This project implements an image and video object detection classifier using pretrained yolov3 models. The yolov3 models are taken from the official yolov3 paper which was released in 2018. The yolov3 implementation is from [darkne](https://github.com/pjreddie/darknet). Also, this project implements an option to perform classification real-time using the webcam.
With this model, objects given in the labels list can be recognized.
labels = ["person","bicycle","car","motorcycle","airplane","bus","train","truck","boat","trafficlight",
"firehydrant","stopsign","parkingmeter","bench","bird","cat","dog","horse","sheep","cow",
"elephant","bear","zebra","giraffe","backpack","umbrella","handbag","tie","suitcase","frisbee",
"skis","snowboard","sportsball","kite","baseballbat","baseballglove","skateboard","surfboard",
"tennisracket","bottle","wineglass","cup","fork","knife","spoon","bowl","banana","apple",
"sandwich","orange","broccoli","carrot","hotdog","pizza","donut","cake","chair","sofa",
"pottedplant","bed","diningtable","toilet","tvmonitor","laptop","mouse","remote","keyboard",
"cellphone","microwave","oven","toaster","sink","refrigerator","book","clock","vase",
"scissors","teddybear","hairdrier","toothbrush"]
1 ) Clone the repository
git clone https://github.com/mucahitbektas/RealTimeObjectDetection.git
2 ) Move to the directory
cd RealTimeObjectDetection
3.1 ) To infer real-time on your webcam
python3 yolo_objectdetect_fromWebCam.py
3.2 ) To infer real-time on IPCam
python3 yolo_objectdetect_fromIPCam.py
Note: This works considering you have the weights and config files at the yolov3/model directory.
If the files are located somewhere else then mention the path while calling the yolo_objectdetect_fromXXXCam.py. For more details
yolo.py --help
NOTE: If you want to take images over the IP camera, you can use the applications that you can search for 'IP Webcam' on Android or IOS market platforms.
Click on the image to play the video on YouTube( https://youtu.be/R9NNlvLbGTc )
