Face embedding for face identification in Python

Accelerated Computing Intelligent Video Analytics DeepStream SDK
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Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) NVIDIA GeForce RTX 4070 Laptop GPU
• DeepStream Version 7.0
• JetPack Version (valid for Jetson only)
• TensorRT Version 8.6.1.6-1+cuda12.0
• NVIDIA GPU Driver Version (valid for GPU only) 535.183.06
• Issue Type( questions, new requirements, bugs) questions
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)

I need to implement a face identification in Python.
The deepstream-mdx-perception-app describes very well what I am trying to do:

• Retail item recognition pipeline detects retail items from a video and extracts the embedding vector out of every detection bounding box. The embedding vector can form a query to a database of embedding vectors and find the closest match.

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The figure below also describes the idea.

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Is there any Python application that I can use as base?
What model could I use for embedding face?

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No. It is just another programming language, the logic is the same. You may refer to the other python samples NVIDIA-AI-IOT/deepstream_python_apps: DeepStream SDK Python bindings and sample applications (github.com) and customized the python app by yourself.

There is no pretrained face embeding model from TAO. You can refer to Retail Object Recognition | NVIDIA NGC for how to train the model by yourself. For more details, please raise topic in the TAO forum. Latest Intelligent Video Analytics/TAO Toolkit topics - NVIDIA Developer Forums

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Thank you!

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