im using NLP since nearly a year now and loving it. But quiet often i get quiet different Results on the Sam Batch of Images, even in the same Light Conditions.
And sometimes, i just dont get a proper conversion.
Im using a D850, mounted above the Kaiser Film Holder and LED panel.
WB the Film with the Border, shooting RAW, overexpose by 1 Stop.
Using Digital Camera, Basic or Frontier, Pre Sat. 3.
All Images are Rendered seperatly. The first One is just Brilliant, why i Love NLP, but the others are quiet off. (Image 1, 3, 5, 6 - are captured exactly at the same window)
I Would say 30% of the time it works, and 70% its quiet off. Is this normal or what could i improve or change?
Thanks in advance for you Help. And a huuuuuuuuuuuuge preach to your work here - NLP is since years the best Way to get this beuatifull colours out of the Negatives for me
In this case, you could take the conversion you do like, and use the “sync scene” feature in batch mode to bring the same conversion over to the other images.
Right now (as of v2.2), each image is evaluated individually, so based on what is in the scene, it could be evaluated differently. I’m working on analysis for future versions that takes into consideration more context from the entire roll, so it should be able to produce more consistent initial renderings.
first of all, thanks for your time and patience <3
Yes im familiar with the “Sync scene” feauture. So far i use it as you mentioned it.
Good to know there is a feautre coming up and to know that every image is analyised by its own.
On the other Side, im wondering why my colours are so often off and sometimes it hits on Point - even in the same Light scenario (same exposure, same film etc).
I would love to eliminate the mistakes, to get the right colours. As i dont get it with the old women, its not getting the right colours. Even if i tweak a lot and move the sliders as good as i can.
In case its just how it works sometimes, depending on the Light situation, than i deal with it and train my colour tweak skills further. But in case you have an idea why its still often off, after converting. im curios.
