sshuair / torchsat Goto Github PK

🔥TorchSat 🌏 is an open-source deep learning framework for satellite imagery analysis based on PyTorch.

Home Page: https://torchsat.readthedocs.io

License: MIT License

Python 99.68% Dockerfile 0.32%

pytorch deep-learning satellite satellite-imagery torchvision remote-sensing data-augmentation classification semantic-segmentation

torchsat's Issues

what does 'ts' mean?

$ cd  tests/classification/      
$ ts make-mask-cls --filepath T51RTQ_20200513T023551_TCI.tif --width 128 --height 128 --outpath ./patched

newbie, found this command in https://torchsat.readthedocs.io/en/latest/tutorials/image-classification.html , however there is no ts or make-mask-cls command?

Spelling

On the first line of installation.rst, Installation is misspelled. Also the exsamples directory should be examples. :)

pretrained models?

Dear @sshuair , thanks for this great work :)

do you have any pre-trained models for segmentation and detection?

Thanks!

Best regards

Can I contribute to Retina-Net?

About noise

It's a good answers about your to-do.
https://stackoverflow.com/questions/22937589/how-to-add-noise-gaussian-salt-and-pepper-etc-to-image-in-python-with-opencv

and this,
https://gist.github.com/oeway/2e3b989e0343f0884388ed7ed82eb3b0

where can get the dataset in the document example

where can get the example data.

What does "target" mean in Seg*.call(self,img,target)?

For example:

class SegResize(object):
def __ init __(self, size):
if isinstance(size, int):
self.size = (size, size)
else:
self.size = size
def __ call __(self, img, target):
return F.resize(img, self.size), F.resize(target, self.size, Image.NEAREST)

Hello, I was wondering if I could pass the "img" parameter only? Because in the F.resize function, it checks if target is None. So, it will throw an exception if I pass the "target" parameter by None.

Thanks for your sharing anyway.

UNet input size dimension does not match error

code

import torch
from torchsat.models.segmentation import unet34

model = unet34(2)
inputs = torch.randn((1,3,800,800))
outputs = model(inputs)

error message:

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-7-62f9f3e6e8e0> in <module>
      1 model = unet34(2)
      2 inputs = torch.randn((1,3,800,800))
----> 3 outputs = model(inputs)

/usr/local/lib/python3.6/site-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    491             result = self._slow_forward(*input, **kwargs)
    492         else:
--> 493             result = self.forward(*input, **kwargs)
    494         for hook in self._forward_hooks.values():
    495             hook_result = hook(self, input, result)

/usr/local/lib/python3.6/site-packages/torchsat-0.0.1-py3.6.egg/torchsat/models/segmentation/unet.py in forward(self, x)
    172         center = self.center(pool)
    173 
--> 174         dec5 = self.dec5(torch.cat([center, conv5], 1))
    175 
    176         dec4 = self.dec4(torch.cat([dec5, conv4], 1))

RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 1. Got 24 and 25 in dimension 2 at ../aten/src/TH/generic/THTensor.cpp:711
``

Is this project dead?

Hi,

Are there any plans for continuing development on this project or is it dead?

Thanks.

您好！关于该库读取tif的问题

首先非常感谢您为深度学习在遥感图像的应用做的贡献。
其次，我在拜读您的源码：torchvision-enhance/torchvision_x/transforms/functional.py 时
发现有关 tifffile 的相关API还没有出现在源码当中，我印象里仅仅凭cv2好像是无法解决遥感影像的多通道问题。所以想询问一下该库现在是否可以读取tif的数据（如“sample-data/MUL_AOI_4_Shanghai_img1920.tif”）

感谢！

sshuair / torchsat Goto Github PK

torchsat's Issues

what does 'ts' mean?

Spelling

pretrained models?

Can I contribute to Retina-Net?

About noise

where can get the dataset in the document example

What does "target" mean in Seg*.call(self,img,target)?

UNet input size dimension does not match error

Is this project dead?

您好！关于该库读取tif的问题

Recommend Projects

React

Vue.js

Typescript

TensorFlow

Django

Laravel

D3

Recommend Topics

javascript

web

server

Machine learning

Visualization

Game

Recommend Org

Facebook

Microsoft

Google

Alibaba

D3

Tencent