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Issue in label dataset of 2018.Lebedev M A, Vizilter Y V, Vygolov O V, et al. Change detection in remote sensing images using conditional adversarial networks #5
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Thank you for providing such useful information, and maybe you found something interesting. I used daifeng2016/End-to-end-CD-for-VHR-satellite-image used this dataset, I have already opened an issue in The label of the dataset is not binary map, maybe you can take a look. If this dataset is not necessary, I recommend you use the LEVIR-CD dataset. Or you can email the author of the dataset for advice, the paper of the dataset is this URL. Please correct me if I made any mistakes. |
Hello, here is another question on this dataset. I downloaded the compressed file and found that the validation set contained only 2998 image pairs, which contradicts the "3000 pairs for validation" as mentioned in the paper. I wonder if I've had the complete file downloaded. Do you encounter the same problem? |
@Bobholamovic |
Hello:
Thank you for sharing resource firstly.
I found the label data such as
"ChangeDetectionDataset\Real\subset\train\OUT\00000.jpg" is not a binary image ,which contain values as following , you can also found it by eyeball 。So it can not be used as organized dataset for training without image preprocess , what is your opinion?
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,
27, 28, 29, 30, 31, 32, 34, 35, 36, 38, 39, 40, 41,
43, 44, 45, 46, 47, 48, 50, 51, 53, 54, 55, 56, 57,
58, 59, 60, 62, 64, 65, 66, 67, 68, 69, 70, 71, 72,
73, 74, 75, 76, 78, 79, 80, 81, 83, 84, 85, 86, 88,
90, 91, 92, 94, 95, 96, 97, 99, 100, 101, 102, 103, 104,
106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118,
119, 121, 122, 123, 124, 125, 127, 128, 129, 130, 131, 132, 133,
134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146,
147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 160,
161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173,
174, 175, 177, 178, 179, 180, 182, 183, 184, 185, 186, 187, 188,
189, 190, 191, 193, 194, 195, 196, 197, 198, 199, 201, 202, 203,
204, 205, 206, 207, 208, 209, 210, 212, 214, 215, 217, 218, 219,
220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232,
233, 234, 235, 236, 237, 238, 240, 241, 242, 243, 244, 245, 246,
247, 248, 249, 251, 252, 253, 254, 255], dtype=uint8)
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