node-yolo

This Node.js C++ Addon came out from a computer engineering project, VAPi. It allow you to use a state-of-the-art, real-time object detection system called Yolo.

Note: Now is in progress some work to improve the module, to enhance the current functionalities:

• First we begin to improve more robustness to the lib
• Second give the possibility to process videos files and later on video streams
• Split the libyolo and node-yolo projects, for those that like an easy lib to continue on C or C++ instead node.js.

Who fork and/or use this repo please stay sharp because alot of changes happening and not backwards compatibility between 1..* version and 2.*. version.**

Pre-requirements

• C/C++ Compiler
• Nvidia graphic card with CUDA support and required files installed (Only if you want to use GPU acceleration)
• Node.js >= 9
• node-gyp
• ImageMagick

Installation

npm i @vapi/node-yolo --save

How To Use

const yolo = require('@vapi/node-yolo');
const detector = new yolo("darknet-configs", "cfg/coco.data", "cfg/yolov3.cfg", "yolov3.weights");
try{
    detector.detect(path)
         .then(detections => {
            // here you receive the detections
         })
         .catch(error => {
           // here you can handle the errors. Ex: Out of memory
        });
}
catch(error){
    console.log('Catch: ' + error);
}

darknet-configs is a folder where you should put the Yolo weights, cfg and data files. You need to create two folder, cfg and data and put the files for each one. Like this:

.
├── darknet-configs         # The folder for the Yolo weight, cfg and data files
│   ├── cfg                 # cfg folder
|          |── coco.data
|          |── yolov3.cfg
│   ├── data                # data folder
|   |      |── coco.names
│   └── yolov3.weights      # YoloV3 weights file
└── ...

detections object

box object