Next (#216)
* Simplify bbox access * Code cleanup * Simplify bbox access * Move code to face helper * Swap and paste back without insightface * Swap and paste back without insightface * Remove semaphore where possible * Improve paste back performance * Cosmetic changes * Move the predictor to ONNX to avoid tensorflow, Use video ranges for prediction * Make CI happy * Move template and size to the options * Fix different color on box * Uniform model handling for predictor * Uniform frame handling for predictor * Pass kps direct to warp_face * Fix urllib * Analyse based on matches * Analyse based on rate * Fix CI * ROCM and OpenVINO mapping for torch backends * Fix the paste back speed * Fix import * Replace retinaface with yunet (#168) * Remove insightface dependency * Fix urllib * Some fixes * Analyse based on matches * Analyse based on rate * Fix CI * Migrate to Yunet * Something is off here * We indeed need semaphore for yunet * Normalize the normed_embedding * Fix download of models * Fix download of models * Fix download of models * Add score and improve affine_matrix * Temp fix for bbox out of frame * Temp fix for bbox out of frame * ROCM and OpenVINO mapping for torch backends * Normalize bbox * Implement gender age * Cosmetics on cli args * Prevent face jumping * Fix the paste back speed * FIx import * Introduce detection size * Cosmetics on face analyser ARGS and globals * Temp fix for shaking face * Accurate event handling * Accurate event handling * Accurate event handling * Set the reference_frame_number in face_selector component * Simswap model (#171) * Add simswap models * Add ghost models * Introduce normed template * Conditional prepare and normalize for ghost * Conditional prepare and normalize for ghost * Get simswap working * Get simswap working * Fix refresh of swapper model * Refine face selection and detection (#174) * Refine face selection and detection * Update README.md * Fix some face analyser UI * Fix some face analyser UI * Introduce range handling for CLI arguments * Introduce range handling for CLI arguments * Fix some spacings * Disable onnxruntime warnings * Use cv2.blur over cv2.GaussianBlur for better performance * Revert "Use cv2.blur over cv2.GaussianBlur for better performance" This reverts commit bab666d6f9216a9f24faa84ead2d006b76f30159. * Prepare universal face detection * Prepare universal face detection part2 * Reimplement retinaface * Introduce cached anchors creation * Restore filtering to enhance performance * Minor changes * Minor changes * More code but easier to understand * Minor changes * Rename predictor to content analyser * Change detection/recognition to detector/recognizer * Fix crop frame borders * Fix spacing * Allow normalize output without a source * Improve conditional set face reference * Update dependencies * Add timeout for get_download_size * Fix performance due disorder * Move models to assets repository, Adjust namings * Refactor face analyser * Rename models once again * Fix spacing * Highres simswap (#192) * Introduce highres simswap * Fix simswap 256 color issue (#191) * Fix simswap 256 color issue * Update face_swapper.py * Normalize models and host in our repo * Normalize models and host in our repo --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> * Rename face analyser direction to face analyser order * Improve the UI for face selector * Add best-worst, worst-best detector ordering * Clear as needed and fix zero score bug * Fix linter * Improve startup time by multi thread remote download size * Just some cosmetics * Normalize swagger source input, Add blendface_256 (unfinished) * New paste back (#195) * add new paste_back (#194) * add new paste_back * Update face_helper.py * Update face_helper.py * add commandline arguments and gui * fix conflict * Update face_mask.py * type fix * Clean some wording and typing --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> * Clean more names, use blur range approach * Add blur padding range * Change the padding order * Fix yunet filename * Introduce face debugger * Use percent for mask padding * Ignore this * Ignore this * Simplify debugger output * implement blendface (#198) * Clean up after the genius * Add gpen_bfr_256 * Cosmetics * Ignore face_mask_padding on face enhancer * Update face_debugger.py (#202) * Shrink debug_face() to a minimum * Mark as 2.0.0 release * remove unused (#204) * Apply NMS (#205) * Apply NMS * Apply NMS part2 * Fix restoreformer url * Add debugger cli and gui components (#206) * Add debugger cli and gui components * update * Polishing the types * Fix usage in README.md * Update onnxruntime * Support for webp * Rename paste-back to face-mask * Add license to README * Add license to README * Extend face selector mode by one * Update utilities.py (#212) * Stop inline camera on stream * Minor webcam updates * Gracefully start and stop webcam * Rename capture to video_capture * Make get webcam capture pure * Check webcam to not be None * Remove some is not None * Use index 0 for webcam * Remove memory lookup within progress bar * Less progress bar updates * Uniform progress bar * Use classic progress bar * Fix image and video validation * Use different hash for cache * Use best-worse order for webcam * Normalize padding like CSS * Update preview * Fix max memory * Move disclaimer and license to the docs * Update wording in README * Add LICENSE.md * Fix argument in README --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> Co-authored-by: alex00ds <31631959+alex00ds@users.noreply.github.com>
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from typing import List
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from facefusion.typing import FaceRecognition, FaceAnalyserDirection, FaceAnalyserAge, FaceAnalyserGender, TempFrameFormat, OutputVideoEncoder
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import numpy
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face_recognitions : List[FaceRecognition] = [ 'reference', 'many' ]
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face_analyser_directions : List[FaceAnalyserDirection] = [ 'left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small' ]
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from facefusion.typing import FaceSelectorMode, FaceAnalyserOrder, FaceAnalyserAge, FaceAnalyserGender, TempFrameFormat, OutputVideoEncoder
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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] = [ 'male', 'female' ]
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face_detector_models : List[str] = [ 'retinaface', 'yunet' ]
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face_detector_sizes : List[str] = [ '160x160', '320x320', '480x480', '512x512', '640x640', '768x768', '960x960', '1024x1024' ]
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face_selector_modes : List[FaceSelectorMode] = [ 'reference', 'one', 'many' ]
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temp_frame_formats : List[TempFrameFormat] = [ 'jpg', 'png' ]
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output_video_encoders : List[OutputVideoEncoder] = [ 'libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc' ]
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execution_thread_count_range : List[int] = numpy.arange(1, 129, 1).tolist()
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execution_queue_count_range : List[int] = numpy.arange(1, 33, 1).tolist()
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max_memory_range : List[int] = numpy.arange(0, 129, 1).tolist()
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face_detector_score_range : List[float] = numpy.arange(0.0, 1.05, 0.05).tolist()
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face_mask_blur_range : List[float] = numpy.arange(0.0, 1.05, 0.05).tolist()
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face_mask_padding_range : List[float] = numpy.arange(0, 101, 1).tolist()
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reference_face_distance_range : List[float] = numpy.arange(0.0, 1.55, 0.05).tolist()
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temp_frame_quality_range : List[int] = numpy.arange(0, 101, 1).tolist()
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output_image_quality_range : List[int] = numpy.arange(0, 101, 1).tolist()
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output_video_quality_range : List[int] = numpy.arange(0, 101, 1).tolist()
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