I hope you are having a good time working on the projects in the frame of SOCIS,
a listed here: https://socis.esa.int/projects/
Could you please provide a link to your public code repository to be posted
on the website (if available)?
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@vicente-gonzalez-ruiz sir, I have used a set of images data to generate its downsampled images X(0.5) and trained my model to generate that X2(original) image from downsampled images.
basically, this contains 3 steps
1) converting original images to X(0.5) (256x256)downsampled images.
2) generating the X(2) (512x512) images from the model
3) comparing it with original images and updating model to reduce loss.
output/lena_processed_2X.png. My question are: why the resolution of the output images is 2048 x 1536? And ... which is the difference between
[vruiz@pluton output] (master) pwd /home/vruiz/Super-resolution_Imaging/model/output [vruiz@pluton output] (master) file lena_original_2X.png lena_original_2X.png: PNG image data, 2048 x 1536, 8-bit/color RGB, non-interlaced
run_model.pyand (I'm always referring to
lena, if you can, ignore by now the other image, please, it consumes a lot of CPU and now I'm only interested in
lena). The input image of the module should be
lenawith 256x256 and the output
lenawith 512x512 (now, the output has 1024x1024). As I commented before, you should use the DWT for obtaining the 256x256 version. Is this so?
output/lena_pywt_1X.pngis the input of the up-scaler? If so, why is a grayscale image? I don't see how are you able to input a grayscale image and output a color one ...