| from facefusion import state_manager |
| from facefusion.filesystem import get_file_name, is_video, resolve_file_paths |
| from facefusion.jobs import job_store |
| from facefusion.normalizer import normalize_fps, normalize_space |
| from facefusion.processors.core import get_processors_modules |
| from facefusion.types import ApplyStateItem, Args |
| from facefusion.vision import detect_video_fps |
|
|
|
|
| def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None: |
| apply_state_item('command', args.get('command')) |
| apply_state_item('temp_path', args.get('temp_path')) |
| apply_state_item('jobs_path', args.get('jobs_path')) |
| apply_state_item('source_paths', args.get('source_paths')) |
| apply_state_item('target_path', args.get('target_path')) |
| apply_state_item('output_path', args.get('output_path')) |
| apply_state_item('source_pattern', args.get('source_pattern')) |
| apply_state_item('target_pattern', args.get('target_pattern')) |
| apply_state_item('output_pattern', args.get('output_pattern')) |
| apply_state_item('face_detector_model', args.get('face_detector_model')) |
| apply_state_item('face_detector_size', args.get('face_detector_size')) |
| apply_state_item('face_detector_margin', normalize_space(args.get('face_detector_margin'))) |
| apply_state_item('face_detector_angles', args.get('face_detector_angles')) |
| apply_state_item('face_detector_score', args.get('face_detector_score')) |
| apply_state_item('face_landmarker_model', args.get('face_landmarker_model')) |
| apply_state_item('face_landmarker_score', args.get('face_landmarker_score')) |
| apply_state_item('face_selector_mode', args.get('face_selector_mode')) |
| apply_state_item('face_selector_order', args.get('face_selector_order')) |
| apply_state_item('face_selector_age_start', args.get('face_selector_age_start')) |
| apply_state_item('face_selector_age_end', args.get('face_selector_age_end')) |
| apply_state_item('face_selector_gender', args.get('face_selector_gender')) |
| apply_state_item('face_selector_race', args.get('face_selector_race')) |
| apply_state_item('reference_face_position', args.get('reference_face_position')) |
| apply_state_item('reference_face_distance', args.get('reference_face_distance')) |
| apply_state_item('reference_frame_number', args.get('reference_frame_number')) |
| apply_state_item('face_tracker_score', args.get('face_tracker_score')) |
| apply_state_item('face_occluder_model', args.get('face_occluder_model')) |
| apply_state_item('face_parser_model', args.get('face_parser_model')) |
| apply_state_item('face_mask_types', args.get('face_mask_types')) |
| apply_state_item('face_mask_areas', args.get('face_mask_areas')) |
| apply_state_item('face_mask_regions', args.get('face_mask_regions')) |
| apply_state_item('face_mask_blur', args.get('face_mask_blur')) |
| apply_state_item('face_mask_padding', normalize_space(args.get('face_mask_padding'))) |
| apply_state_item('voice_extractor_model', args.get('voice_extractor_model')) |
| apply_state_item('trim_frame_start', args.get('trim_frame_start')) |
| apply_state_item('trim_frame_end', args.get('trim_frame_end')) |
| apply_state_item('temp_frame_format', args.get('temp_frame_format')) |
| apply_state_item('temp_pixel_format', args.get('temp_pixel_format')) |
| apply_state_item('target_frame_amount', args.get('target_frame_amount')) |
| apply_state_item('output_image_quality', args.get('output_image_quality')) |
| apply_state_item('output_image_scale', args.get('output_image_scale')) |
| apply_state_item('output_audio_encoder', args.get('output_audio_encoder')) |
| apply_state_item('output_audio_quality', args.get('output_audio_quality')) |
| apply_state_item('output_audio_volume', args.get('output_audio_volume')) |
| apply_state_item('output_video_encoder', args.get('output_video_encoder')) |
| apply_state_item('output_video_preset', args.get('output_video_preset')) |
| apply_state_item('output_video_quality', args.get('output_video_quality')) |
| apply_state_item('output_video_scale', args.get('output_video_scale')) |
|
|
| if args.get('output_video_fps') or is_video(args.get('target_path')): |
| output_video_fps = normalize_fps(args.get('output_video_fps')) or detect_video_fps(args.get('target_path')) |
| apply_state_item('output_video_fps', output_video_fps) |
|
|
| apply_state_item('workflow_mode', args.get('workflow_mode')) |
| apply_state_item('workflow_strategy', args.get('workflow_strategy')) |
| available_processors = [ get_file_name(file_path) for file_path in resolve_file_paths('facefusion/processors/modules') ] |
| apply_state_item('processors', args.get('processors')) |
|
|
| for processor_module in get_processors_modules(available_processors): |
| processor_module.apply_args(args, apply_state_item) |
|
|
| apply_state_item('open_browser', args.get('open_browser')) |
| apply_state_item('ui_layouts', args.get('ui_layouts')) |
| apply_state_item('ui_workflow', args.get('ui_workflow')) |
| apply_state_item('execution_device_ids', args.get('execution_device_ids')) |
| apply_state_item('execution_providers', args.get('execution_providers')) |
| apply_state_item('execution_thread_count', args.get('execution_thread_count')) |
| apply_state_item('download_providers', args.get('download_providers')) |
| apply_state_item('download_scope', args.get('download_scope')) |
| apply_state_item('benchmark_mode', args.get('benchmark_mode')) |
| apply_state_item('benchmark_resolutions', args.get('benchmark_resolutions')) |
| apply_state_item('benchmark_cycle_count', args.get('benchmark_cycle_count')) |
| apply_state_item('video_memory_strategy', args.get('video_memory_strategy')) |
| apply_state_item('log_level', args.get('log_level')) |
| apply_state_item('halt_on_error', args.get('halt_on_error')) |
| apply_state_item('job_id', args.get('job_id')) |
| apply_state_item('job_status', args.get('job_status')) |
| apply_state_item('step_index', args.get('step_index')) |
|
|
|
|
| def reduce_step_args(args : Args) -> Args: |
| step_args =\ |
| { |
| key: args[key] for key in args if key in job_store.get_step_keys() |
| } |
| return step_args |
|
|
|
|
| def reduce_job_args(args : Args) -> Args: |
| job_args =\ |
| { |
| key: args[key] for key in args if key in job_store.get_job_keys() |
| } |
| return job_args |
|
|
|
|
| def collect_step_args() -> Args: |
| step_args =\ |
| { |
| key: state_manager.get_item(key) for key in job_store.get_step_keys() |
| } |
| return step_args |
|
|
|
|
| def collect_job_args() -> Args: |
| job_args =\ |
| { |
| key: state_manager.get_item(key) for key in job_store.get_job_keys() |
| } |
| return job_args |
|
|