Normalize the training data according to the overlap value. Args: ground_truth_mapping: the raw ground truth mapping array Returns: dist_norm_data: normalized ground truth mapping array
(ground_truth_mapping)
| 7 | |
| 8 | |
| 9 | def normalize_data(ground_truth_mapping): |
| 10 | """Normalize the training data according to the overlap value. |
| 11 | Args: |
| 12 | ground_truth_mapping: the raw ground truth mapping array |
| 13 | Returns: |
| 14 | dist_norm_data: normalized ground truth mapping array |
| 15 | """ |
| 16 | gt_map = ground_truth_mapping |
| 17 | bin_0_9 = gt_map[np.where(gt_map[:, 2] < 0.1)] |
| 18 | bin_10_19 = gt_map[(gt_map[:, 2] < 0.2) & (gt_map[:, 2] >= 0.1)] |
| 19 | bin_20_29 = gt_map[(gt_map[:, 2] < 0.3) & (gt_map[:, 2] >= 0.2)] |
| 20 | bin_30_39 = gt_map[(gt_map[:, 2] < 0.4) & (gt_map[:, 2] >= 0.3)] |
| 21 | bin_40_49 = gt_map[(gt_map[:, 2] < 0.5) & (gt_map[:, 2] >= 0.4)] |
| 22 | bin_50_59 = gt_map[(gt_map[:, 2] < 0.6) & (gt_map[:, 2] >= 0.5)] |
| 23 | bin_60_69 = gt_map[(gt_map[:, 2] < 0.7) & (gt_map[:, 2] >= 0.6)] |
| 24 | bin_70_79 = gt_map[(gt_map[:, 2] < 0.8) & (gt_map[:, 2] >= 0.7)] |
| 25 | bin_80_89 = gt_map[(gt_map[:, 2] < 0.9) & (gt_map[:, 2] >= 0.8)] |
| 26 | bin_90_100 = gt_map[(gt_map[:, 2] <= 1) & (gt_map[:, 2] >= 0.9)] |
| 27 | |
| 28 | |
| 29 | |
| 30 | dist_norm_data = np.concatenate((bin_0_9, bin_10_19, bin_20_29, bin_30_39, bin_40_49, |
| 31 | bin_50_59, bin_60_69, bin_70_79, bin_80_89, bin_90_100)) |
| 32 | |
| 33 | # print("Distribution normalized data: ", dist_norm_data) |
| 34 | print("size of normalized data: ", len(dist_norm_data)) |
| 35 | |
| 36 | return dist_norm_data |
| 37 | |
| 38 | |
| 39 | if __name__ == '__main__': |