
* 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
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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 f4a7ae6824
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* 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>
35 lines
2.4 KiB
Python
Executable File
35 lines
2.4 KiB
Python
Executable File
from typing import List, Dict
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from facefusion.typing import VideoMemoryStrategy, FaceSelectorMode, FaceAnalyserOrder, FaceAnalyserAge, FaceAnalyserGender, FaceDetectorModel, FaceMaskType, FaceMaskRegion, TempFrameFormat, OutputVideoEncoder, OutputVideoPreset
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from facefusion.common_helper import create_int_range, create_float_range
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video_memory_strategies : List[VideoMemoryStrategy] = [ 'strict', 'moderate', 'tolerant' ]
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face_analyser_orders : List[FaceAnalyserOrder] = [ 'left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small', 'best-worst', 'worst-best' ]
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face_analyser_ages : List[FaceAnalyserAge] = [ 'child', 'teen', 'adult', 'senior' ]
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face_analyser_genders : List[FaceAnalyserGender] = [ 'female', 'male' ]
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face_detector_set : Dict[FaceDetectorModel, List[str]] =\
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{
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'retinaface': [ '160x160', '320x320', '480x480', '512x512', '640x640' ],
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'yoloface': [ '640x640' ],
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'yunet': [ '160x160', '320x320', '480x480', '512x512', '640x640', '768x768', '960x960', '1024x1024' ]
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}
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face_selector_modes : List[FaceSelectorMode] = [ 'reference', 'one', 'many' ]
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face_mask_types : List[FaceMaskType] = [ 'box', 'occlusion', 'region' ]
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face_mask_regions : List[FaceMaskRegion] = [ 'skin', 'left-eyebrow', 'right-eyebrow', 'left-eye', 'right-eye', 'eye-glasses', 'nose', 'mouth', 'upper-lip', 'lower-lip' ]
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temp_frame_formats : List[TempFrameFormat] = [ 'bmp', 'jpg', 'png' ]
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output_video_encoders : List[OutputVideoEncoder] = [ 'libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc' ]
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output_video_presets : List[OutputVideoPreset] = [ 'ultrafast', 'superfast', 'veryfast', 'faster', 'fast', 'medium', 'slow', 'slower', 'veryslow' ]
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video_template_sizes : List[int] = [ 240, 360, 480, 540, 720, 1080, 1440, 2160 ]
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execution_thread_count_range : List[int] = create_int_range(1, 128, 1)
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execution_queue_count_range : List[int] = create_int_range(1, 32, 1)
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system_memory_limit_range : List[int] = create_int_range(0, 128, 1)
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face_detector_score_range : List[float] = create_float_range(0.0, 1.0, 0.05)
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face_mask_blur_range : List[float] = create_float_range(0.0, 1.0, 0.05)
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face_mask_padding_range : List[int] = create_int_range(0, 100, 1)
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reference_face_distance_range : List[float] = create_float_range(0.0, 1.5, 0.05)
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temp_frame_quality_range : List[int] = create_int_range(0, 100, 1)
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output_image_quality_range : List[int] = create_int_range(0, 100, 1)
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output_video_quality_range : List[int] = create_int_range(0, 100, 1)
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