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| import numpy as np | |
| import torch | |
| import kornia as K | |
| from kornia.core import Tensor | |
| from kornia.contrib import FaceDetector, FaceDetectorResult, FaceKeypoint | |
| print('Loading Face Detector...') | |
| face_detection = FaceDetector() | |
| print('DONE') | |
| def detect_face(input): | |
| # Preprocessing | |
| img = K.image_to_tensor(np.array(input), keepdim=False) | |
| img = K.color.bgr_to_rgb(img.float()) | |
| with torch.no_grad(): | |
| dets = face_detection(img) | |
| return [FaceDetectorResult(o) for o in dets[0]] | |
| def process_face(dets): | |
| vis_threshold = 0.8 | |
| faces = [] | |
| hairs = [] | |
| for b in dets: | |
| if b.score < vis_threshold: | |
| continue | |
| reye_kpt=b.get_keypoint(FaceKeypoint.EYE_RIGHT).int().tolist() | |
| leye_kpt=b.get_keypoint(FaceKeypoint.EYE_LEFT).int().tolist() | |
| rmou_kpt=b.get_keypoint(FaceKeypoint.MOUTH_RIGHT).int().tolist() | |
| lmou_kpt=b.get_keypoint(FaceKeypoint.MOUTH_LEFT).int().tolist() | |
| nose_kpt=b.get_keypoint(FaceKeypoint.NOSE).int().tolist() | |
| faces.append([nose_kpt, | |
| rmou_kpt, | |
| lmou_kpt, | |
| reye_kpt, | |
| leye_kpt | |
| ]) | |
| # point above | |
| top=((b.top_right + b.top_left)/2).int().tolist() | |
| bot=((b.bottom_right + b.bottom_left)/2).int().tolist() | |
| face_h = np.abs(top[1]-bot[1]) | |
| top_margin=[top[0], top[1]-face_h*0.1] | |
| hairs.append([ | |
| top_margin | |
| ]) | |
| return faces, hairs |