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test_iou.py

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+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)