Comments (6)
Same as the training dataset type
from remote-sensing-image-semantic-segmentation.
Me too!!!do u solve this problem??
from remote-sensing-image-semantic-segmentation.
Same as the training dataset type
How can other datasets be adjusted to the same format as the training set?
from remote-sensing-image-semantic-segmentation.
Of course, you can adjust the palette and one-hot preprocessing of the dataset.
from remote-sensing-image-semantic-segmentation.
当然,您可以调整数据集的调色板和 one-hot 预处理。
非常感谢您的回复!!!我直接跑的预测,用您的模型,发现是蓝色的,是因为one-hot 预处理不对吗?
from remote-sensing-image-semantic-segmentation.
You need to make sure that your data is of the same category as my predefined category, and the palette is the same. For rivers and lakes, the processed colored semantic regions are blue. Please note that the output result of the network is the predicted segmentation map, and then according to the color of the palette corresponding to the fixed category number, the map of different color semantics is generated.
from remote-sensing-image-semantic-segmentation.
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from remote-sensing-image-semantic-segmentation.