Demonstration of Object Detection using MobileNets and OpenCV.
This project was made for detecting 20 different types of object such as "background", "aeroplane", "bicycle", "bird", "boat",
"bottle", "bus", "car", "cat", "chair", "cow", "diningtable",
"dog", "horse", "motorbike", "person", "pottedplant", "sheep",
"sofa", "train", "tvmonitor" in a live video using the webcam or a pre-recorded video.
- numpy
- imutils
- OpenCV
You can install all the required libraries by running the following command
pip install requirements.txt
- Using pre-trained MobileNet architecture for detection of the objects present.
- Combining MobileNet and Single Shot Detector(SSD) framework.
- Model used is Caffe version of original TensorFlow implementation by Howard et al.
./image_object_detection.py -i #path to the input image -p #path to Caffe deploy prototxt file -m #path to the Caffe pre-trained model
./video_object_detection.py -p #path to Caffe deploy prototxt file -m #path to the Caffe pre-trained model
Adrian Rosebrock creator of PyimageSearch