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