107 lines
3.8 KiB
Python
107 lines
3.8 KiB
Python
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_cycle_count = state_manager.get_item('benchmark_cycle_count')
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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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state_manager.init_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_cycle_count))
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yield benchmarks
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def cycle(cycle_count : 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(cycle_count):
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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 * cycle_count / 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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'cycle_count': cycle_count,
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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_cycle_count',
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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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