Realtime Obejct Recognition

Realtime object recognition using the OpenCV + MobileNetSSD caffemodel. Realtime Object Recognition is an innovative project leveraging computer vision and machine learning techniques to detect and classify objects in real-time. Whether you're building a smart surveillance system, developing augmented reality applications, or enhancing robotics capabilities, this project provides a robust foundation for object detection tasks.

Key Features:

-Utilizes state-of-the-art deep learning models for object detection -Real-time inference for live video streams or camera feeds -Supports a wide range of objects and environments -Easily customizable and extendable for specific use cases -Integration with popular frameworks like TensorFlow and OpenCV -Seamless deployment on edge devices or cloud platforms

Installation

All the dependencies can be installed using pip.

pip3 install -r requirements.txt

How to run this script?

To run the script using webcam as source :

python3 real_time_object_detection.py --prototxt MobileNetSSD_deploy.prototxt.txt --model MobileNetSSD_deploy.caffemodel --source webcam

Then to run the script using IP as source :

python3 real_time_object_detection.py --prototxt MobileNetSSD_deploy.prototxt.txt --model MobileNetSSD_deploy.caffemodel --source web