使用numpy计算miou指标

使用numpy计算miou指标的实现：

import os
from os.path import join, exists
import cv2
import numpy as np
from tqdm import tqdm


def cal_miou(pred_mask, mask, n_classes=2, smooth=1e-10):
    iou_per_class = []
    for clas in range(0, n_classes):  # loop per pixel class
        true_class = pred_mask == clas
        true_label = mask == clas

        if true_label.sum() == 0:  # no exist label in this loop
            iou_per_class.append(np.nan)
        else:
            intersect = np.bitwise_and(true_class, true_label).sum()
            union = np.bitwise_or(true_class, true_label).sum()

            iou = (intersect + smooth) / (union + smooth)
            iou_per_class.append(iou)
    return np.nanmean(iou_per_class)


def eval(pred_dir, gt_dir):
    files = [i for i in os.listdir(gt_dir)]
    files.sort()

    mious = []
    for f in tqdm(files):
        fp = join(pred_dir, f)
        pred_mask = cv2.imread(fp, -1)
        fg = join(gt_dir, f)