This folder contains an Augmented Reality (AR) application that performs real-time object detection using a pre-trained MobileNet-SSD model. The project uses Python 3.6, and it’s recommended to run it in an Anaconda environment.
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Python Version: Python 3.6 (recommended via Anaconda)
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Dependencies: Install the required packages by running:
pip install -r requirements.txt
After installing the necessary dependencies, you can run the object detection code to enable real-time object detection in an AR environment.
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Linux/MacOS:
python3 real_time_object_detection.py --prototxt MobileNetSSD_deploy.prototxt.txt --model MobileNetSSD_deploy.caffemodel
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Windows:
python real_time_object_detection.py --prototxt MobileNetSSD_deploy.prototxt.txt --model MobileNetSSD_deploy.caffemodel
real_time_object_detection.py
: The main script for running the object detection model in real-time.MobileNetSSD_deploy.prototxt.txt
: The configuration file defining the MobileNet-SSD model structure.MobileNetSSD_deploy.caffemodel
: The pre-trained MobileNet-SSD model weights.
The application uses a MobileNet-SSD model to detect objects in real-time through a connected camera or video feed. The detected objects are overlaid with bounding boxes, making it suitable for augmented reality applications.
- Ensure that your camera is properly connected for real-time detection.
- Adjust the detection threshold in the script if necessary to improve accuracy or speed.