NLP v 3.02 performance : how 2000 images in batch mode

NLP 3.02


I have a small business to digitize negative.
but there are several thousand per day
I would like to automate this.
it is enough if i have an average good result per image (NLP standard)
in batch mode this does not work well with NLP.
I am currently working with a workstation and 64 GB Ram
how can I convert e.g. 2000 negative images at the same time in batch mode?

how much RAM (GB) is necessary for smooth work ?

Who can help me?


Hello friends, i am also looking for an answer to pet’s query.
Please do guide. Thanks.

I already have problems when I convert more than 400 images. not all of them are converted, there are always some that remain negative


Hi @pet

This will be greatly improved shortly with v3.0.3… found a way to improve the memory management, so it should allow thousands of conversions at once (the biggest limiting factor will be that Lightroom may be a bit slower when working with these many files at once).


I have about 35,000 negs to digitize!

The most important are negs to be like a medical theatre. Have a dust cleaner and anti-static dust. Colton gloves. If you are not doing this, then forget it!

I use Canon R5 and 100mm macro - profile, settings, constant - everything zero!

I used to shoot in RAW. I used to connect the camera to my computer, but after I found that simply trying and good in the camera is the quickest.

Using RAW is too time-consuming. Shoot the negative you are shooting a photographer when you like with 100% perfection.

Hope you can shoot with images/slides, use the camera, using manual and with no auto, no nothing - Be as perfect out of the camera so there is no need after.

If you do not add 1/3 when you need to, when you can use perfect, then you are going to take a LONG time!

If you are comfortable and good at using the camera, you can go to many, getting 100 per perfect without going on Auto, etc., then this is SO much easier.

Lens at F7=F11. Keep no more than 200 ISO.

If colour, use a CR97+; the light is so important.

I just take them on the card with all the negatives in JPG without needing to perfect them - put them in Lightroom and use Negative Lab Pro 3.

I have Eposn 850. have used a film scanner Noritsu and all kinds - this is what MY best is just what I have told you. I know everyone has their idea. This is just what I do!


is there a timeline for when the long-promised new NLP version will be released? It takes an enormous amount of effort to manage the program crashes when processing many images.

Thank you very much, I look forward to your prompt feedback.


Experimented with converting 15’000 RAW files with NLP in order to see if it can handle such loads.
I noticed the following

  • From start to when NLP asks to apply the conversion (and save converted copies) took less than 8 hours. Started the conversion late in the evening and in the morning, the “apply” moment had been reached.
  • From the start of “apply” to when I canceled the process took about 4 hours, in which about 3000 JPEG images had been exported. Extrapolating this would result in 20 hours for the export!
  • The original RAW files had not been converted, they contained ordinary positive images, but in smaller batches, these are converted into negatives without further issues or interactions.
  • At no time have I seen any limits being reached with processing or memory resources. Load curves as seen in macOS’s activity monitor were fairly low, nevertheless, the fans kicked in at times

As of now, NLP is not ready to process larger batches imo, mainly due to the fact that one has to interact with it half-way in order to actually store the conversions and exported files.

To make NLP ready for unattended processing of larger quantities, I’d welcome to following changes:

  • Do not stop and ask to apply the conversion and export positives.
  • Divide large batches into smaller batches or rearrange processing in a way to make results visible earlier in the process. The goal of such changes is to enable to cancel at an earlier stage, e.g. if one has set the wrong export action, once one has checked the positives.
  • Export positives in more than one format per conversion, add DNG as export format.
  • Custom prefix and suffix

A first step could be to add a section in the manual with recommendations on how to process XL batches.

Tested on a 2019 5K iMac, 3.6 GHz 8-Core Intel Core i9 - Radeon Pro 580X 8 GB - 40 GB 2400 MHz DDR4 - macOS 14.4.1 (23E224) — “caffeinated” in order to keep the Mac from sleeping.