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import hashlib
import os
import statistics
import tempfile
from time import perf_counter
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 BenchmarkCycleSet
from facefusion.vision import count_video_frame_total, detect_video_fps, detect_video_resolution, pack_resolution
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
def run() -> Generator[List[BenchmarkCycleSet], None, None]:
benchmark_resolutions = state_manager.get_item('benchmark_resolutions')
benchmark_cycle_count = state_manager.get_item('benchmark_cycle_count')
state_manager.init_item('source_paths', [ '.assets/examples/source.jpg', '.assets/examples/source.mp3' ])
state_manager.init_item('face_landmarker_score', 0)
state_manager.init_item('temp_frame_format', 'bmp')
state_manager.init_item('output_audio_volume', 0)
state_manager.init_item('output_video_preset', 'ultrafast')
state_manager.init_item('video_memory_strategy', 'tolerant')
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)
state_manager.set_item('output_path', suggest_output_path(state_manager.get_item('target_path')))
benchmarks.append(cycle(benchmark_cycle_count))
yield benchmarks
def cycle(cycle_count : 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'))
state_manager.set_item('output_video_resolution', pack_resolution(output_video_resolution))
state_manager.set_item('output_video_fps', detect_video_fps(state_manager.get_item('target_path')))
core.conditional_process()
for index in range(cycle_count):
start_time = perf_counter()
core.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 * cycle_count / sum(process_times), 2)
return\
{
'target_path': state_manager.get_item('target_path'),
'cycle_count': cycle_count,
'average_run': average_run,
'fastest_run': fastest_run,
'slowest_run': slowest_run,
'relative_fps': relative_fps
}
def suggest_output_path(target_path : str) -> str:
target_file_extension = get_file_extension(target_path)
return os.path.join(tempfile.gettempdir(), hashlib.sha1().hexdigest()[:8] + target_file_extension)
def render() -> None:
benchmarks = []
headers =\
[
'target_path',
'cycle_count',
'average_run',
'fastest_run',
'slowest_run',
'relative_fps'
]
for benchmark in run():
benchmarks = benchmark
contents = [ list(benchmark_set.values()) for benchmark_set in benchmarks ]
render_table(headers, contents)
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