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seanet_torch's Issues

RuntimeError: Expected 3D (unbatched) or 4D (batched) input to conv2d, but got input of size: [2, 8, 3, 512, 512]

Dear authors,

I trivially copied the file and instantiated the model as:

torch_device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
print('Using device:', torch_device)
model = SEANet(num_classes=1)  # the same error with a different num_classes
print(summary(model, (8, 3, 512, 512)))  # the same error with a different batch_size

I got this error:

    343 def forward(self, x):
    344     # VGG
    345     img_H, img_W = x.shape[2], x.shape[3]
-> 347     conv1_1 = self.activ(self.conv1_1(x))

RuntimeError: Expected 3D (unbatched) or 4D (batched) input to conv2d, but got input of size: [2, 8, 3, 512, 512]

Could you help me?

Many thanks for your excellent work.

D

Pre trained weights

Hello,
I can not access the pretrained weights through the current link.
can you provide an alternative link for international people, please.

获取地块边界

您好,有个问题一直困惑我,我看到您论文的结果是有地块边界的,但是我试验了把mask的图像换成边界(把mask换成contour),并没法预测。我也试过直接用边界线当mask,但是这样的mask无法计算dist_contour和contour,也无法进行训练。如果我用面去预测,就只能得到一整块地块的边界,所以我想请问您,如何能得到一小块一小块地块的边界?谢谢您!

图片无法识别

你好,我在训练的时候总是出现图片无法识别的问题,请问这是什么原因呀,我用的是GF2的4波段tif数据。

Snipaste_2024-04-15_17-09-24

不用dist_contour和contour

如果我不用dist_contour和contour会有影响吗?因为我换了数据,生成dist_contour是有问题的,我在arcgispro上打开是灰色的整张图片,所以想去掉dist_contour和contour来试验

Issues with Output

I tested the SEANet model (no changes made); however, the predicted extent mask has a different range. I believe it should be between 0 and 1.

output_

What threshold value have you used to generate binary output from the predicted extent mask?

后处理问题

有两个问题想请教一下
1、预测的第二个输出是[6,1,256,256] 怎么获取边缘的输出
2、预测的mask还是存在地块的粘连,怎么通过后处理获取最终的地块矢量呢 谢谢

结果拼接

请问一下,您有没有可以将预测结果又拼回一整张图片的代码,也就是cai_duobands.py的逆过程,谢谢!

提取边界

您好!我想将mask的数据换成contour的数据,以实现边界的提取,但是我现在预测输出的结果是错误的(如何用原mask,是可以提取出地块的),请问这个模型能否实现边界提取的操作呢?谢谢您!!!

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