I built up another SD card for this project...got tidl_api and examples to
compile....this set uses opencv 3.2.0....
my camera didn't kick in until segmentation and ssd_multibox .... also
found out it is more responsive using -w 400 instead of -w 1200.

Will keep working with this...again thanks for the link Mark

Andy

On Wed, Jan 16, 2019 at 5:30 AM Mark A. Yoder <[email protected]>
wrote:

> My x15 has an AM5729 on it and it has 2 DSPs and 4 EVEs[1] (Embedded
> Vision Engines).  I don't know much about the EVEs, but I read somewhere
> that each EVE can do 16 multiply accumulates per clock cycle.  The tidl
> gives you some control over which processors (DSP or EVE) works on what
> part of the problem.
>
> I'm often seeing 15 to 30 frames per second wile recognizing objects.
>
> --Mark
>
> [1] http://processors.wiki.ti.com/index.php/EVE
>
> On Thursday, January 10, 2019 at 4:40:06 PM UTC-5, Calvin Slater wrote:
>>
>> That's fantastic!
>>
>> I was just wondering about this a couple weeks ago.
>>
>> I heard the AM5728 had TIDL support this whole time and uses the DSPs
>> right?
>>
>>
>>
>> On Wednesday, 9 January 2019 18:08:28 UTC-8, Mark A. Yoder wrote:
>>>
>>> It was recently pointed out to me that the BeagleBoard-X15 has hardware
>>> that supports Deep Learning
>>> <http://downloads.ti.com/mctools/esd/docs/tidl-api/> and TI has already
>>> created several examples
>>> <http://downloads.ti.com/mctools/esd/docs/tidl-api/example.html> of how
>>> to use it.
>>>
>>> I've created a wiki page
>>> <https://elinux.org/EBC_Exercise_39_Setting_Up_tidl_on_X15> that gives
>>> a quick guide for installing and running the examples.
>>>
>>> https://elinux.org/EBC_Exercise_39_Setting_Up_tidl_on_X15
>>>
>>> All the examples are pretrained and the X15 is just running the
>>> inference engine.  It's been trained to recognize 1000 objects from a live
>>> video stream.
>>> Using a simple webcam, I've shown it several objects (tennis ball,
>>> baseball, coffee mug, beer bottle, etc.) and it has recognized them all.
>>>
>>> I'm impressed.
>>>
>>> Has anyone else played with this? What do you think?
>>>
>>> --Mark
>>>
>>> [image: Items.png][image: Water_bottle.png]
>>>
>>> --
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