recognition_utils.py 文件源码

def plot_confusion_matrix(cm, clf_target_names, title='Confusion matrix', cmap=plt.cm.jet):
    target_names = map(lambda key: key.replace('_','-'), clf_target_names)

    for idx in range(len(cm)): 
        cm[idx,:] = (cm[idx,:] * 100.0 / np.sum(cm[idx,:])).astype(np.int)

    plt.imshow(cm, interpolation='nearest', cmap=cmap)
    # plt.matshow(cm)
    plt.title(title)
    plt.colorbar()
    tick_marks = np.arange(len(clf_target_names))
    plt.xticks(tick_marks, target_names, rotation=45)
    plt.yticks(tick_marks, target_names)
    # plt.tight_layout()
    plt.ylabel('True label')
    plt.xlabel('Predicted label')