Comments (7)
Hi, check this issue. #19
Thanks.
from caffe-vdsr.
Thanks,
I seems that you have applied around 17 to 18 different transformation, can you share the training file, where these transformation occurs.
Cheers,
from caffe-vdsr.
Sorry, I can't fine the code of data augmentation right now since I wrote this code long ago.
You can write it by yourself. It's very simple in matlab.
Like this:
image_rotate = imrotate(image,rotate_angle);
image_flip = flip(image,2);
image_translate = immove(image,translate_x,translate_y);
image_zoom = imresize(image,zoom_scale,'bicubic');
from caffe-vdsr.
I am doing it in matlab, but I am not getting the same results as yours. Thats why I asked for the specific data augmentation types.
cheers.
from caffe-vdsr.
How many training samples you used during training?
And what's your solver setting?
from caffe-vdsr.
The solver setting is same as yours, and the number of samples are around 600k from (582 data augmented, flipped only from 291 images)
from caffe-vdsr.
Hi, you should modify the solve setting since your number of training samples is different from mine.
Check the readme I just updated, and do training again.
I hope this helps.
Thanks!
from caffe-vdsr.
Related Issues (20)
- Multi-Scale Implementation HOT 10
- Caffemodels corresponding to VDSR_official.mat and VDSR_ADAM.mat HOT 3
- This version isn't use the clip-gradients? HOT 2
- about the data sample HOT 3
- loss during training HOT 9
- Test Function at Caffe HOT 2
- Error in VDSR_Matconvnet (line 15) HOT 4
- A display bug in Demo_SR_Conv.m ?
- how to get high resolution output by using my own image data?
- Questions about parameters HOT 2
- sr_psnr less than bicubic psnr HOT 6
- Test code in pyCaffe/C++ HOT 7
- About learning rate HOT 2
- File for training data is offline – alternative location? HOT 2
- Data Preprocessing HOT 2
- About GPU load
- loss nan
- Thanks and some questions HOT 1
- Questions about usage HOT 1
- Some questions about DEM(>255)
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from caffe-vdsr.