Next (#384)

* feat/yoloface (#334)

* added yolov8 to face_detector (#323)

* added yolov8 to face_detector

* added yolov8 to face_detector

* Initial cleanup and renaming

* Update README

* refactored detect_with_yoloface (#329)

* refactored detect_with_yoloface

* apply review

* Change order again

* Restore working code

* modified code (#330)

* refactored detect_with_yoloface

* apply review

* use temp_frame in detect_with_yoloface

* reorder

* modified

* reorder models

* Tiny cleanup

---------

Co-authored-by: tamoharu <133945583+tamoharu@users.noreply.github.com>

* include audio file functions (#336)

* Add testing for audio handlers

* Change order

* Fix naming

* Use correct typing in choices

* Update help message for arguments, Notation based wording approach (#347)

* Update help message for arguments, Notation based wording approach

* Fix installer

* Audio functions (#345)

* Update ffmpeg.py

* Create audio.py

* Update ffmpeg.py

* Update audio.py

* Update audio.py

* Update typing.py

* Update ffmpeg.py

* Update audio.py

* Rename Frame to VisionFrame (#346)

* Minor tidy up

* Introduce audio testing

* Add more todo for testing

* Add more todo for testing

* Fix indent

* Enable venv on the fly

* Enable venv on the fly

* Revert venv on the fly

* Revert venv on the fly

* Force Gradio to shut up

* Force Gradio to shut up

* Clear temp before processing

* Reduce terminal output

* include audio file functions

* Enforce output resolution on merge video

* Minor cleanups

* Add age and gender to face debugger items (#353)

* Add age and gender to face debugger items

* Rename like suggested in the code review

* Fix the output framerate vs. time

* Lip Sync (#356)

* Cli implementation of wav2lip

* - create get_first_item()
- remove non gan wav2lip model
- implement video memory strategy
- implement get_reference_frame()
- implement process_image()
- rearrange crop_mask_list
- implement test_cli

* Simplify testing

* Rename to lip syncer

* Fix testing

* Fix testing

* Minor cleanup

* Cuda 12 installer (#362)

* Make cuda nightly (12) the default

* Better keep legacy cuda just in case

* Use CUDA and ROCM versions

* Remove MacOS options from installer (CoreML include in default package)

* Add lip-syncer support to source component

* Add lip-syncer support to source component

* Fix the check in the source component

* Add target image check

* Introduce more helpers to suite the lip-syncer needs

* Downgrade onnxruntime as of buggy 1.17.0 release

* Revert "Downgrade onnxruntime as of buggy 1.17.0 release"

This reverts commit f4a7ae6824fed87f0be50906bbc7e2d61d00617b.

* More testing and add todos

* Fix the frame processor API to at least not throw errors

* Introduce dict based frame processor inputs (#364)

* Introduce dict based frame processor inputs

* Forgot to adjust webcam

* create path payloads (#365)

* create index payload to paths for process_frames

* rename to payload_paths

* This code now is poetry

* Fix the terminal output

* Make lip-syncer work in the preview

* Remove face debugger test for now

* Reoder reference_faces, Fix testing

* Use inswapper_128 on buggy onnxruntime 1.17.0

* Undo inswapper_128_fp16 duo broken onnxruntime 1.17.0

* Undo inswapper_128_fp16 duo broken onnxruntime 1.17.0

* Fix lip_syncer occluder & region mask issue

* Fix preview once in case there was no output video fps

* fix lip_syncer custom fps

* remove unused import

* Add 68 landmark functions (#367)

* Add 68 landmark model

* Add landmark to face object

* Re-arrange and modify typing

* Rename function

* Rearrange

* Rearrange

* ignore type

* ignore type

* change type

* ignore

* name

* Some cleanup

* Some cleanup

* Opps, I broke something

* Feat/face analyser refactoring (#369)

* Restructure face analyser and start TDD

* YoloFace and Yunet testing are passing

* Remove offset from yoloface detection

* Cleanup code

* Tiny fix

* Fix get_many_faces()

* Tiny fix (again)

* Use 320x320 fallback for retinaface

* Fix merging mashup

* Upload wave2lip model

* Upload 2dfan2 model and rename internal to face_predictor

* Downgrade onnxruntime for most cases

* Update for the face debugger to render landmark 68

* Try to make detect_face_landmark_68() and detect_gender_age() more uniform

* Enable retinaface testing for 320x320

* Make detect_face_landmark_68() and detect_gender_age() as uniform as … (#370)

