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Hello,

I was kindly pointed to an implementation which can do face identity detection. https://docs.opencv.org/master/d5/d86/tutorial_dnn_javascript.html I want to check if my current understanding is correct as i dont have anyone with knowledge who i could ask.

• The first part is to find and extract faces with bounding boxes Once the face(s) is detected - it is extracted(into a mat).

• The second part is to feed the extracted face(s) mat into another network which will produce a vector with unique values which represents the identify for one face.

Is my current understanding correct?

• Does it makes sense to combine these two step into one(model) or should it be seperated?
• Can the second model work for all types of object or does it have to be specific to the object you want to classify(i guess so)?

Thank you again for your help, should be enoug for today - dont want to be too greedy.

Greetings, Holger

Hello,

I was kindly pointed to an implementation which can do face identity detection. https://docs.opencv.org/master/d5/d86/tutorial_dnn_javascript.html I want to check if my current understanding is correct as i dont have anyone with knowledge who i could ask.

• The first part is to find and extract faces with bounding boxes Once the face(s) is detected - it is extracted(into a mat).

• The second part is to feed the extracted face(s) mat into another network which will produce a vector with unique values which represents the identify for one face.

Is my current understanding correct?

• Does it makes sense to combine these two step into one(model) or should it be seperated?
• Can the second model work for all types of object or does it have to be specific to the object you want to classify(i guess so)?

Thank you again for your help, should be enoug enougj for today - dont want to be too greedy.

Greetings, Holger

Hello,

I was kindly pointed to an implementation which can do face identity detection. https://docs.opencv.org/master/d5/d86/tutorial_dnn_javascript.html I want to check if my current understanding is correct as i dont have anyone with knowledge who i could ask.

• The first part is to find and extract faces with bounding boxes Once the face(s) is detected - it is extracted(into a mat).

• The second part is to feed the extracted face(s) mat into another network which will produce a vector with unique values which represents the identify for one face.

Is my current understanding correct?

• Does it makes sense to combine these two step into one(model) or should it be seperated?
• Can the second model work for all types of object or does it have to be specific to the object you want to classify(i guess so)?

Thank you again for your help, should be enougj enough for today - dont want to be too greedy.

Greetings, Holger