import cv2
import numpy as np
import os
import glob

def IOU(pred, label):
    Iand1 = np.sum(label[:, :] * pred[:, :])
    Ior1 = np.sum(label[:, :]) + np.sum(pred[:, :]) - Iand1
    IoU1 = Iand1 / Ior1
    return IoU1

model_name = 'u2netp'

mask_dir = os.path.join(os.getcwd(), 'test_data', model_name + '_results' + os.sep)
label_dir = os.path.join(os.getcwd(), 'train_data', 'DUTS', 'DUTS-TR', 'miou_gt' + os.sep)
mask_name_list = glob.glob(mask_dir + os.sep + '*')
label_name_List = glob.glob(label_dir + os.sep + '*')

for mask_name, label_name in mask_name_list, label_name_List:
    mask = cv2.imread(mask_name, cv2.IMREAD_GRAYSCALE)
    label = cv2.imread(label_name, cv2.IMREAD_GRAYSCALE)
    h = mask.shape[0]
    w = mask.shape[1]
    for i in range(h):
        for j in range(w):
            if mask[i][j] <= 127:
                mask[i][j] = 0
            if mask[i][j] > 127:
                mask[i][j] = 1
            if label[i][j] <= 127:
                label[i][j] = 0
            if label[i][j] > 127:
                label[i][j] = 1
            iou = IOU(mask, label)
            print(iou)