2.1.0 (#253)
* Operating system specific installer options * Update dependencies * Sorting before NMS according to the standard * Minor typing fix * Change the wording * Update preview.py (#222) Added a release listener to the preview frame slider, this will update the frame preview with the latest frame * Combine preview slider listener * Remove change listener * Introduce multi source (#223) * Implement multi source * Adjust face enhancer and face debugger to multi source * Implement multi source to UI * Implement multi source to UI part2 * Implement multi source to UI part3 * Implement multi source to UI part4 * Some cleanup * Add face occluder (#225) (#226) * Add face occluder (#225) * add face-occluder (commandline only) * review 1 * Update face_masker.py * Update face_masker.py * Add gui & fix typing * Minor naming cleanup * Minor naming cleanup part2 --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> * Update usage information * Fix averaged normed_embedding * Remove blur from face occluder, enable accelerators * Switch to RANSAC with 100 threshold * Update face_enhancer.py (#229) * Update face_debugger.py (#230) * Split utilities (#232) * Split utilities * Split utilities part2 * Split utilities part3 * Split utilities part4 * Some cleanup * Implement log level support (#233) * Implement log level support * Fix testing * Implement debug logger * Implement debug logger * Fix alignment offset (#235) * Update face_helper.py * fix 2 * Enforce virtual environment via installer * Enforce virtual environment via installer * Enforce virtual environment via installer * Enforce virtual environment via installer * Feat/multi process reference faces (#239) * Multi processing aware reference faces * First clean up and joining of files * Finalize the face store * Reduce similar face detection to one set, use __name__ for scopes in logger * Rename to face_occluder * Introduce ModelSet type * Improve webcam error handling * Prevent null pointer on is_image() and is_video() * Prevent null pointer on is_image() and is_video() * Fix find similar faces * Fix find similar faces * Fix process_images for face enhancer * Bunch of minor improvements * onnxruntime for ROCM under linux * Improve mask related naming * Fix falsy import * Fix typo * Feat/face parser refactoring (#247) * Face parser update (#244) * face-parser * Update face_masker.py * update debugger * Update globals.py * Update face_masker.py * Refactor code to split occlusion from region * fix (#246) * fix * fix debugger resolution * flip input to horizontal * Clean up UI * Reduce the regions to inside face only * Reduce the regions to inside face only --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> * Fix enhancer, remove useless dest in add_argument() * Prevent unselect of the face_mask_regions via UI * Prepare next release * Shorten arguments that have choices and nargs * Add missing clear to face debugger --------- Co-authored-by: Mathias <github@feroc.de> Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>
This commit is contained in:
Henry Ruhs
128
facefusion/face_masker.py
Executable file
128
facefusion/face_masker.py
Executable file
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from typing import Any, Dict, List
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from cv2.typing import Size
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from functools import lru_cache
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import threading
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import cv2
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import numpy
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import onnxruntime
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import facefusion.globals
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from facefusion.typing import Frame, Mask, Padding, FaceMaskRegion, ModelSet
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from facefusion.filesystem import resolve_relative_path
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from facefusion.download import conditional_download
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FACE_OCCLUDER = None
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FACE_PARSER = None
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THREAD_LOCK : threading.Lock = threading.Lock()
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MODELS : ModelSet =\
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{
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'face_occluder':
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{
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'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/face_occluder.onnx',
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'path': resolve_relative_path('../.assets/models/face_occluder.onnx')
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},
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'face_parser':
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{
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'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/face_parser.onnx',
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'path': resolve_relative_path('../.assets/models/face_parser.onnx')
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}
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}
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FACE_MASK_REGIONS : Dict[FaceMaskRegion, int] =\
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{
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'skin': 1,
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'left-eyebrow': 2,
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'right-eyebrow': 3,
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'left-eye': 4,
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'right-eye': 5,
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'eye-glasses': 6,
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'nose': 10,
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'mouth': 11,
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'upper-lip': 12,
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'lower-lip': 13
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}
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def get_face_occluder() -> Any:
