# Copyright (c) Alibaba, Inc. and its affiliates. import cv2 from easycv.predictors.builder import PREDICTORS from .base import PredictorV2 face_contour_point_index = [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32 ] left_eye_brow_point_index = [33, 34, 35, 36, 37, 38, 39, 40, 41, 33] right_eye_brow_point_index = [42, 43, 44, 45, 46, 47, 48, 49, 50, 42] left_eye_point_index = [66, 67, 68, 69, 70, 71, 72, 73, 66] right_eye_point_index = [75, 76, 77, 78, 79, 80, 81, 82, 75] nose_bridge_point_index = [51, 52, 53, 54] nose_contour_point_index = [55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65] mouth_outer_point_index = [84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 84] mouth_inter_point_index = [96, 97, 98, 99, 100, 101, 102, 103, 96] @PREDICTORS.register_module() class FaceKeypointsPredictor(PredictorV2): """Predict pipeline for face keypoint Args: model_path (str): Path of model path config_file (str): config file path for model and processor to init. Defaults to None. batch_size (int): batch size for forward. device (str): Support 'cuda' or 'cpu', if is None, detect device automatically. save_results (bool): Whether to save predict results. save_path (str): File path for saving results, only valid when `save_results` is True. pipelines (list[dict]): Data pipeline configs. """ def __init__(self, model_path, config_file, batch_size=1, device=None, save_results=False, save_path=None, pipelines=None): super(FaceKeypointsPredictor, self).__init__( model_path, config_file, batch_size=batch_size, device=device, save_results=save_results, save_path=save_path, pipelines=pipelines) self.input_size = self.cfg.IMAGE_SIZE self.point_number = self.cfg.POINT_NUMBER def preprocess(self, inputs, *args, **kwargs): batch_outputs = super().preprocess(inputs, *args, **kwargs) self.img_metas = batch_outputs['img_metas'] return batch_outputs def postprocess(self, inputs, *args, **kwargs): results = [] points = inputs['point'].cpu().numpy() poses = inputs['pose'].cpu().numpy() for idx, point in enumerate(points): h, w, c = self.img_metas[idx]['img_shape'] scale_h = h / self.input_size scale_w = w / self.input_size point = point.reshape((self.point_number, 2)) for index in range(len(point)): point[index][0] *= scale_w point[index][1] *= scale_h results.append({'point': point, 'pose': poses[idx]}) return results def show_result(self, img, points, scale=4.0, save_path=None): """Draw `result` over `img`. Args: img ( ndarray ): The image to be displayed. result (list): The face keypoints to draw over `img`. scale: zoom in or out scale save_path: path to save drawned 'img' Returns: img (ndarray): Only if not `show` or `out_file` """ image = cv2.resize(img, dsize=None, fx=scale, fy=scale) def draw_line(point_index, image, point): for i in range(len(point_index) - 1): cur_index = point_index[i] next_index = point_index[i + 1] cur_pt = (int(point[cur_index][0] * scale), int(point[cur_index][1] * scale)) next_pt = (int(point[next_index][0] * scale), int(point[next_index][1] * scale)) cv2.line(image, cur_pt, next_pt, (0, 0, 255), thickness=2) draw_line(face_contour_point_index, image, points) draw_line(left_eye_brow_point_index, image, points) draw_line(right_eye_brow_point_index, image, points) draw_line(left_eye_point_index, image, points) draw_line(right_eye_point_index, image, points) draw_line(nose_bridge_point_index, image, points) draw_line(nose_contour_point_index, image, points) draw_line(mouth_outer_point_index, image, points) draw_line(mouth_inter_point_index, image, points) size = len(points) for i in range(size): x = int(points[i][0]) y = int(points[i][1]) cv2.putText(image, str(i), (int(x * scale), int(y * scale)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1) cv2.circle(image, (int(x * scale), int(y * scale)), 2, (0, 255, 0), cv2.FILLED) if save_path is not None: cv2.imwrite(save_path, image) return image