vnyash
141 lines
4.6 KiB
Python
141 lines
4.6 KiB
Python
from typing import Any, Optional, List, Dict, Generator
|
|
from time import sleep, perf_counter
|
|
import tempfile
|
|
import statistics
|
|
import gradio
|
|
|
|
import deepfuze.globals
|
|
from deepfuze import process_manager, wording
|
|
from deepfuze.face_store import clear_static_faces
|
|
from deepfuze.processors.frame.core import get_frame_processors_modules
|
|
from deepfuze.vision import count_video_frame_total, detect_video_resolution, detect_video_fps, pack_resolution
|
|
from deepfuze.core import conditional_process
|
|
from deepfuze.memory import limit_system_memory
|
|
from deepfuze.filesystem import clear_temp
|
|
from deepfuze.uis.core import get_ui_component
|
|
|
|
BENCHMARK_RESULTS_DATAFRAME : Optional[gradio.Dataframe] = None
|
|
BENCHMARK_START_BUTTON : Optional[gradio.Button] = None
|
|
BENCHMARK_CLEAR_BUTTON : Optional[gradio.Button] = None
|
|
BENCHMARKS : Dict[str, str] =\
|
|
{
|
|
'240p': '../../models/facefusion/examples/target-240p.mp4',
|
|
'360p': '../../models/facefusion/examples/target-360p.mp4',
|
|
'540p': '../../models/facefusion/examples/target-540p.mp4',
|
|
'720p': '../../models/facefusion/examples/target-720p.mp4',
|
|
'1080p': '../../models/facefusion/examples/target-1080p.mp4',
|
|
'1440p': '../../models/facefusion/examples/target-1440p.mp4',
|
|
'2160p': '../../models/facefusion/examples/target-2160p.mp4'
|
|
}
|
|
|
|
|
|
def render() -> None:
|
|
global BENCHMARK_RESULTS_DATAFRAME
|
|
global BENCHMARK_START_BUTTON
|
|
global BENCHMARK_CLEAR_BUTTON
|
|
|
|
BENCHMARK_RESULTS_DATAFRAME = gradio.Dataframe(
|
|
label = wording.get('uis.benchmark_results_dataframe'),
|
|
headers =
|
|
[
|
|
'target_path',
|
|
'benchmark_cycles',
|
|
'average_run',
|
|
'fastest_run',
|
|
'slowest_run',
|
|
'relative_fps'
|
|
],
|
|
datatype =
|
|
[
|
|
'str',
|
|
'number',
|
|
'number',
|
|
'number',
|
|
'number',
|
|
'number'
|
|
]
|
|
)
|
|
BENCHMARK_START_BUTTON = gradio.Button(
|
|
value = wording.get('uis.start_button'),
|
|
variant = 'primary',
|
|
size = 'sm'
|
|
)
|
|
BENCHMARK_CLEAR_BUTTON = gradio.Button(
|
|
value = wording.get('uis.clear_button'),
|
|
size = 'sm'
|
|
)
|
|
|
|
|
|
def listen() -> None:
|
|
benchmark_runs_checkbox_group = get_ui_component('benchmark_runs_checkbox_group')
|
|
benchmark_cycles_slider = get_ui_component('benchmark_cycles_slider')
|
|
|
|
if benchmark_runs_checkbox_group and benchmark_cycles_slider:
|
|
BENCHMARK_START_BUTTON.click(start, inputs = [ benchmark_runs_checkbox_group, benchmark_cycles_slider ], outputs = BENCHMARK_RESULTS_DATAFRAME)
|
|
BENCHMARK_CLEAR_BUTTON.click(clear, outputs = BENCHMARK_RESULTS_DATAFRAME)
|
|
|
|
|
|
def start(benchmark_runs : List[str], benchmark_cycles : int) -> Generator[List[Any], None, None]:
|
|
deepfuze.globals.source_paths = [ '../../models/facefusion/examples/source.jpg', '../../models/facefusion/examples/source.mp3' ]
|
|
deepfuze.globals.output_path = tempfile.gettempdir()
|
|
deepfuze.globals.face_landmarker_score = 0
|
|
deepfuze.globals.temp_frame_format = 'bmp'
|
|
deepfuze.globals.output_video_preset = 'ultrafast'
|
|
benchmark_results = []
|
|
target_paths = [ BENCHMARKS[benchmark_run] for benchmark_run in benchmark_runs if benchmark_run in BENCHMARKS ]
|
|
|
|
if target_paths:
|
|
pre_process()
|
|
for target_path in target_paths:
|
|
deepfuze.globals.target_path = target_path
|
|
benchmark_results.append(benchmark(benchmark_cycles))
|
|
yield benchmark_results
|
|
post_process()
|
|
|
|
|
|
def pre_process() -> None:
|
|
if deepfuze.globals.system_memory_limit > 0:
|
|
limit_system_memory(deepfuze.globals.system_memory_limit)
|
|
for frame_processor_module in get_frame_processors_modules(deepfuze.globals.frame_processors):
|
|
frame_processor_module.get_frame_processor()
|
|
|
|
|
|
def post_process() -> None:
|
|
clear_static_faces()
|
|
|
|
|
|
def benchmark(benchmark_cycles : int) -> List[Any]:
|
|
process_times = []
|
|
video_frame_total = count_video_frame_total(deepfuze.globals.target_path)
|
|
output_video_resolution = detect_video_resolution(deepfuze.globals.target_path)
|
|
deepfuze.globals.output_video_resolution = pack_resolution(output_video_resolution)
|
|
deepfuze.globals.output_video_fps = detect_video_fps(deepfuze.globals.target_path)
|
|
|
|
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\
|
|
[
|
|
deepfuze.globals.target_path,
|
|
benchmark_cycles,
|
|
average_run,
|
|
fastest_run,
|
|
slowest_run,
|
|
relative_fps
|
|
]
|
|
|
|
|
|
def clear() -> gradio.Dataframe:
|
|
while process_manager.is_processing():
|
|
sleep(0.5)
|
|
if deepfuze.globals.target_path:
|
|
clear_temp(deepfuze.globals.target_path)
|
|
return gradio.Dataframe(value = None)
|