https://github.com/ivangael/objects_detection_with_neural_network_training_visualization

Real-time Object Detection and Neural Network Training Visualization
https://github.com/ivangael/objects_detection_with_neural_network_training_visualization

keras matplotlib neural-network neural-network-training neural-network-visualizations numpy object-detection opencv python tensorflow ultralytics

Last synced: 7 days ago
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Real-time Object Detection and Neural Network Training Visualization

• Host: GitHub
• URL: https://github.com/ivangael/objects_detection_with_neural_network_training_visualization
• Owner: IvanGael
• Created: 2024-06-25T01:28:27.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-06-25T20:26:40.000Z (5 months ago)
• Last Synced: 2024-06-25T22:03:46.955Z (5 months ago)
• Topics: keras, matplotlib, neural-network, neural-network-training, neural-network-visualizations, numpy, object-detection, opencv, python, tensorflow, ultralytics
• Language: Python
• Homepage:
• Size: 11.5 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Real-time Object Detection and Neural Network Training Visualization

## Overview

This project combines real-time object detection using YOLOv8 with concurrent neural network training visualization. It processes a video stream, detects objects, collects training data, and simultaneously displays object counts and neural network training progress.













## Features

- Real-time object detection using YOLOv8

- Concurrent neural network training on detected objects

- Live visualization of object counts and training loss

- Multithreaded processing for smooth performance

## Requirements

- Python 3.7+

- OpenCV

- NumPy

- Matplotlib

- Ultralytics YOLO

- TensorFlow/Keras

````

pip install -r requirements.txt

````