* Make detect_face_landmark_68() and detect_gender_age() as uniform as possible

* Revert landmark scale and translation

* Make box-mask for lip-syncer adjustable

* Add create_bbox_from_landmark()

* Remove currently unused code

* Feat/uniface (#375)

* add uniface (#373)

* Finalize UniFace implementation

---------

Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>

* My approach how todo it

* edit

* edit

* replace vertical blur with gaussian

* remove region mask

* Rebase against next and restore method

* Minor improvements

* Minor improvements

* rename & add forehead padding

* Adjust and host uniface model

* Use 2dfan4 model

* Rename to face landmarker

* Feat/replace bbox with bounding box (#380)

* Add landmark 68 to 5 convertion

* Add landmark 68 to 5 convertion

* Keep 5, 5/68 and 68 landmarks

* Replace kps with landmark

* Replace bbox with bounding box

* Reshape face_landmark5_list different

* Make yoloface the default

* Move convert_face_landmark_68_to_5 to face_helper

* Minor spacing issue

* Dynamic detector sizes according to model (#382)

* Dynamic detector sizes according to model

* Dynamic detector sizes according to model

* Undo false commited files

* Add lib syncer model to the UI

* fix halo (#383)

* Bump to 2.3.0

* Update README and wording

* Update README and wording

* Fix spacing

* Apply _vision suffix

* Apply _vision suffix

* Apply _vision suffix

* Apply _vision suffix

* Apply _vision suffix

* Apply _vision suffix

* Apply _vision suffix, Move mouth mask to face_masker.py

* Apply _vision suffix

* Apply _vision suffix

* increase forehead padding

---------

Co-authored-by: tamoharu <133945583+tamoharu@users.noreply.github.com>
Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>

facefusion/choices.py

@@ -1,18 +1,22 @@
-from typing import List
+from typing import List, Dict
 
-from facefusion.typing import VideoMemoryStrategy, FaceSelectorMode, FaceAnalyserOrder, FaceAnalyserAge, FaceAnalyserGender, FaceMaskType, FaceMaskRegion, TempFrameFormat, OutputVideoEncoder, OutputVideoPreset
+from facefusion.typing import VideoMemoryStrategy, FaceSelectorMode, FaceAnalyserOrder, FaceAnalyserAge, FaceAnalyserGender, FaceDetectorModel, FaceMaskType, FaceMaskRegion, TempFrameFormat, OutputVideoEncoder, OutputVideoPreset
 from facefusion.common_helper import create_int_range, create_float_range
 
 video_memory_strategies : List[VideoMemoryStrategy] = [ 'strict', 'moderate', 'tolerant' ]
 face_analyser_orders : List[FaceAnalyserOrder] = [ 'left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small', 'best-worst', 'worst-best' ]
 face_analyser_ages : List[FaceAnalyserAge] = [ 'child', 'teen', 'adult', 'senior' ]
-face_analyser_genders : List[FaceAnalyserGender] = [ 'male', 'female' ]
-face_detector_models : List[str] = [ 'retinaface', 'yunet' ]
-face_detector_sizes : List[str] = [ '160x160', '320x320', '480x480', '512x512', '640x640', '768x768', '960x960', '1024x1024' ]
+face_analyser_genders : List[FaceAnalyserGender] = [ 'female', 'male' ]
+face_detector_set : Dict[FaceDetectorModel, List[str]] =\
+{
+	'retinaface':  [ '160x160', '320x320', '480x480', '512x512', '640x640' ],
+	'yoloface': [ '640x640' ],
+	'yunet': [ '160x160', '320x320', '480x480', '512x512', '640x640', '768x768', '960x960', '1024x1024' ]
+}
 face_selector_modes : List[FaceSelectorMode] = [ 'reference', 'one', 'many' ]
 face_mask_types : List[FaceMaskType] = [ 'box', 'occlusion', 'region' ]
 face_mask_regions : List[FaceMaskRegion] = [ 'skin', 'left-eyebrow', 'right-eyebrow', 'left-eye', 'right-eye', 'eye-glasses', 'nose', 'mouth', 'upper-lip', 'lower-lip' ]
-temp_frame_formats : List[TempFrameFormat] = [ 'jpg', 'png', 'bmp' ]
+temp_frame_formats : List[TempFrameFormat] = [ 'bmp', 'jpg', 'png' ]
 output_video_encoders : List[OutputVideoEncoder] = [ 'libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc' ]
 output_video_presets : List[OutputVideoPreset] = [ 'ultrafast', 'superfast', 'veryfast', 'faster', 'fast', 'medium', 'slow', 'slower', 'veryslow' ]