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.
-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
All the dependencies can be installed using pip.
pip3 install -r requirements.txtTo run the script using webcam as source :
python3 real_time_object_detection.py --prototxt MobileNetSSD_deploy.prototxt.txt --model MobileNetSSD_deploy.caffemodel --source webcamThen 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