles_slider:
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BENCHMARK_START_BUTTON.click(start, inputs = [ benchmark_resolutions_checkbox_group, benchmark_cycles_slider ], outputs = BENCHMARK_BENCHMARKS_DATAFRAME)
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def suggest_output_path(target_path : str) -> Optional[str]:
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if is_video(target_path):
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target_file_extension = get_file_extension(target_path)
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return os.path.join(tempfile.gettempdir(), hashlib.sha1().hexdigest()[:8] + target_file_extension)
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return None
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def start(benchmark_runs : List[str], benchmark_cycles : int) -> Generator[List[Any], None, None]:
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state_manager.init_item('source_paths', [ '.assets/examples/source.jpg', '.assets/examples/source.mp3' ])
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state_manager.init_item('face_landmarker_score', 0)
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state_manager.init_item('temp_frame_format', 'bmp')
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state_manager.init_item('output_audio_volume', 0)
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state_manager.init_item('output_video_preset', 'ultrafast')
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def start(benchmark_resolutions : List[BenchmarkResolution], benchmark_cycles : int) -> Generator[List[Any], None, None]:
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state_manager.set_item('benchmark_resolutions', benchmark_resolutions)
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state_manager.set_item('benchmark_cycles', benchmark_cycles)
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state_manager.sync_item('execution_providers')
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state_manager.sync_item('execution_thread_count')
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state_manager.sync_item('execution_queue_count')
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state_manager.sync_item('system_memory_limit')
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benchmark_results = []
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target_paths = [ BENCHMARKS[benchmark_run] for benchmark_run in benchmark_runs if benchmark_run in BENCHMARKS ]
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if target_paths:
|
||||
pre_process()
|
||||
for target_path in target_paths:
|
||||
state_manager.init_item('target_path', target_path)
|
||||
state_manager.init_item('output_path', suggest_output_path(state_manager.get_item('target_path')))
|
||||
benchmark_results.append(benchmark(benchmark_cycles))
|
||||
yield benchmark_results
|
||||
|
||||
|
||||
def pre_process() -> None:
|
||||
system_memory_limit = state_manager.get_item('system_memory_limit')
|
||||
if system_memory_limit and system_memory_limit > 0:
|
||||
limit_system_memory(system_memory_limit)
|
||||
|
||||
|
||||
def benchmark(benchmark_cycles : int) -> List[Any]:
|
||||
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'))
|
||||
state_manager.init_item('output_video_resolution', pack_resolution(output_video_resolution))
|
||||
state_manager.init_item('output_video_fps', detect_video_fps(state_manager.get_item('target_path')))
|
||||
|
||||
conditional_process()
|
||||
for index in range(benchmark_cycles):
|
||||
start_time = perf_counter()
|
||||
conditional_process()
|
||||
end_time = perf_counter()
|
||||
process_times.append(end_time - start_time)
|
||||
average_run = round(statistics.mean(process_times), 2)
|
||||
fastest_run = round(min(process_times), 2)
|
||||
slowest_run = round(max(process_times), 2)
|
||||
relative_fps = round(video_frame_total * benchmark_cycles / sum(process_times), 2)
|
||||
|
||||
return\
|
||||
[
|
||||
state_manager.get_item('target_path'),
|
||||
benchmark_cycles,
|
||||
average_run,
|
||||
fastest_run,
|
||||
slowest_run,
|
||||
relative_fps
|
||||
]
|
||||
for benchmark in benchmarker.run():
|
||||
yield [ list(benchmark_set.values()) for benchmark_set in benchmark ]
|
||||
|
||||
@@ -2,29 +2,29 @@ from typing import Optional
|
||||
|
||||
import gradio
|
||||
|
||||
import facefusion.choices
|
||||
from facefusion import wording
|
||||
from facefusion.uis.components.benchmark import BENCHMARKS
|
||||
from facefusion.uis.core import register_ui_component
|
||||
|
||||
BENCHMARK_RUNS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
|
||||
