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* mark as next * unify the dependency checks in pre_check and add ffprobe (#1181) * drop keep_temp and the common options component (#1180) Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * introduce ffprobe and ffprobe_builder (#1182) * introduce ffprobe and ffprobe_builder Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * introduce ffprobe and ffprobe_builder Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * probe video metadata via ffprobe in vision (#1184) * probe video metadata via ffprobe in vision Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * probe video metadata via ffprobe in vision Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * adopt the workflow task vocabulary from next major (#1185) Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * introduce workflow-mode and workflow-strategy like next major (#1187) Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * restrict hdr color transfer and tag the merge output as bt709 (#1188) * restrict hdr color transfer and tag the merge output as bt709 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * restrict hdr color transfer and tag the merge output as bt709 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * full video migration * compose the hdr fixture via the builder chain Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * compose the test fixtures via the builder and run_ffmpeg Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * compose every test fixture via the builder and run_ffmpeg (#1189) * compose every test fixture via the builder and run_ffmpeg Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * use loops in tests for ffmpeg stuff --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * New Video Manager (#1191) * tiny adjustment for tests * address the review on the video manager Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * introduce the stream strategy for the video workflow (#1192) * introduce the stream strategy for the video workflow Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * address the review on the stream strategy Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * annotate the changes for review Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * annotate the new tests for review Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * match the temp pixel format help to the locale style Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * question the set_input_seek naming Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * question the reader and writer keys Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * drop the review annotations from the encoder mapping tests Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * drop the review annotations from the thread count tests Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * drop the review annotations from the ui files Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * capture the open review questions as annotations Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a * drop the settled annotations from the types Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Tbcd6VWCiU4BQP1gywPr2a --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * switch to ffmpeg.style for audio.py * remove todos that were never needed * fix for ffmpeg7 * Add frame_store module (#1194) * add frame_store module * rename and change tests * rename and update tests * route window read through frame_store (#1196) * route window read through frame_store * update proper id * restore todos * restore todos * go v4 style for workflow (#1197) * go v4 style for workflow * remove some todos * route chunk read through frame_store (#1198) * vision integration * Deleted read_video_chunk + read_static_video_chunk * margin decouple (#1199) * fix windows CI fail (#1200) * Cleanup Part1 (#1201) * remove some todos, improve video manager, simplify ffmpeg commands and more * do more * remove thread count for filters * Cleanup Part 2 (#1202) * tons of renaming * tons of renaming * multi reader approach * bring tests to an okay-ish state * bring drain back * improve read_video_frame speed * rename method * move variables * seek video reader only when trim frame start is larger 0 * make stream the default * Cleanup/part 3 (#1203) * remove todo * sort out workflow, to match upcoming v4 * remove look ahead * remove core namespace again * Revamp execution provider overrides/adjustments (#1206) * Split provider hooks into override/adjust with cached CoreML base Replace the single resolve_inference_providers processor hook with two: override_inference_providers (full replacement) and adjust_inference_providers (merge options onto the base providers built by create_inference_providers). This lets CoreML processors inherit ModelCacheDirectory + SpecializationStrategy from the base while layering ModelFormat/MLComputeUnits on top. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01HTQCZiYjJyUX11bDpbRSiB * fix caching for execution provider by having override and adjust ways * fix caching for execution provider by having override and adjust ways * fix lint * use proper pytest fixtures --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix update preview bug (#1205) * fix update preview bug * fix update preview bug * remove guard * add is_vision_frame * Restrict the preview frame slider and the reader seek to the last frame index (#1207) * fix index bug * fix rounding bug * avoid tobytes copy (#1208) * beautify tests * hide ffmpeg warnings * simplify process_stream_frame * Use is vision frame everywhere (#1210) * use is_vision_frame everywhere * fix hash * fix lint * fix hash creation in face store * that model does not exist * update workflow ffmpeg * guard workflow (#1211) * bump version and dependencies * Update preview * switch workflow strategy to disk|memory * update preview * update preview * fix wording * last minute change workflow position * adjust wording --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> Co-authored-by: harisreedhar <h4harisreedhar.s.s@gmail.com>
116 lines
5.0 KiB
Python
116 lines
5.0 KiB
Python
import importlib
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import random
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from functools import lru_cache
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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, translator
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from facefusion.app_context import detect_app_context
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from facefusion.common_helper import is_windows
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from facefusion.execution import create_inference_providers, has_execution_provider
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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, InferenceProvider
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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 = state_manager.get_item('execution_providers')
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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_providers = resolve_static_inference_providers(module_name, execution_device_id)
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INFERENCE_POOL_SET[app_context][inference_context] = create_inference_pool(model_source_set, inference_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, inference_providers : List[InferenceProvider]) -> 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, inference_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 = state_manager.get_item('execution_providers')
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app_context = detect_app_context()
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if is_windows() and has_execution_provider('directml'):
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INFERENCE_POOL_SET[app_context].clear()
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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, inference_providers : List[InferenceProvider]) -> 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 = InferenceSession(model_path, providers = inference_providers)
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logger.debug(translator.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(translator.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 : int, execution_providers : List[ExecutionProvider]) -> str:
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inference_context = '.'.join([ module_name ] + model_names + [ str(execution_device_id) ] + list(execution_providers))
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return inference_context
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@lru_cache()
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def resolve_static_inference_providers(module_name : str, execution_device_id : int) -> List[InferenceProvider]:
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module = importlib.import_module(module_name)
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execution_providers = state_manager.get_item('execution_providers')
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if hasattr(module, 'override_inference_providers'):
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override_inference_providers = getattr(module, 'override_inference_providers')()
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if override_inference_providers:
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return override_inference_providers
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if hasattr(module, 'adjust_inference_providers'):
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adjust_inference_providers = getattr(module, 'adjust_inference_providers')()
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if adjust_inference_providers:
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inference_providers = create_inference_providers(execution_device_id, execution_providers)
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for adjust_inference_provider in adjust_inference_providers:
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for inference_provider in inference_providers:
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if inference_provider[0] == adjust_inference_provider[0] and inference_provider[1]:
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inference_provider[1].update(adjust_inference_provider[1])
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return inference_providers
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return create_inference_providers(execution_device_id, execution_providers)
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