README
Darknet.JS
A Node wrapper of pjreddie's open source neural network framework Darknet, using the Foreign Function Interface Library. Read: YOLOv3 in JavaScript.
Prerequisites
- Linux, Mac, Windows (Linux sub-system),
- Node (most versions will work, darknet.js <=1.1.5 only works on node <=8.11.2)
- Build tools (make, gcc, etc.)
Examples
To run the examples, run the following commands:
git clone https://github.com/bennetthardwick/darknet.js.git darknet && cd darknet
npm install
./examples/example
Note: The example weights are quite large, the download might take some time
Installation
Super easy, just install it with npm:
npm install darknet
If you'd like to enable CUDA and/or CUDANN, export the flags DARKNET_BUILD_WITH_GPU=1
for CUDA, and DARKNET_BUILD_WITH_CUDNN=1
for CUDANN, and rebuild:
export DARKNET_BUILD_WITH_GPU=1
export DARKNET_BUILD_WITH_CUDNN=1
npm rebuild darknet
Usage
To create an instance of darknet.js, you need a three things. The trained weights, the configuration file they were trained with and a list of the names of all the classes.
import { Darknet } from 'darknet';
// Init
let darknet = new Darknet({
weights: './cats.weights',
config: './cats.cfg',
names: [ 'dog', 'cat' ]
});
// Detect
console.log(darknet.detect('/image/of/a/dog.jpg'));
In conjuction with opencv4nodejs, Darknet.js can also be used to detect objects inside videos.
const fs = require('fs');
const cv = require('opencv4nodejs');
const { Darknet } = require('darknet');
const darknet = new Darknet({
weights: 'yolov3.weights',
config: 'cfg/yolov3.cfg',
namefile: 'data/coco.names'
});
const cap = new cv.VideoCapture('video.mp4');
let frame;
let index = 0;
do {
frame = cap.read().cvtColor(cv.COLOR_BGR2RGB);
console.log('frame', index++);
console.log(darknet.detect({
b: frame.getData(),
w: frame.cols,
h: frame.rows,
c: frame.channels
}));
} while(!frame.empty);
Example Configuration
You can download pre-trained weights and configuration from pjreddie's website. The latest version (yolov3-tiny) is linked below:
If you don't want to download that stuff manually, navigate to the examples
directory and issue the ./example
command. This will download the necessary files and run some detections.
## Built-With
- [Node FFI](https://github.com/node-ffi/node-ffi)
- [Ref](https://github.com/TooTallNate/ref)
- [Darknet](https://github.com/pjreddie/darknet)