d149a71a1b
* Terminate base directory from temp helper * Partial adjust program codebase * Move arguments around * Make `-j` absolete * Resolve args * Fix job register keys * Adjust date test * Finalize temp path
119 lines
5.8 KiB
Python
119 lines
5.8 KiB
Python
from facefusion import state_manager
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from facefusion.filesystem import is_image, is_video, list_directory
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from facefusion.jobs import job_store
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from facefusion.normalizer import normalize_fps, normalize_padding
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from facefusion.processors.core import get_processors_modules
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from facefusion.typing import ApplyStateItem, Args
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from facefusion.vision import create_image_resolutions, create_video_resolutions, detect_image_resolution, detect_video_fps, detect_video_resolution, pack_resolution
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def reduce_step_args(args : Args) -> Args:
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step_args =\
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{
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key: args[key] for key in args if key in job_store.get_step_keys()
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}
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return step_args
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def collect_step_args() -> Args:
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step_args =\
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{
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key: state_manager.get_item(key) for key in job_store.get_step_keys() #type:ignore[arg-type]
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}
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return step_args
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def collect_job_args() -> Args:
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job_args =\
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{
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key: state_manager.get_item(key) for key in job_store.get_job_keys() #type:ignore[arg-type]
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}
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return job_args
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def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
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# general
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apply_state_item('command', args.get('command'))
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# paths
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apply_state_item('temp_path', args.get('temp_path'))
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apply_state_item('jobs_path', args.get('jobs_path'))
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apply_state_item('source_paths', args.get('source_paths'))
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apply_state_item('target_path', args.get('target_path'))
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apply_state_item('output_path', args.get('output_path'))
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# face detector
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apply_state_item('face_detector_model', args.get('face_detector_model'))
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apply_state_item('face_detector_size', args.get('face_detector_size'))
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apply_state_item('face_detector_angles', args.get('face_detector_angles'))
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apply_state_item('face_detector_score', args.get('face_detector_score'))
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# face landmarker
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apply_state_item('face_landmarker_model', args.get('face_landmarker_model'))
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apply_state_item('face_landmarker_score', args.get('face_landmarker_score'))
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# face selector
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apply_state_item('face_selector_mode', args.get('face_selector_mode'))
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apply_state_item('face_selector_order', args.get('face_selector_order'))
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apply_state_item('face_selector_age_start', args.get('face_selector_age_start'))
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apply_state_item('face_selector_age_end', args.get('face_selector_age_end'))
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apply_state_item('face_selector_gender', args.get('face_selector_gender'))
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apply_state_item('face_selector_race', args.get('face_selector_race'))
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apply_state_item('reference_face_position', args.get('reference_face_position'))
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apply_state_item('reference_face_distance', args.get('reference_face_distance'))
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apply_state_item('reference_frame_number', args.get('reference_frame_number'))
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# face masker
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apply_state_item('face_mask_types', args.get('face_mask_types'))
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apply_state_item('face_mask_blur', args.get('face_mask_blur'))
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apply_state_item('face_mask_padding', normalize_padding(args.get('face_mask_padding')))
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apply_state_item('face_mask_regions', args.get('face_mask_regions'))
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# frame extraction
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apply_state_item('trim_frame_start', args.get('trim_frame_start'))
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apply_state_item('trim_frame_end', args.get('trim_frame_end'))
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apply_state_item('temp_frame_format', args.get('temp_frame_format'))
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apply_state_item('keep_temp', args.get('keep_temp'))
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# output creation
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apply_state_item('output_image_quality', args.get('output_image_quality'))
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if is_image(args.get('target_path')):
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output_image_resolution = detect_image_resolution(args.get('target_path'))
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output_image_resolutions = create_image_resolutions(output_image_resolution)
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if args.get('output_image_resolution') in output_image_resolutions:
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apply_state_item('output_image_resolution', args.get('output_image_resolution'))
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else:
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apply_state_item('output_image_resolution', pack_resolution(output_image_resolution))
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apply_state_item('output_audio_encoder', args.get('output_audio_encoder'))
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apply_state_item('output_video_encoder', args.get('output_video_encoder'))
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apply_state_item('output_video_preset', args.get('output_video_preset'))
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apply_state_item('output_video_quality', args.get('output_video_quality'))
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if is_video(args.get('target_path')):
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output_video_resolution = detect_video_resolution(args.get('target_path'))
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output_video_resolutions = create_video_resolutions(output_video_resolution)
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if args.get('output_video_resolution') in output_video_resolutions:
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apply_state_item('output_video_resolution', args.get('output_video_resolution'))
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else:
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apply_state_item('output_video_resolution', pack_resolution(output_video_resolution))
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if args.get('output_video_fps') or is_video(args.get('target_path')):
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output_video_fps = normalize_fps(args.get('output_video_fps')) or detect_video_fps(args.get('target_path'))
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apply_state_item('output_video_fps', output_video_fps)
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apply_state_item('skip_audio', args.get('skip_audio'))
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# processors
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available_processors = list_directory('facefusion/processors/modules')
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apply_state_item('processors', args.get('processors'))
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for processor_module in get_processors_modules(available_processors):
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processor_module.apply_args(args, apply_state_item)
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# uis
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apply_state_item('open_browser', args.get('open_browser'))
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apply_state_item('ui_layouts', args.get('ui_layouts'))
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apply_state_item('ui_workflow', args.get('ui_workflow'))
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# execution
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apply_state_item('execution_device_id', args.get('execution_device_id'))
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apply_state_item('execution_providers', args.get('execution_providers'))
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apply_state_item('execution_thread_count', args.get('execution_thread_count'))
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apply_state_item('execution_queue_count', args.get('execution_queue_count'))
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# memory
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apply_state_item('video_memory_strategy', args.get('video_memory_strategy'))
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apply_state_item('system_memory_limit', args.get('system_memory_limit'))
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# misc
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apply_state_item('skip_download', args.get('skip_download'))
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apply_state_item('log_level', args.get('log_level'))
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# jobs
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apply_state_item('job_id', args.get('job_id'))
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apply_state_item('job_status', args.get('job_status'))
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apply_state_item('step_index', args.get('step_index'))
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