def evaluate(embeddings, actual_issame, far_target=1e-3, distance_metric=0, nrof_folds=10): thresholds = np.arange(0, 4, 0.01) if distance_metric == 1: thresholdes = np.arange(0, 1, 0.0025) embeddings1 = embeddings[0::2] embeddings2 = embeddings[1::2] tpr, fpr, accuracy = calculate_roc(thresholds, embeddings1, embeddings2, np.asarray(actual_issame), distance_metric=distance_metric, nrof_folds=nrof_folds) tar, tar_std, far = calculate_tar(thresholds, embeddings1, embeddings2, np.asarray(actual_issame), far_target=far_target, distance_metric=distance_metric, nrof_folds=nrof_folds) acc_mean = np.mean(accuracy) acc_std = np.std(accuracy) return tpr, fpr, acc_mean, acc_std, tar, tar_std, far
def evaluate(l_embds, r_embds, actual_issame, far_target=1e-3, distance_metric=0, nrof_folds=10): thresholds = np.arange(0, 4, 0.01) tpr, fpr, accuracy = calculate_roc(thresholds, l_embds, r_embds, np.asarray(actual_issame), distance_metric=distance_metric, nrof_folds=nrof_folds) tar, tar_std, far = calculate_tar(thresholds, l_embds, r_embds, np.asarray(actual_issame), far_target=far_target, distance_metric=distance_metric, nrof_folds=nrof_folds) acc_mean = np.mean(accuracy) acc_std = np.std(accuracy) return tpr, fpr, acc_mean, acc_std, tar, tar_std, far