Is there any way to speed up the intial display when graphing (3D primarily) an image’s colours? I know the user manual suggests having dimensions of around 100x100 pixels & sure enough, it’s not too bad with such tiny images. But it’s a real hassle to constantly have to resize each & every image before graphing it.
In my own testing, using Win7 x86 & x64 on an i7 930 at 4.2GHz (constant, no turbo, etc) & 12GB ram, it is horrendously slow to graph just about anything much bigger than about 200x160 pixels. Certainly, when using ‘normal’ sized images everything just seems to grind to a halt while ColorThink thinks about the image colours & ‘optimizes’ them for graphing display.
I know that only 1 CPU core is being used (from watching task manager) and that core is still not being used at 100%, usually it hovers around 85-90% while optimizing the image colours.
So, 3 questions: 1) Are you guys doing anything to make ColorThink Pro 3.x multi-core enabled & utilise those 7 cores that are sitting idle? It’s not like multi-core is anything new these days, not even sure if it’s still actually possible to purchase a single core CPU anymore?
Monaco’s GamutWorks is able to graph the image colours from any image within just a few seconds, if that, with almsot no size restrictions - certainly any image up to about 60MB or around 3000x5500 is displayed with almost no hesitation. There haven’t been any updates to GamutWorks in (I think) at least 5 years so how is it possible Monaco gets the image colours displayed many orders of magnitude faster than ColorThink Pro?
I’ve tried TIF, JPG, GIF, PNG, etc and all seem to be as slow as each other. Apart from resizing images until they’re so small they’re almost not even there, is there anything one can do to improve the graphing display wait times?
Hope you manage to make ColorThink Pro multi-core enabled because at least that would definitely speed things up a bit.
One last thing - just came across an excellent way of displaying image colours when set to deltaE colours on-screen. After setting the destination profile & viewing the deltaE vectors, drag the image back into the graph window & we get the best of both worlds… deltaE coloured vectors but ALSO the original image colours too, so this way we can see not only the deltaE amounts but also what colour the pixels are/where in the colour space the variations are happening. Just give it a try, much easier to do than to explain but I find it really helpful & much more informative as I immediately know exactly which colours have what deltaE changes.