dr's Issues
GMSV algorithm?
Can you share the code of the GMSV algorithm in the article, not in the conference paper?
RandomCrop如何导入
您好,可以麻烦问一下这个怎么导入嘛?我搜不到这个库呀?
from transform.transforms_group import RandomCrop
我运行代码,一直在这个地方报错是怎么回事呢?
if self.transform is not None: # train
info = self.hr_transform(info)
报错如下
File "E:\MyUse\CVcode\DR-main\data_process.py", line 91, in getitem
info = self.hr_transform(info)
File "D:\Soft\Anaconda\envs\pytorchgpu_38\lib\site-packages\torchvision\transforms\transforms.py", line 60, in call
img = t(img)
File "D:\Soft\Anaconda\envs\pytorchgpu_38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "D:\Soft\Anaconda\envs\pytorchgpu_38\lib\site-packages\torchvision\transforms\transforms.py", line 586, in forward
width, height = F._get_image_size(img)
File "D:\Soft\Anaconda\envs\pytorchgpu_38\lib\site-packages\torchvision\transforms\functional.py", line 67, in _get_image_size
return F_pil._get_image_size(img)
File "D:\Soft\Anaconda\envs\pytorchgpu_38\lib\site-packages\torchvision\transforms\functional_pil.py", line 26, in _get_image_size
raise TypeError("Unexpected type {}".format(type(img)))
TypeError: Unexpected type <class 'list'>
there is no U_Net_Cut model in network file?
Can you update the files?
about the number of epochs
您好,请问在第一阶段训练中,epoch数真的是30000吗?
Code Issue?
extractor = ModelOutputs(cls_net)
features, fc_output = extractor(cls_input)
cam_all_sr = {'size256': [], 'size128': [], 'size64': [], 'size32': []}
for batch in range(fc_output.shape[0]):
device = fc_output[batch].device.index
index = np.argmax(fc_output[batch].cpu().data.numpy())
if index == 0:
one_hot = np.zeros((1, fc_output[batch].size()[-1]), dtype=np.float32)
one_hot[0][0] = 1
if index > 0:
one_hot = np.ones((1, fc_output[batch].size()[-1]), dtype=np.float32)
one_hot[0][0] = 0
if batch == 0:
one_hot_all = Variable(torch.from_numpy(one_hot).cuda(device), requires_grad=True)
else:
one_hot_all = torch.cat((Variable(torch.from_numpy(one_hot).cuda(device), requires_grad=True), one_hot_all), 0)
if the index of batches is the same, there is no problem. But if they are different, it calculates the opposite loss between one_hot_all and fc_output.
Example:
fc_output one_hot_all
[[0.9, 0.1, 0.1, 0.1, 0.1] [[1, 0, 0, 0, 0]
[0.8, 0.2, 0.2, 0.3, 0.4]] [1, 0, 0, 0, 0]] There is no problem.
fc_output one_hot_all
[[0.2, 0.1, 0.1, 0.1, 0.8] [[0, 1, 1, 1, 1]
[0.3, 0.2, 0.7, 0.3, 0.4]] [0, 1, 1, 1, 1]] There is no problem.
fc_output one_hot_all
[[0.9, 0.1, 0.1, 0.1, 0.7] [[0, 1, 1, 1, 1]
[0.3, 0.2, 0.4, 0.9, 0.4]] [1, 0, 0, 0, 0]] There is problem here because of this line torch.cat((Variable(torch.from_numpy(one_hot).cuda(device), requires_grad=True), one_hot_all), 0).
should be one_hot_all = torch.cat((one_hot_all, Variable(torch.from_numpy(one_hot).cuda(device), requires_grad=True)), 0) ???
Thanks
This is not the right code for an indicated article. Can you share the updated code?
MultiScale_Intergrate should not remove the grad_fn?
Should we use F.interpolate instead of resizing it to prevent grad_fn disapeering?
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.