Real-Time Detection Dashboard App

[rakheshkrishna2005]

Add New Project: Real-Time Detection Dashboard Streamlit App - YOLOv8 + OpenCV

Is your feature request related to a problem? Please describe:

The Real-Time Object Counter Streamlit app focuses on counting objects from a live video feed or webcam and displaying real-time results. This feature has practical use cases, including:

• Crowd monitoring for public events or festivals.
• Traffic management by counting vehicles in real-time.
• Security applications for surveillance.

This app builds on YOLOv8's real-time object detection capabilities, but its focus is on counting detected objects in a seamless Streamlit interface.

Solution Description:

This project uses a different approach, incorporating:

• Streamlit for a user-friendly, web-based interface.
• YOLOv8 for high-accuracy object detection.
• OpenCV for processing live video streams from webcams or video feeds.
• PyTorch for the underlying deep learning model.

The app will allow users to see real-time object counting based on detected objects, displaying dynamic and live results.

Alternatives Considered:

Although object detection using YOLO is already present, this project expands the functionality with real-time object counting, which is not covered in the existing "Object detection using YOLO" folder.

Potential alternative approaches to the tech stack could include:

• Using Flask or FastAPI for the backend instead of Streamlit.
• Using HTML, CSS, and JS for the frontend, though this would complicate the user interface.

Approach to be Followed:

To implement this solution, the following files and workflow will be used:

• Files:

  • app.py: Streamlit code for the app.
  • main.css: CSS for styling the interface.
  • yolov8n.pt: Pre-trained YOLOv8 weights for object detection.
  • run.bat: Batch file to simplify the app launch.
  • README.md: Documentation on installation and usage.

• Steps:

  1. Install dependencies from requirements.txt.
  2. Run the run.bat file to start the app.
  3. The app will open in a browser window, and users can start real-time object detection and counting from their webcam or a video feed.

Why This is a Unique Addition:

Although a folder exists for "Object detection using YOLO," this project is distinct in that it focuses specifically on object counting in real-time and offers a web-based interface using Streamlit. Additionally, the integration of YOLOv8 (which is newer and more advanced than earlier YOLO versions) and OpenCV for real-time processing makes this a novel addition to the repository.

[github-actions[bot]]

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[github-actions[bot]]

Thanks for raising this issue! However, we believe a similar issue already exists. Kindly go through all the open issues and ask to be assigned to that issue.

[rakheshkrishna2005]

I have raised this issue since my previous issue was automatically closed. Ignore this (#397) and reopen #396 instead.

[UppuluriKalyani]

I have raised this issue since my previous issue was automatically closed. Ignore this (#397) and reopen #396 instead.

Assigned check once

[github-actions[bot]]

Hello @rakheshkrishna2005! Your issue #397 has been closed. Thank you for your contribution!