Asked
Resolved Resolved by JustinRatliff!

Detect Multiple Face From EZ Blocky Logic

Dear: i want to detect the multiple face and on detection the audio response of the JD humanoid robot, like if he seems my face he respond l see my creators, if he sees any other one he replay according to that person, The response from robot something like .... he is not my creator, if he see any other face/object/thing response according that thing/person/object , i am facing issue to do this from block y drag and drop is there is anyone who guide me ? i am working from 2 months still no good results, kindly guide me from scratch because i will do lots of working and everything is mixed and i am a bit confused because i worked with every module, kindly guide me from scratch.


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#3  

For us to help you further, I think you need to upload your entire ARC project as a Public App, that way we can download it and try it out and attempt to offer corrections.  I think there must be something you are still struggling to understand and the best way to help you is to see your entire project.

To save it in ARC go to File > use the Save option in the middle for Synthiam AppStore > make sure it is a Public App.  Let us know once you post it.

#4  

Hello @Uzair,

Without your project I took a shot at creating one of my own for you to test.  I did a video demo because what you want to combine is KNOWN face recognition - which is the trained objections in ARC for trained faces along with the general Face detection for face tracking to show that an UNKNOWN face has been detected.

Here is a project file - app you can download to test

There are probably other solutions, because once you understand what you need to enable how Trained Objects work and how Face tracking works then it just becomes a logic problem of how to deploy and combine using them for the outcome you want.

#5  

Thank You Justin Ratliff for making video for me, it is helpful for me.Now i have clear all the problems which i am facing, this video exact fit for my present problem. Thanks again Justin Ratliff.

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#6   — Edited

hey Justin Ratliff copied your code, works very well, thanks -  on the camera, I checked face and object