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petCam Machine Learning TensorFlow.js Demo

Description

This project is a practice exercise to understand the application Machine Learning (ML) using TensorFlow.js and Google's COCO-SSD model. The core functionality is built around a web application that utilizes a webcam to detect and recognize pets (cat or dog) and other objects.

Dependencies:

npm init -y npm install @tensorflow/tfjs npm install --save-dev webpack webpack-cli npm install --global http-server

Features

  • Webcam Integration: Utilizes the browser's webcam to capture real-time video feed.
  • Object Detection: Employs Google's COCO-SSD model to identify and classify objects within the video feed.
  • Customizable Alerts: Allows users to select specific pets and objects to monitor and receive alerts.

Tech Stack

  • TensorFlow.js: For running machine learning models in the browser.
  • COCO-SSD Model: A pre-trained model by Google for object detection.
  • HTML/CSS/JavaScript: For the frontend development

Acknowledgments

This project is a copy by Google Developers and TensorFlow.js tutorials. Thankful for the amazing tutorials to understand these concepts.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details

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