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opencv_streamlit_app's Introduction

Deployment TBD

OpenCV_Streamlit_APP

Try to make an online application with Streamlit App combined with modern vision ML technology, YOLO, OpenCV. Deploy it on Azure with CI/CD.

Running Locally

  • create virtual environment in current folder

    virtualenv .venv

  • start virtual environment

    source .venv/bin/activate

  • deactivate virtual environment

    deactivate

Automatically go to virtual vironment in VSCode:

  • first setting all up and activate your virtual environment

  • then choose file --> Preference -->settings select workspace tab then click open setting json icon from top right

  • put this code in

    { "python.terminal.activateEnvInCurrentTerminal": true, "python.defaultInterpreterPath": "/home/ycbq999/face_recognition_venv/bin/python" }

  • see reference [https://www.youtube.com/watch?v=g7bg2ADfx4c&ab_channel=JohnSolly]

Streamlit

  • I include stream tutorial folder called 3_Streamlit_crash_course

  • Streamlit treats multiple apps as pages, you need to make a fold named "pages" exactly to activate this feature. also name 1_,2_,--- infront of each page name so it will detect sequence. Remember that

see reference in udemy [https://www.udemy.com/course/yolo-custom-object-detection/learn/lecture/33903494#notes]

Web Video Streaming

We will first use google colab to train the model

Later we will use azure to train and deploy the model.

-reference [https://learn.microsoft.com/en-us/azure/machine-learning/tutorial-train-model?view=azureml-api-2]

-webrtc may not work in this environment due the security on the network. but still can deploy for image object detection.

HTTPS
streamlit-webrtc uses getUserMedia() API to access local webcams, and this method does not work in an insecure context.

This document says

A secure context is, in short, a page loaded using HTTPS or the file:/// URL scheme, or a page loaded from localhost.

So, when hosting your app on a remote server, it must be served via HTTPS.

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