| 72 | return feed_dict |
| 73 | |
| 74 | def f_score(label, predict, dist_label, dist_pred, threshold): |
| 75 | num_label = label.shape[0] |
| 76 | num_predict = predict.shape[0] |
| 77 | |
| 78 | f_scores = [] |
| 79 | for i in range(len(threshold)): |
| 80 | num = len(np.where(dist_label <= threshold[i])[0]) |
| 81 | recall = 100.0 * num / num_label |
| 82 | num = len(np.where(dist_pred <= threshold[i])[0]) |
| 83 | precision = 100.0 * num / num_predict |
| 84 | |
| 85 | f_scores.append((2*precision*recall)/(precision+recall+1e-8)) |
| 86 | return np.array(f_scores) |
| 87 | |
| 88 | # Load data |
| 89 | data = DataFetcher(FLAGS.data_list) |