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36 lines
1.1 KiB
36 lines
1.1 KiB
import cv2
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import numpy as np
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import os
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import glob
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def IOU(pred, label):
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Iand1 = np.sum(label[:, :] * pred[:, :])
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Ior1 = np.sum(label[:, :]) + np.sum(pred[:, :]) - Iand1
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IoU1 = Iand1 / Ior1
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return IoU1
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model_name = 'u2netp'
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mask_dir = os.path.join(os.getcwd(), 'test_data', model_name + '_results' + os.sep)
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label_dir = os.path.join(os.getcwd(), 'train_data', 'DUTS', 'DUTS-TR', 'miou_gt' + os.sep)
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mask_name_list = glob.glob(mask_dir + os.sep + '*')
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label_name_List = glob.glob(label_dir + os.sep + '*')
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for mask_name, label_name in mask_name_list, label_name_List:
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mask = cv2.imread(mask_name, cv2.IMREAD_GRAYSCALE)
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label = cv2.imread(label_name, cv2.IMREAD_GRAYSCALE)
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h = mask.shape[0]
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w = mask.shape[1]
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for i in range(h):
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for j in range(w):
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if mask[i][j] <= 127:
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mask[i][j] = 0
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if mask[i][j] > 127:
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mask[i][j] = 1
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if label[i][j] <= 127:
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label[i][j] = 0
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if label[i][j] > 127:
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label[i][j] = 1
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iou = IOU(mask, label)
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print(iou)
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