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This commit is contained in:
henryruhs
2025-06-22 10:52:03 +02:00
parent 2193794501
commit 9d169164f6
3 changed files with 1 additions and 55 deletions
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2
facefusion/benchmarker.py
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@@ -92,7 +92,7 @@ def render() -> None:
headers =\
[
'target_path',
'benchmark_cycle_count',
'cycle_count',
'average_run',
'fastest_run',
'slowest_run',

3
facefusion/core.py
View File

@@ -23,7 +23,6 @@ from facefusion.memory import limit_system_memory
from facefusion.processors.core import get_processors_modules
from facefusion.program import create_program
from facefusion.program_helper import validate_args
from facefusion.statistics import conditional_log_statistics
from facefusion.temp_helper import clear_temp_directory, create_temp_directory, get_temp_file_path, move_temp_file, resolve_temp_frame_paths
from facefusion.types import Args, ErrorCode
from facefusion.vision import pack_resolution, read_image, read_static_images, read_video_frame, restrict_image_resolution, restrict_trim_frame, restrict_video_fps, restrict_video_resolution, unpack_resolution
@@ -409,7 +408,6 @@ def process_image(start_time : float) -> ErrorCode:
if is_image(state_manager.get_item('output_path')):
seconds = '{:.2f}'.format((time() - start_time) % 60)
logger.info(wording.get('processing_image_succeed').format(seconds = seconds), __name__)
conditional_log_statistics()
else:
logger.error(wording.get('processing_image_failed'), __name__)
process_manager.end()
@@ -500,7 +498,6 @@ def process_video(start_time : float) -> ErrorCode:
if is_video(state_manager.get_item('output_path')):
seconds = '{:.2f}'.format((time() - start_time))
logger.info(wording.get('processing_video_succeed').format(seconds = seconds), __name__)
conditional_log_statistics()
else:
logger.error(wording.get('processing_video_failed'), __name__)
process_manager.end()

51
facefusion/statistics.py
View File

@@ -1,51 +0,0 @@
from typing import Any, Dict
import numpy
from facefusion import logger, state_manager
from facefusion.face_store import get_face_store
from facefusion.types import FaceSet
def create_statistics(static_faces : FaceSet) -> Dict[str, Any]:
face_detector_scores = []
face_landmarker_scores = []
statistics =\
{
'min_face_detector_score': 0,
'min_face_landmarker_score': 0,
'max_face_detector_score': 0,
'max_face_landmarker_score': 0,
'average_face_detector_score': 0,
'average_face_landmarker_score': 0,
'total_face_landmark_5_fallbacks': 0,
'total_frames_with_faces': 0,
'total_faces': 0
}
for faces in static_faces.values():
statistics['total_frames_with_faces'] = statistics.get('total_frames_with_faces') + 1
for face in faces:
statistics['total_faces'] = statistics.get('total_faces') + 1
face_detector_scores.append(face.score_set.get('detector'))
face_landmarker_scores.append(face.score_set.get('landmarker'))
if numpy.array_equal(face.landmark_set.get('5'), face.landmark_set.get('5/68')):
statistics['total_face_landmark_5_fallbacks'] = statistics.get('total_face_landmark_5_fallbacks') + 1
if face_detector_scores:
statistics['min_face_detector_score'] = round(min(face_detector_scores), 2)
statistics['max_face_detector_score'] = round(max(face_detector_scores), 2)
statistics['average_face_detector_score'] = round(numpy.mean(face_detector_scores), 2)
if face_landmarker_scores:
statistics['min_face_landmarker_score'] = round(min(face_landmarker_scores), 2)
statistics['max_face_landmarker_score'] = round(max(face_landmarker_scores), 2)
statistics['average_face_landmarker_score'] = round(numpy.mean(face_landmarker_scores), 2)
return statistics
def conditional_log_statistics() -> None:
if state_manager.get_item('log_level') == 'debug':
statistics = create_statistics(get_face_store().get('static_faces'))
for name, value in statistics.items():
logger.debug(str(name) + ': ' + str(value), __name__)