Well thank you for that detailed explanation. It is certainly an interesting mix of software. Someone should come up with a name for this. A simple, descriptive name would be a good thing. Tensorflow/Darknet/YOLO is a bit of a mouthful to say. Perhaps "TiDY" or "DitTY"

--Thomas

SUCCESS!

I finally have DTY (Darknet/Tensorflow/YOLO2) working with ARC. DTY classifies/identifies an object. I added code to then output what it sees to a text file. Then I read the text into ARC, and finally parse it and assigns each atribute to a variable. The attributes are

• OBJECT
• CONFIDENCE
• TOP
• BOTTOM
• LEFT
• RIGHT
• HCENTER
• VCENTER
• TIMESTAMP

Quote:

If at first you don't succeed, code, code again!

@thomas! Great job! I look forward to details and videos !

Congratulations @thomasfromla ! That is no small feat to accomplish! It sounds like you did it a very efficient way as well (write text file/read in - I love that method).

I hope you'll get to share more on how your did it, I'd like to follow in your foot steps and experiment. With TensorFlow I assume you used the 'CPU' install instead of the GPU install?

I was pricing a multi unit GPU system the other day...PHEEWWW! I was not prepared for those prices!

@thomasfromla Man this is great...really looking forward to see how you accomplished!:D

@thomasfromla: Good job. Compiling Yolo is quick, regarding Tensorflow: How long it took to compile ? Did you enabled AVX2 extensions ?

(write text/read in) pointed by Justin follows the KISS principle !

I'm working on a different integration, not so simple .. so no results yet.

@ptp

Thanks.

I'm running it from Atom/Python with a few changes.

Best of luck on your implementation!

PS. I've gotten my robot to physically point at requested objects.

Me: do you see a dog? Robot: yes. It's on my left. (Points to the dog.)