Updated version number and examples

Author: Bennett Hardwick

README.md

@@ -2,7 +2,7 @@
 A Node wrapper of pjreddie's open source neural network framework Darknet, using the Foreign Function Interface Library. Read: YOLOv3 in JavaScript.
 
 ## Prerequisites
-- Linux, Windows (Linux sub-system), Mac (probably)
+- 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.)
 
@@ -37,6 +37,34 @@ let darknet = new Darknet({
 console.log(darknet.detect('/image/of/a/dog.jpg'));
 ```
 
+In conjuction with [opencv4nodejs](https://github.com/justadudewhohacks/opencv4nodejs), Darknet.js can also be used to detect objects inside videos.
+```javascript
+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: 
 - [weights](https://pjreddie.com/media/files/yolov3-tiny.weights)

darknet.d.ts

@@ -9,28 +9,51 @@ export declare class Darknet {
      * @param config
      */
     constructor(config: IDarknetConfig);
-    private getArrayFromBuffer;
-    private bufferToDetections;
-    private _detectSync;
-    private _detectAsync;
+    private getArrayFromBuffer(buffer, length, type);
+    private bufferToDetections(buffer, length);
+    private _detectSync(net, meta, image, thresh?, hier_thresh?, nms?);
+    private _detectAsync(net, meta, image, thresh?, hier_thresh?, nms?);
     /**
      * Synchronously detect objects in an image.
      * @param image the destination of the image to be detected
      * @param config optional configuration (threshold, etc.)
      */
     detect(image: string | IBufferImage, config?: IConfig): Detection[];
+    /**
+     * Get a Darknet Image from path
+     * @param path
+     * @returns IMAGE
+     */
     getImageFromPath(path: string): any;
+    /**
+     * Get a Darknet Image async from path
+     * @param path
+     * @returns Promise<IMAGE>
+     */
     getImageFromPathAsync(path: String): Promise<{}>;
+    /**
+     * convert darknet image to rgb buffer
+     * @param {IMAGE} image
+     * @returns {Buffer}
+     */
     imageToRGBBuffer(image: any): Buffer;
-    private rgbToDarknet;
+    private rgbToDarknet(buffer, w, h, c);
+    /**
+     * Transform an RGB buffer to a darknet encoded image
+     * @param buffer - rgb buffer
+     * @param w - width
+     * @param h - height
+     * @param c - channels
+     * @returns {IMAGE}
+     */
     RGBBufferToImage(buffer: Buffer, w: number, h: number, c: number): any;
     /**
      * Transform an RGB buffer to a darknet encoded image
      * @param buffer - rgb buffer
      * @param w - width
      * @param h - height
      * @param c - channels
-     * @returns Promise<IMAGE>
+     * @returns {Promise<IMAGE>}
      */
     RGBBufferToImageAsync(buffer: Buffer, w: number, h: number, c: number): Promise<any>;
     /**

darknet.js

@@ -151,8 +151,8 @@ var Darknet = /** @class */ (function () {
     };
     Darknet.prototype._detectAsync = function (net, meta, image, thresh, hier_thresh, nms) {
         return __awaiter(this, void 0, void 0, function () {
-            var pnum, dets, num, detections;
             var _this = this;
+            var pnum, dets, num, detections;
             return __generator(this, function (_a) {
                 switch (_a.label) {
                     case 0: return [4 /*yield*/, new Promise(function (res, rej) {
@@ -201,9 +201,19 @@ var Darknet = /** @class */ (function () {
         }
         return detection;
     };
+    /**
+     * Get a Darknet Image from path
+     * @param path
+     * @returns IMAGE
+     */
     Darknet.prototype.getImageFromPath = function (path) {
         return this.darknet.load_image_color(path, 0, 0);
     };
+    /**
+     * Get a Darknet Image async from path
+     * @param path
+     * @returns Promise<IMAGE>
+     */
     Darknet.prototype.getImageFromPathAsync = function (path) {
         return __awaiter(this, void 0, void 0, function () {
             var _this = this;
@@ -214,6 +224,11 @@ var Darknet = /** @class */ (function () {
             });
         });
     };
+    /**
+     * convert darknet image to rgb buffer
+     * @param {IMAGE} image
+     * @returns {Buffer}
+     */
     Darknet.prototype.imageToRGBBuffer = function (image) {
         var w = image.w;
         var h = image.h;
@@ -246,6 +261,14 @@ var Darknet = /** @class */ (function () {
         }
         return floatBuff;
     };
+    /**
+     * Transform an RGB buffer to a darknet encoded image
+     * @param buffer - rgb buffer
+     * @param w - width
+     * @param h - height
+     * @param c - channels
+     * @returns {IMAGE}
+     */
     Darknet.prototype.RGBBufferToImage = function (buffer, w, h, c) {
         var floatBuff = this.rgbToDarknet(buffer, w, h, c);
         return this.darknet.float_to_image(w, h, c, new Uint8Array(floatBuff.buffer, 0, floatBuff.length * Float32Array.BYTES_PER_ELEMENT));
@@ -256,12 +279,12 @@ var Darknet = /** @class */ (function () {
      * @param w - width
      * @param h - height
      * @param c - channels
-     * @returns Promise<IMAGE>
+     * @returns {Promise<IMAGE>}
      */
     Darknet.prototype.RGBBufferToImageAsync = function (buffer, w, h, c) {
         return __awaiter(this, void 0, void 0, function () {
-            var floatBuff;
             var _this = this;
+            var floatBuff;
             return __generator(this, function (_a) {
                 floatBuff = this.rgbToDarknet(buffer, w, h, c);
                 return [2 /*return*/, new Promise(function (res, rej) { return _this.darknet.float_to_image.async(w, h, c, new Uint8Array(floatBuff.buffer, 0, floatBuff.length * Float32Array.BYTES_PER_ELEMENT), function (e, image) { return e ? rej(e) : res(image); }); })];
@@ -276,8 +299,8 @@ var Darknet = /** @class */ (function () {
      */
     Darknet.prototype.detectAsync = function (image, config) {
         return __awaiter(this, void 0, void 0, function () {
-            var thresh, hier_thresh, nms, darkNetLoadedImage, imageData, _a, detection;
             var _this = this;
+            var thresh, hier_thresh, nms, darkNetLoadedImage, imageData, _a, detection;
             return __generator(this, function (_b) {
                 switch (_b.label) {
                     case 0:

examples/yolov3-tiny.js

@@ -1,4 +1,4 @@
-const Darknet = require('../darknet').Darknet;
+const { Darknet } = require('../darknet');
 
 const darknet = new Darknet({
     weights: 'yolov3-tiny.weights',
@@ -8,4 +8,4 @@ const darknet = new Darknet({
 
 console.log("Dog:", darknet.detect('./dog.jpg'));
 console.log("Eagle:", darknet.detect('./eagle.jpg'));
-console.log("Giraffe:", darknet.detect('./giraffe.jpg'));
+console.log("Giraffe:", darknet.detect('./giraffe.jpg'));

package-lock.json

@@ -1,6 +1,6 @@
 {
   "name": "darknet",
-  "version": "1.1.6",
+  "version": "1.2.6",
   "description": "",
   "main": "darknet.js",
   "typings": "darknet.d.ts",