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global FACE_OCCLUDER
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with THREAD_LOCK:
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if FACE_OCCLUDER is None:
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model_path = MODELS.get('face_occluder').get('path')
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FACE_OCCLUDER = onnxruntime.InferenceSession(model_path, providers = facefusion.globals.execution_providers)
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return FACE_OCCLUDER
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def get_face_parser() -> Any:
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global FACE_PARSER
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with THREAD_LOCK:
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if FACE_PARSER is None:
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model_path = MODELS.get('face_parser').get('path')
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FACE_PARSER = onnxruntime.InferenceSession(model_path, providers = facefusion.globals.execution_providers)
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return FACE_PARSER
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def clear_face_occluder() -> None:
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global FACE_OCCLUDER
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FACE_OCCLUDER = None
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def clear_face_parser() -> None:
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global FACE_PARSER
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FACE_PARSER = None
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def pre_check() -> bool:
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if not facefusion.globals.skip_download:
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download_directory_path = resolve_relative_path('../.assets/models')
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model_urls =\
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[
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MODELS.get('face_occluder').get('url'),
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MODELS.get('face_parser').get('url'),
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]
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conditional_download(download_directory_path, model_urls)
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return True
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@lru_cache(maxsize = None)
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def create_static_box_mask(crop_size : Size, face_mask_blur : float, face_mask_padding : Padding) -> Mask:
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blur_amount = int(crop_size[0] * 0.5 * face_mask_blur)
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blur_area = max(blur_amount // 2, 1)
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box_mask = numpy.ones(crop_size, numpy.float32)
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box_mask[:max(blur_area, int(crop_size[1] * face_mask_padding[0] / 100)), :] = 0
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box_mask[-max(blur_area, int(crop_size[1] * face_mask_padding[2] / 100)):, :] = 0
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box_mask[:, :max(blur_area, int(crop_size[0] * face_mask_padding[3] / 100))] = 0
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box_mask[:, -max(blur_area, int(crop_size[0] * face_mask_padding[1] / 100)):] = 0
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if blur_amount > 0:
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box_mask = cv2.GaussianBlur(box_mask, (0, 0), blur_amount * 0.25)
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return box_mask
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def create_occlusion_mask(crop_frame : Frame) -> Mask:
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face_occluder = get_face_occluder()
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prepare_frame = cv2.resize(crop_frame, face_occluder.get_inputs()[0].shape[1:3][::-1])
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prepare_frame = numpy.expand_dims(prepare_frame, axis = 0).astype(numpy.float32) / 255
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prepare_frame = prepare_frame.transpose(0, 1, 2, 3)
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occlusion_mask = face_occluder.run(None,
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{
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face_occluder.get_inputs()[0].name: prepare_frame
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})[0][0]
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occlusion_mask = occlusion_mask.transpose(0, 1, 2).clip(0, 1).astype(numpy.float32)
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occlusion_mask = cv2.resize(occlusion_mask, crop_frame.shape[:2][::-1])
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return occlusion_mask
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def create_region_mask(crop_frame : Frame, face_mask_regions : List[FaceMaskRegion]) -> Mask:
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face_parser = get_face_parser()
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prepare_frame = cv2.flip(cv2.resize(crop_frame, (512, 512)), 1)
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prepare_frame = numpy.expand_dims(prepare_frame, axis = 0).astype(numpy.float32)[:, :, ::-1] / 127.5 - 1
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prepare_frame = prepare_frame.transpose(0, 3, 1, 2)
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region_mask = face_parser.run(None,
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{
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face_parser.get_inputs()[0].name: prepare_frame
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})[0][0]
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region_mask = numpy.isin(region_mask.argmax(0), [ FACE_MASK_REGIONS[region] for region in face_mask_regions ])
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region_mask = cv2.resize(region_mask.astype(numpy.float32), crop_frame.shape[:2][::-1])
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return region_mask
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