mirror of
https://github.com/facefusion/facefusion.git
synced 2026-06-06 20:53:54 +02:00
Henry Ruhs
f6e56a3d8c
* renaming and restructuring (#282) * Renaming and restructuring * Renaming and restructuring * Renaming and restructuring * Fix gender detection * Implement distance to face debugger * Implement distance to face debugger part2 * Implement distance to face debugger part3 * Mark as next * Fix reference when face_debugger comes first * Use official onnxruntime nightly * CUDA on steroids * CUDA on steroids * Add some testing * Set inswapper_128_fp16 as default * Feat/block until post check (#292) * Block until download is done * Introduce post_check() * Fix webcam * Update dependencies * Add --force-reinstall to installer * Introduce config ini (#298) * Introduce config ini * Fix output video encoder * Revert help listings back to commas, Move SSL hack to download.py * Introduce output-video-preset which defaults to veryfast * Mapping for nvenc encoders * Rework on events and non-blocking UI * Add fast bmp to temp_frame_formats * Add fast bmp to temp_frame_formats * Show total processing time on success * Show total processing time on success * Show total processing time on success * Move are_images, is_image and is_video back to filesystem * Fix some spacings * Pissing everyone of by renaming stuff * Fix seconds output * feat/video output fps (#312) * added output fps slider, removed 'keep fps' option (#311) * added output fps slider, removed 'keep fps' option * now uses passed fps instead of global fps for ffmpeg * fps values are now floats instead of ints * fix previous commit * removed default value from fps slider this is so we can implement a dynamic default value later * Fix seconds output * Some cleanup --------- Co-authored-by: Ran Shaashua <47498956+ranshaa05@users.noreply.github.com> * Allow 0.01 steps for fps * Make fps unregulated * Make fps unregulated * Remove distance from face debugger again (does not work) * Fix gender age * Fix gender age * Hotfix benchmark suite * Warp face normalize (#313) * use normalized kp templates * Update face_helper.py * My 50 cents to warp_face() --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> * face-swapper-weight (#315) * Move prepare_crop_frame and normalize_crop_frame out of apply_swap * Fix UI bug with different range * feat/output video resolution (#316) * Introduce detect_video_resolution, Rename detect_fps to detect_video_fps * Add calc_video_resolution_range * Make output resolution work, does not auto-select yet * Make output resolution work, does not auto-select yet * Try to keep the origin resolution * Split code into more fragments * Add pack/unpack resolution * Move video_template_sizes to choices * Improve create_video_resolutions * Reword benchmark suite * Optimal speed for benchmark * Introduce different video memory strategies, rename max_memory to max… (#317) * Introduce different video memory strategies, rename max_memory to max_system_memory * Update readme * Fix limit_system_memory call * Apply video_memory_strategy to face debugger * Limit face swapper weight to 3.0 * Remove face swapper weight due bad render outputs * Show/dide logic for output video preset * fix uint8 conversion * Fix whitespace * Finalize layout and update preview * Fix multi renders on face debugger * Restore less restrictive rendering of preview and stream * Fix block mode for model downloads * Add testing * Cosmetic changes * Enforce valid fps and resolution via CLI * Empty config * Cosmetics on args processing * Memory workover (#319) * Cosmetics on args processing * Fix for MacOS * Rename all max_ to _limit * More fixes * Update preview * Fix whitespace --------- Co-authored-by: Ran Shaashua <47498956+ranshaa05@users.noreply.github.com> Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>
59 lines
2.0 KiB
Python
Executable File
59 lines
2.0 KiB
Python
Executable File
from typing import Any, Literal, Callable, List, Tuple, Dict, TypedDict
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from collections import namedtuple
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import numpy
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Bbox = numpy.ndarray[Any, Any]
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Kps = numpy.ndarray[Any, Any]
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Score = float
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Embedding = numpy.ndarray[Any, Any]
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Face = namedtuple('Face',
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[
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'bbox',
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'kps',
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'score',
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'embedding',
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'normed_embedding',
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'gender',
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'age'
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])
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FaceSet = Dict[str, List[Face]]
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FaceStore = TypedDict('FaceStore',
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{
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'static_faces' : FaceSet,
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'reference_faces': FaceSet
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})
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Frame = numpy.ndarray[Any, Any]
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Mask = numpy.ndarray[Any, Any]
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Matrix = numpy.ndarray[Any, Any]
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Fps = float
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Padding = Tuple[int, int, int, int]
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Resolution = Tuple[int, int]
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Update_Process = Callable[[], None]
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Process_Frames = Callable[[List[str], List[str], Update_Process], None]
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Template = Literal['arcface_112_v1', 'arcface_112_v2', 'arcface_128_v2', 'ffhq_512']
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ProcessMode = Literal['output', 'preview', 'stream']
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LogLevel = Literal['error', 'warn', 'info', 'debug']
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VideoMemoryStrategy = Literal['strict', 'moderate', 'tolerant']
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FaceSelectorMode = Literal['reference', 'one', 'many']
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FaceAnalyserOrder = Literal['left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small', 'best-worst', 'worst-best']
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FaceAnalyserAge = Literal['child', 'teen', 'adult', 'senior']
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FaceAnalyserGender = Literal['male', 'female']
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FaceDetectorModel = Literal['retinaface', 'yunet']
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FaceRecognizerModel = Literal['arcface_blendswap', 'arcface_inswapper', 'arcface_simswap']
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FaceMaskType = Literal['box', 'occlusion', 'region']
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FaceMaskRegion = Literal['skin', 'left-eyebrow', 'right-eyebrow', 'left-eye', 'right-eye', 'eye-glasses', 'nose', 'mouth', 'upper-lip', 'lower-lip']
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TempFrameFormat = Literal['jpg', 'png', 'bmp']
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OutputVideoEncoder = Literal['libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc']
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OutputVideoPreset = Literal['ultrafast', 'superfast', 'veryfast', 'faster', 'fast', 'medium', 'slow', 'slower', 'veryslow']
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ModelValue = Dict[str, Any]
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ModelSet = Dict[str, ModelValue]
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OptionsWithModel = TypedDict('OptionsWithModel',
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{
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'model' : ModelValue
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})
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