Thanks so much. I imagined it might work well with landscape and hadn’t had a chance to try it. Nice!
Wow, that’s a gem, thanks for sharing!
From the original samples it seems that the use of wide angle lenses and the distortion that comes from those help in making the images pop, too. Apart from that the look is matched quite well with those processing instructions.
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I worked through this tutorial yesterday without any problems, and wanted to try again today.
However, when I apply the local contrast step, it results in unmistakable panels or quadrant lines showing on my photos – see attached image. What is causing this?
g/mic settings: Details->Simple local contrast
edge sensitivity 25
iterations 1
paint effect 50
channels luminance only
pre-gamma 1.00
post-gamma 1.20
all luminance masks are set to 1.00
parallel processing = auto
Cheers,
Dave
It is a problem with the filter not working well with parallel processing.t the turning off parallel processing or leave gamma settings at 1
Cheers Iain. Turning off the parallel processing cleared the problem.
Many thanks,
Dave
Had the same problem with the simple contrast filter. Only after turning parallel processing off, did the tile artifact vanish.
In addition: The 1% rule for the smoothing algorithm works fine for smaller images. For larger ones (3000px+) you can bump this up. Did you make similar experiences?
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I plan to add the gmic command (and any others I find for gmic) to our github scripts repo. 
Is it possible to see photos before and after?
Are the before/after images not showing up for you? Do you mean in the article or from others comments?
From others.
Wow, the effect on your picture reminds me of the adobe product’s results which are hip nowadays. Maybe they are using something similar in the background, because that community doesn’t want to get any realism anyway. 
If I’m not wrong something like this should also be possible using wavelets decompose, right?
Because basically we are separating the details from the “rest” or “residual” and then working on the residual…
This is basically started with a high/low frequency separation. So yes, it’s the same fundamental idea as wavelets. A wavelet residual tends to be much more coarse than the lowpass used here, though.
Thanks for your advice, everyone. Now I owe you an example! Sguyader’s “new active layer” suggestion works perfectly for me.
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