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* Rename calcXXX to calculateXXX * Add migraphx support * Add migraphx support * Add migraphx support * Add migraphx support * Add migraphx support * Add migraphx support * Use True for the flags * Add migraphx support * add face-swapper-weight * add face-swapper-weight to facefusion.ini * changes * change choice * Fix typing for xxxWeight * Feat/log inference session (#906) * Log inference session, Introduce time helper * Log inference session, Introduce time helper * Log inference session, Introduce time helper * Log inference session, Introduce time helper * Mark as NEXT * Follow industry standard x1, x2, y1 and y2 * Follow industry standard x1, x2, y1 and y2 * Follow industry standard in terms of naming (#908) * Follow industry standard in terms of naming * Improve xxx_embedding naming * Fix norm vs. norms * Reduce timeout to 5 * Sort out voice_extractor once again * changes * Introduce many to the occlusion mask (#910) * Introduce many to the occlusion mask * Then we use minimum * Add support for wmv * Run platform tests before has_execution_provider (#911) * Add support for wmv * Introduce benchmark mode (#912) * Honestly makes no difference to me * Honestly makes no difference to me * Fix wording * Bring back YuNet (#922) * Reintroduce YuNet without cv2 dependency * Fix variable naming * Avoid RGB to YUV colorshift using libx264rgb * Avoid RGB to YUV colorshift using libx264rgb * Make libx264 the default again * Make libx264 the default again * Fix types in ffmpeg builder * Fix quality stuff in ffmpeg builder * Fix quality stuff in ffmpeg builder * Add libx264rgb to test * Revamp Processors (#923) * Introduce new concept of pure target frames * Radical refactoring of process flow * Introduce new concept of pure target frames * Fix webcam * Minor improvements * Minor improvements * Use deque for video processing * Use deque for video processing * Extend the video manager * Polish deque * Polish deque * Deque is not even used * Improve speed with multiple futures * Fix temp frame mutation and * Fix RAM usage * Remove old types and manage method * Remove execution_queue_count * Use init_state for benchmarker to avoid issues * add voice extractor option * Change the order of voice extractor in code * Use official download urls * Use official download urls * add gui * fix preview * Add remote updates for voice extractor * fix crash on headless-run * update test_job_helper.py * Fix it for good * Remove pointless method * Fix types and unused imports * Revamp reference (#925) * Initial revamp of face references * Initial revamp of face references * Initial revamp of face references * Terminate find_similar_faces * Improve find mutant faces * Improve find mutant faces * Move sort where it belongs * Forward reference vision frame * Forward reference vision frame also in preview * Fix reference selection * Use static video frame * Fix CI * Remove reference type from frame processors * Improve some naming * Fix types and unused imports * Fix find mutant faces * Fix find mutant faces * Fix imports * Correct naming * Correct naming * simplify pad * Improve webcam performance on highres * Camera manager (#932) * Introduce webcam manager * Fix order * Rename to camera manager, improve video manager * Fix CI * Remove optional * Fix naming in webcam options * Avoid using temp faces (#933) * output video scale * Fix imports * output image scale * upscale fix (not limiter) * add unit test scale_resolution & remove unused methods * fix and add test * fix * change pack_resolution * fix tests * Simplify output scale testing * Fix benchmark UI * Fix benchmark UI * Update dependencies * Introduce REAL multi gpu support using multi dimensional inference pool (#935) * Introduce REAL multi gpu support using multi dimensional inference pool * Remove the MULTI:GPU flag * Restore "processing stop" * Restore "processing stop" * Remove old templates * Go fill in with caching * add expression restorer areas * re-arrange * rename method * Fix stop for extract frames and merge video * Replace arcface_converter models with latest crossface models * Replace arcface_converter models with latest crossface models * Move module logs to debug mode * Refactor/streamer (#938) * Introduce webcam manager * Fix order * Rename to camera manager, improve video manager * Fix CI * Fix naming in webcam options * Move logic over to streamer * Fix streamer, improve webcam experience * Improve webcam experience * Revert method * Revert method * Improve webcam again * Use release on capture instead * Only forward valid frames * Fix resolution logging * Add AVIF support * Add AVIF support * Limit avif to unix systems * Drop avif * Drop avif * Drop avif * Default to Documents in the UI if output path is not set * Update wording.py (#939) "succeed" is grammatically incorrect in the given context. To succeed is the infinitive form of the verb. Correct would be either "succeeded" or alternatively a form involving the noun "success". * Fix more grammar issue * Fix more grammar issue * Sort out caching * Move webcam choices back to UI * Move preview options to own file (#940) * Fix Migraphx execution provider * Fix benchmark * Reuse blend frame method * Fix CI * Fix CI * Fix CI * Hotfix missing check in face debugger, Enable logger for preview * Fix reference selection (#942) * Fix reference selection * Fix reference selection * Fix reference selection * Fix reference selection * Side by side preview (#941) * Initial side by side preview * More work on preview, remove UI only stuff from vision.py * Improve more * Use fit frame * Add different fit methods for vision * Improve preview part2 * Improve preview part3 * Improve preview part4 * Remove none as choice * Remove useless methods * Fix CI * Fix naming * use 1024 as preview resolution default * Fix fit_cover_frame * Uniform fit_xxx_frame methods * Add back disabled logger * Use ui choices alias * Extract select face logic from processors (#943) * Extract select face logic from processors to use it for face by face in preview * Fix order * Remove old code * Merge methods * Refactor face debugger (#944) * Refactor huge method of face debugger * Remove text metrics from face debugger * Remove useless copy of temp frame * Resort methods * Fix spacing * Remove old method * Fix hard exit to work without signals * Prevent upscaling for face-by-face * Switch to version * Improve exiting --------- Co-authored-by: harisreedhar <h4harisreedhar.s.s@gmail.com> Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> Co-authored-by: Rafael Tappe Maestro <rafael@tappemaestro.com>
93 lines
4.1 KiB
Python
93 lines
4.1 KiB
Python
import importlib
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import random
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from time import sleep, time
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from typing import List
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from onnxruntime import InferenceSession
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from facefusion import logger, process_manager, state_manager, wording
