Files
facefusion/facefusion/inference_manager.py
T
da0da3a4b4 Next (#945)
* 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>
2025-09-08 10:43:58 +02:00

93 lines
4.1 KiB
Python

import importlib
import random
from time import sleep, time
from typing import List
from onnxruntime import InferenceSession
from facefusion import logger, process_manager, state_manager, wording
from facefusion.app_context import detect_app_context
from facefusion.execution import create_inference_session_providers
from facefusion.exit_helper import fatal_exit
from facefusion.filesystem import get_file_name, is_file
from facefusion.time_helper import calculate_end_time
from facefusion.types import DownloadSet, ExecutionProvider, InferencePool, InferencePoolSet
INFERENCE_POOL_SET : InferencePoolSet =\
{
'cli': {},
'ui': {}
}
def get_inference_pool(module_name : str, model_names : List[str], model_source_set : DownloadSet) -> InferencePool:
while process_manager.is_checking():
sleep(0.5)
execution_device_ids = state_manager.get_item('execution_device_ids')
execution_providers = resolve_execution_providers(module_name)
app_context = detect_app_context()
for execution_device_id in execution_device_ids:
inference_context = get_inference_context(module_name, model_names, execution_device_id, execution_providers)
if app_context == 'cli' and INFERENCE_POOL_SET.get('ui').get(inference_context):
INFERENCE_POOL_SET['cli'][inference_context] = INFERENCE_POOL_SET.get('ui').get(inference_context)
if app_context == 'ui' and INFERENCE_POOL_SET.get('cli').get(inference_context):
INFERENCE_POOL_SET['ui'][inference_context] = INFERENCE_POOL_SET.get('cli').get(inference_context)
if not INFERENCE_POOL_SET.get(app_context).get(inference_context):
INFERENCE_POOL_SET[app_context][inference_context] = create_inference_pool(model_source_set, execution_device_id, execution_providers)
current_inference_context = get_inference_context(module_name, model_names, random.choice(execution_device_ids), execution_providers)
return INFERENCE_POOL_SET.get(app_context).get(current_inference_context)
def create_inference_pool(model_source_set : DownloadSet, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferencePool:
inference_pool : InferencePool = {}
for model_name in model_source_set.keys():
model_path = model_source_set.get(model_name).get('path')
if is_file(model_path):
inference_pool[model_name] = create_inference_session(model_path, execution_device_id, execution_providers)
return inference_pool
def clear_inference_pool(module_name : str, model_names : List[str]) -> None:
execution_device_ids = state_manager.get_item('execution_device_ids')
execution_providers = resolve_execution_providers(module_name)
app_context = detect_app_context()
for execution_device_id in execution_device_ids:
inference_context = get_inference_context(module_name, model_names, execution_device_id, execution_providers)
if INFERENCE_POOL_SET.get(app_context).get(inference_context):
del INFERENCE_POOL_SET[app_context][inference_context]
def create_inference_session(model_path : str, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferenceSession:
model_file_name = get_file_name(model_path)
start_time = time()
try:
inference_session_providers = create_inference_session_providers(execution_device_id, execution_providers)
inference_session = InferenceSession(model_path, providers = inference_session_providers)
logger.debug(wording.get('loading_model_succeeded').format(model_name = model_file_name, seconds = calculate_end_time(start_time)), __name__)
return inference_session
except Exception:
logger.error(wording.get('loading_model_failed').format(model_name = model_file_name), __name__)
fatal_exit(1)
def get_inference_context(module_name : str, model_names : List[str], execution_device_id : str, execution_providers : List[ExecutionProvider]) -> str:
inference_context = '.'.join([ module_name ] + model_names + [ execution_device_id ] + list(execution_providers))
return inference_context
def resolve_execution_providers(module_name : str) -> List[ExecutionProvider]:
module = importlib.import_module(module_name)
if hasattr(module, 'resolve_execution_providers'):
return getattr(module, 'resolve_execution_providers')()
return state_manager.get_item('execution_providers')