| import os |
| import cv2 |
| from torch.utils.model_zoo import load_url |
|
|
| from ..core import FaceDetector |
|
|
| from .net_s3fd import s3fd |
| from .bbox import * |
| from .detect import * |
|
|
| models_urls = { |
| 's3fd': 'https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth', |
| } |
|
|
|
|
| class SFDDetector(FaceDetector): |
| def __init__(self, device, path_to_detector=os.path.join(os.path.dirname(os.path.abspath(__file__)), 's3fd.pth'), verbose=False): |
| super(SFDDetector, self).__init__(device, verbose) |
|
|
| |
| if not os.path.isfile(path_to_detector): |
| model_weights = load_url(models_urls['s3fd']) |
| else: |
| model_weights = torch.load(path_to_detector) |
|
|
| self.face_detector = s3fd() |
| self.face_detector.load_state_dict(model_weights) |
| self.face_detector.to(device) |
| self.face_detector.eval() |
|
|
| def detect_from_image(self, tensor_or_path): |
| image = self.tensor_or_path_to_ndarray(tensor_or_path) |
|
|
| bboxlist = detect(self.face_detector, image, device=self.device) |
| keep = nms(bboxlist, 0.3) |
| bboxlist = bboxlist[keep, :] |
| bboxlist = [x for x in bboxlist if x[-1] > 0.5] |
|
|
| return bboxlist |
|
|
| def detect_from_batch(self, images): |
| bboxlists = batch_detect(self.face_detector, images, device=self.device) |
| keeps = [nms(bboxlists[:, i, :], 0.3) for i in range(bboxlists.shape[1])] |
| bboxlists = [bboxlists[keep, i, :] for i, keep in enumerate(keeps)] |
| bboxlists = [[x for x in bboxlist if x[-1] > 0.5] for bboxlist in bboxlists] |
|
|
| return bboxlists |
|
|
| @property |
| def reference_scale(self): |
| return 195 |
|
|
| @property |
| def reference_x_shift(self): |
| return 0 |
|
|
| @property |
| def reference_y_shift(self): |
| return 0 |
|
|