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from facefusion.app_context import detect_app_context
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from facefusion.execution import create_inference_session_providers
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from facefusion.exit_helper import fatal_exit
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from facefusion.filesystem import get_file_name, is_file
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from facefusion.time_helper import calculate_end_time
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from facefusion.types import DownloadSet, ExecutionProvider, InferencePool, InferencePoolSet
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INFERENCE_POOL_SET : InferencePoolSet =\
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{
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'cli': {},
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'ui': {}
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}
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def get_inference_pool(module_name : str, model_names : List[str], model_source_set : DownloadSet) -> InferencePool:
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while process_manager.is_checking():
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sleep(0.5)
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execution_device_ids = state_manager.get_item('execution_device_ids')
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execution_providers = resolve_execution_providers(module_name)
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app_context = detect_app_context()
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for execution_device_id in execution_device_ids:
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inference_context = get_inference_context(module_name, model_names, execution_device_id, execution_providers)
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if app_context == 'cli' and INFERENCE_POOL_SET.get('ui').get(inference_context):
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INFERENCE_POOL_SET['cli'][inference_context] = INFERENCE_POOL_SET.get('ui').get(inference_context)
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if app_context == 'ui' and INFERENCE_POOL_SET.get('cli').get(inference_context):
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INFERENCE_POOL_SET['ui'][inference_context] = INFERENCE_POOL_SET.get('cli').get(inference_context)
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if not INFERENCE_POOL_SET.get(app_context).get(inference_context):
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INFERENCE_POOL_SET[app_context][inference_context] = create_inference_pool(model_source_set, execution_device_id, execution_providers)
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current_inference_context = get_inference_context(module_name, model_names, random.choice(execution_device_ids), execution_providers)
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return INFERENCE_POOL_SET.get(app_context).get(current_inference_context)
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def create_inference_pool(model_source_set : DownloadSet, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferencePool:
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inference_pool : InferencePool = {}
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for model_name in model_source_set.keys():
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model_path = model_source_set.get(model_name).get('path')
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if is_file(model_path):
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inference_pool[model_name] = create_inference_session(model_path, execution_device_id, execution_providers)
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return inference_pool
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def clear_inference_pool(module_name : str, model_names : List[str]) -> None:
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execution_device_ids = state_manager.get_item('execution_device_ids')
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execution_providers = resolve_execution_providers(module_name)
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app_context = detect_app_context()
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for execution_device_id in execution_device_ids:
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inference_context = get_inference_context(module_name, model_names, execution_device_id, execution_providers)
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if INFERENCE_POOL_SET.get(app_context).get(inference_context):
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del INFERENCE_POOL_SET[app_context][inference_context]
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def create_inference_session(model_path : str, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferenceSession:
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model_file_name = get_file_name(model_path)
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start_time = time()
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try:
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inference_session_providers = create_inference_session_providers(execution_device_id, execution_providers)
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inference_session = InferenceSession(model_path, providers = inference_session_providers)
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logger.debug(wording.get('loading_model_succeeded').format(model_name = model_file_name, seconds = calculate_end_time(start_time)), __name__)
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return inference_session
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except Exception:
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logger.error(wording.get('loading_model_failed').format(model_name = model_file_name), __name__)
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fatal_exit(1)
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def get_inference_context(module_name : str, model_names : List[str], execution_device_id : str, execution_providers : List[ExecutionProvider]) -> str:
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inference_context = '.'.join([ module_name ] + model_names + [ execution_device_id ] + list(execution_providers))
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return inference_context
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def resolve_execution_providers(module_name : str) -> List[ExecutionProvider]:
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module = importlib.import_module(module_name)
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if hasattr(module, 'resolve_execution_providers'):
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return getattr(module, 'resolve_execution_providers')()
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return state_manager.get_item('execution_providers')
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