Simple object detection app with streamlit

Related tags

Deep Learningopencvaiobject-detectionstreamlit
Overview

object-detection-app

Simple object detection app with streamlit. Upload an image and perform object detection. Adjust the confidence threshold to see how this affects predictions.

Run with Docker

From the root dir:

    docker build -t robmarkcole/object-detection-app .
    docker run -p 8501:8501 robmarkcole/object-detection-app:latest

Then visit localhost:8501

Development

Using devcontainer, see basic python example repo and more advanced repo. Use this streamlit docker template. Note you cannot docker run at the same time as the devcontainer as the ports clash.

References

I took a lot of inspiration from this article by Adrian Rosebrock.

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Comments
  • Camera

    Camera

    Hi

    great project and an inspired one, I would like to know if I want to connect a camera or a phone camera instead of the computer camera , what should I include ? and what steps I need to add or remove?

    appreciate your feedback

    opened by oalharb 1
  • Bump opencv-python from 4.1.2.30 to 4.2.0.32

    Bump opencv-python from 4.1.2.30 to 4.2.0.32

    Bumps opencv-python from 4.1.2.30 to 4.2.0.32.

    Release notes

    Sourced from opencv-python's releases.

    4.2.0.32

    OpenCV version 4.2.0.

    Changes:

    • macOS environment updated from xcode8.3 to xcode 9.4
    • macOS uses now Qt 5 instead of Qt 4
    • Nasm version updated to Docker containers
    • multibuild updated

    Fixes:

    • don't use deprecated brew tap-pin, instead refer to the full package name when installing #267
    • replace get_config_var() with get_config_vars() in setup.py #274
    • add workaround for DLL errors in Windows Server #264
    Commits

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Releases(v0.3)
Owner
Robin Cole
Physics PhD, python, data science, deep learning & space
Robin Cole
GitHub Repository https://streamlit.io/
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