(self, idx)
| 78 | return len(self.img_paths) |
| 79 | |
| 80 | def __getitem__(self, idx): |
| 81 | |
| 82 | img = load_img(self.img_paths[idx],'BGR') |
| 83 | img_whole_bbox = np.array([0, 0, img.shape[1],img.shape[0]]) |
| 84 | img, img2bb_trans, bb2img_trans, _, _ = \ |
| 85 | augmentation_keep_size(img, img_whole_bbox, 'test') |
| 86 | |
| 87 | cropped_img_shape=img.shape[:2] |
| 88 | img = (img.astype(np.float32)) |
| 89 | |
| 90 | inputs = {'img': img} |
| 91 | targets = { |
| 92 | 'body_bbox_center': np.array(img_whole_bbox[None]), |
| 93 | 'body_bbox_size': np.array(img_whole_bbox[None])} |
| 94 | meta_info = { |
| 95 | 'ori_shape':np.array(self.resolution), |
| 96 | 'img_shape': np.array(img.shape[:2]), |
| 97 | 'img2bb_trans': img2bb_trans, |
| 98 | 'bb2img_trans': bb2img_trans, |
| 99 | 'ann_idx': idx} |
| 100 | result = {**inputs, **targets, **meta_info} |
| 101 | |
| 102 | result = self.normalize(result) |
| 103 | result = self.format(result) |
| 104 | |
| 105 | return result |
| 106 | |
| 107 | def inference(self, outs): |
| 108 | img_paths = self.img_paths |
nothing calls this directly
no test coverage detected