BENCHMARK_RESOLUTIONS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
|
||||
BENCHMARK_CYCLES_SLIDER : Optional[gradio.Button] = None
|
||||
|
||||
|
||||
def render() -> None:
|
||||
global BENCHMARK_RUNS_CHECKBOX_GROUP
|
||||
global BENCHMARK_RESOLUTIONS_CHECKBOX_GROUP
|
||||
global BENCHMARK_CYCLES_SLIDER
|
||||
|
||||
BENCHMARK_RUNS_CHECKBOX_GROUP = gradio.CheckboxGroup(
|
||||
label = wording.get('uis.benchmark_runs_checkbox_group'),
|
||||
choices = list(BENCHMARKS.keys()),
|
||||
value = list(BENCHMARKS.keys())
|
||||
BENCHMARK_RESOLUTIONS_CHECKBOX_GROUP = gradio.CheckboxGroup(
|
||||
label = wording.get('uis.benchmark_resolutions_checkbox_group'),
|
||||
choices = facefusion.choices.benchmark_resolutions,
|
||||
value = facefusion.choices.benchmark_resolutions
|
||||
)
|
||||
BENCHMARK_CYCLES_SLIDER = gradio.Slider(
|
||||
label = wording.get('uis.benchmark_cycles_slider'),
|
||||
value = 5,
|
||||
step = 1,
|
||||
minimum = 1,
|
||||
maximum = 10
|
||||
minimum = min(facefusion.choices.benchmark_cycles_range),
|
||||
maximum = max(facefusion.choices.benchmark_cycles_range)
|
||||
)
|
||||
register_ui_component('benchmark_runs_checkbox_group', BENCHMARK_RUNS_CHECKBOX_GROUP)
|
||||
register_ui_component('benchmark_resolutions_checkbox_group', BENCHMARK_RESOLUTIONS_CHECKBOX_GROUP)
|
||||
register_ui_component('benchmark_cycles_slider', BENCHMARK_CYCLES_SLIDER)
|
||||
|
||||
@@ -1,24 +1,12 @@
|
||||
import gradio
|
||||
|
||||
from facefusion import state_manager
|
||||
from facefusion.download import conditional_download, resolve_download_url
|
||||
from facefusion.benchmarker import pre_check as benchmarker_pre_check
|
||||
from facefusion.uis.components import about, age_modifier_options, benchmark, benchmark_options, deep_swapper_options, download, execution, execution_queue_count, execution_thread_count, expression_restorer_options, face_debugger_options, face_editor_options, face_enhancer_options, face_swapper_options, frame_colorizer_options, frame_enhancer_options, lip_syncer_options, memory, processors
|
||||
|
||||
|
||||
def pre_check() -> bool:
|
||||
conditional_download('.assets/examples',
|
||||
[
|
||||
resolve_download_url('examples-3.0.0', 'source.jpg'),
|
||||
resolve_download_url('examples-3.0.0', 'source.mp3'),
|
||||
resolve_download_url('examples-3.0.0', 'target-240p.mp4'),
|
||||
resolve_download_url('examples-3.0.0', 'target-360p.mp4'),
|
||||
resolve_download_url('examples-3.0.0', 'target-540p.mp4'),
|
||||
resolve_download_url('examples-3.0.0', 'target-720p.mp4'),
|
||||
resolve_download_url('examples-3.0.0', 'target-1080p.mp4'),
|
||||
resolve_download_url('examples-3.0.0', 'target-1440p.mp4'),
|
||||
resolve_download_url('examples-3.0.0', 'target-2160p.mp4')
|
||||
])
|
||||
return True
|
||||
return benchmarker_pre_check()
|
||||
|
||||
|
||||
def render() -> gradio.Blocks:
|
||||
|
||||
@@ -6,7 +6,7 @@ ComponentName = Literal\
|
||||
'age_modifier_direction_slider',
|
||||
'age_modifier_model_dropdown',
|
||||
'benchmark_cycles_slider',
|
||||
'benchmark_runs_checkbox_group',
|
||||
'benchmark_resolutions_checkbox_group',
|
||||
'deep_swapper_model_dropdown',
|
||||
'deep_swapper_morph_slider',
|
||||
'expression_restorer_factor_slider',
|
||||
|
||||
@@ -197,6 +197,9 @@ WORDING : Dict[str, Any] =\
|
||||
# download
|
||||
'download_providers': 'download using different providers (choices: {choices}, ...)',
|
||||
'download_scope': 'specify the download scope',
|
||||
# benchmark
|
||||
'benchmark_resolutions': 'choose the resolution for the benchmarks (choices: {choices}, ...)',
|
||||
'benchmark_cycles': 'specify the number of benchmark cycles',
|
||||
# memory
|
||||
'video_memory_strategy': 'balance fast processing and low VRAM usage',
|
||||
'system_memory_limit': 'limit the available RAM that can be used while processing',
|
||||
@@ -208,6 +211,7 @@ WORDING : Dict[str, Any] =\
|
||||
'headless_run': 'run the program in headless mode',
|
||||
'batch_run': 'run the program in batch mode',
|
||||
'force_download': 'force automate downloads and exit',
|
||||
'benchmark': 'benchmark the program',
|
||||
# jobs
|
||||
'job_id': 'specify the job id',
|
||||
'job_status': 'specify the job status',
|
||||
@@ -241,7 +245,7 @@ WORDING : Dict[str, Any] =\
|
||||
'age_modifier_model_dropdown': 'AGE MODIFIER MODEL',
|
||||
'apply_button': 'APPLY',
|
||||
'benchmark_cycles_slider': 'BENCHMARK CYCLES',
|
||||
'benchmark_runs_checkbox_group': 'BENCHMARK RUNS',
|
||||
'benchmark_resolutions_checkbox_group': 'BENCHMARK RESOLUTIONS',
|
||||
'clear_button': 'CLEAR',
|
||||
'common_options_checkbox_group': 'OPTIONS',
|
||||
'download_providers_checkbox_group': 'DOWNLOAD PROVIDERS',
|
||||
|
||||
Reference in New Issue
Block a user