Comments (7)
Run python3 eval.py, no SR picture. Only the following sentences, can you achieve it? What do I need to change?
Namespace(chop_forward=True, gpu_mode=True, gpus=1, input_dir='Input', model='models/DBPN_x4.pth', model_type='DBPNL', output='Results/', seed=123, self_ensemble=True, testBatchSize=1, test_dataset='Set5_LR_x4', threads=1, upscale_factor=4)
===> Loading datasets
===> Building model
Pre-trained SR model is loaded
from dbpn-pytorch.
There are several models in the paper. Perhaps the X4 model that the author gives is not the best one. just guess.
from dbpn-pytorch.
@liuiyilang when i just use trained model weights "DBPN_x2.pth", I get wrong result, the result picture is green, did u get normall result?
from dbpn-pytorch.
@liuiyilang when i just use trained model weights "DBPN_x2.pth", I get wrong result, the result picture is green, did u get normall result?
I got the normal results ,but seems the model doesn't performs that good with psnr.
from dbpn-pytorch.
Run python3 eval.py, no SR picture. Only the following sentences, can you achieve it? What do I need to change?
Namespace(chop_forward=True, gpu_mode=True, gpus=1, input_dir='Input', model='models/DBPN_x4.pth', model_type='DBPNL', output='Results/', seed=123, self_ensemble=True, testBatchSize=1, test_dataset='Set5_LR_x4', threads=1, upscale_factor=4)
===> Loading datasets
===> Building model
Pre-trained SR model is loaded
Sorry i can't help you,because i use my own dataloader and test code,while i just use dbpn.py and base_networks.py provided.
from dbpn-pytorch.
@liuiyilang thx, I have fixed it
from dbpn-pytorch.
I try to test the model on Set 5 X4 with provided trained models.When i calculate the psnr in RGB channel i got psnr =30.xxx which seems not right.When i calculate the psnr in Y channel,i got psnr = 31.xxx. Both of them seems lower than psnr presented in the paper(32.47)γIs there anyone got the results presented in the paper?
Have you dealt with it?And what's the PSNR of your result?Thank you.
from dbpn-pytorch.
Related Issues (20)
- What's class D_DownBlock(torch.nn.Module) mean?What's num_stages mean?
- The question about train. HOT 3
- I inserted some layers into dbpn.py,and it can be trained successfully.But failed to test. HOT 1
- I inserted some layers into dbpn.py,and it can be trained successfully.But failed to test.
- How to use correctly
- Question in main.py HOT 1
- normalization for DBPNITER
- cannot download zip file in any way
- I trained and eval got black images HOT 3
- what is the size of input ?
- Can't get the same results as in the article with pretrained model. HOT 2
- About training on GAN HOT 1
- Is it appropriate that the last convolutional layer of DBPN has no activation function?
- Training on other datasets HOT 1
- Did you initialize all models with zero 'a'?
- what's real critertion in main.py?
- Questions about the setting of network when denoising.
- Doubt about the patch_size parameter
- Discriminator pretrained model missing
- no valid convolution algorithms available in CuDNN
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
π 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. πππ
-
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 β€οΈ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from dbpn-pytorch.