He's a question:
Can somebody properly explain FFT?
(I'm feeling so inadequate right now. Am I the only one left who doesn't
know what this magical acronym is?)





Ron Ganbar
email: [email protected]
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url: http://ronganbar.wordpress.com/

On Mon, Mar 20, 2017 at 3:42 PM, Magno Borgo <[email protected]> wrote:

> A non-nuke alternative would be to pre-render the FFT using a python
> package like scipy or similar, which already have fast FFT implementations,
> then load/read it inside NUKE. That might help on some pipelines, though
> the inverse edited FFT would still be needed to handled inside Nuke to be
> practical.
>
>
>
>
>
> On Mon, 20 Mar 2017 11:09:30 -0400, jon parker <[email protected]>
> wrote:
>
> Thanks for the responses! I'm not a full-time comper so am unaware of
>> some of the tricks out there, like using ZDefocus.  And I should have
>> added that large kernels / images are involved so the standard
>> convolve node falls behind at the resolution we are working with.
>>
>> Magno, I wasn't aware of your blinkscript.  If I have some time I'll
>> peek at the code.
>>
>> Someone should put together a commercial implementation for Nuke some
>> day, sounds like there is demand out there for it.
>>
>> -Jon
>>
>> On Mon, Mar 20, 2017 at 7:18 AM, Magno Borgo <[email protected]> wrote:
>>
>>> I coded a naive Blinkscript DCT (and inverse) implementation a while
>>> back,
>>> you can check the code and use as a start for a better implementation.
>>>
>>> http://www.nukepedia.com/blink/other/dct-discrete-cosine-transform
>>>
>>> Magno.
>>>
>>>
>>>
>>>
>>>
>>> On Mon, 20 Mar 2017 03:39:40 -0400, Mads Lund <[email protected]>
>>> wrote:
>>>
>>> we did some CPU vs FFT tests aswell, but I can't remember the exact
>>> kernel
>>> size where FFT started to be more efficient, but it was rather low. On
>>> the
>>> flip side Convolve on the GPU seem to have some memory problems and (at
>>> least for us) cause some random out of memory issues, even on beefy
>>> cards.
>>>
>>> We found that using gaming techniques: up-scaling low frequency areas
>>> (then
>>> convolving) and only full convolving of high frequency areas to be to be
>>> quite efficient for the vast majority of our renders where the plate is
>>> gigantic or a large kernel size is needed.
>>> The result is perceptually indistinguishable.
>>>
>>>
>>>
>>>
>>> man. 20. mar. 2017 kl. 06.14 skrev Deke Kincaid <[email protected]>:
>>>
>>>>
>>>> The convolve node was fixed up quite a while a go(4-5 years ago, it is
>>>> what the zdefocus is based on).  In our tests though we still find the
>>>> FFT
>>>> nodes faster on the farm vs convolve in CPU mode.  If you have a gpu
>>>> farm
>>>> then convolve is faster.
>>>>
>>>>
>>>> On Sun, Mar 19, 2017 at 6:23 PM Michael Habenicht <[email protected]>
>>>> wrote:
>>>>
>>>>>
>>>>> The latest version of the convolve node has gpu support.
>>>>>
>>>>> Am 20.03.2017 um 01:20 schrieb jon parker:
>>>>> > Greetings Nuke users,
>>>>> >
>>>>> > I'm just wondering if there are any faster, more robust FFT tools
>>>>> > available for Nuke besides the (hidden) built-in nodes?
>>>>> >
>>>>> > The built-ins do the job, but they are pretty slow and definitely
>>>>> > prone to crashing fairly often.
>>>>> >
>>>>> > Or, alternatively, something that does fast image convolution, some
>>>>> > other way, under the hood could work too.
>>>>> >
>>>>> > Cheers,
>>>>> > Jon
>>>>> > _______________________________________________
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>>>>> >
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>>>
>>> --
>>> Best regards. Mads Hagbarth Lund
>>>
>>>
>>>
>>>
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