localForage is a fast and simple storage library for JavaScript.localForage uses localStorage in browsers with no IndexedDB or WebSQL.

localforage.setItem('key', 'value', function (err) {
  // if err is non-null, we got an error
  localforage.getItem('key', function (err, value) {
    // if err is non-null, we got an error. otherwise, value is the value
  });
});

:Framework Support

AngularJS

  Angular 4 and up

  Backbone

  Ember

  Vue 

TypeScript:

import localForage from "localforage"; 

What makes 1.0 different from our pre-release builds?

• Stable CSS and API surface.We're now confident in the API for these components and do not plan any breaking changes.
• Supported platforms: Tested on IE 11+, Chrome, Safari, Firefox, Android 4.2+ and iOS 8+.
• Angular 1.5-ready. You can use AngularJS 1.3 and later, but as soon as you update to the new release, you can be confident that ngMaterial components will continue to work as expected. 

GitHub Community is built to support all GitHub users on their educational journey, via Discussions. It is a resource hub, learning portal, and inspiration station, all in one. Regardless of how big or small your challenge is, all resources and information will be accessible in a true open source fashion.

AngularJS is the next big thing for web applications

A 9-Hour Go Course for Beginners

⭐️ Contents ⭐️
(0:00:00) Intro
(0:03:17) Ch 1. Why write Go?
(0:27:39) Ch 2. Variables
(0:51:11) Ch 3. Functions
(1:16:58) Ch 4. Structs
(1:34:36) Ch 5. Interfaces
(2:00:26) Ch 6. Errors
(2:22:01) Ch 7. Loops
(2:48:21) Ch 8. Slices
(3:39:54) Ch 9. Maps
(4:06:19) Ch 10. Advanced functions
(4:31:03) Ch 11. Pointers
(4:48:02) Ch 12. Local development
(5:31:43) Ch 13. Channels & concurrency
(6:07:38) Ch 14. Mutexes
(6:30:56) Ch 15. Generics
(6:38:38) Ch 16. Quiz
(6:43:13) P1. RSS aggregator project
(6:53:43) P2. Chi router
(7:11:37) P3. Postgres database
(7:39:10) P4. Authentication w/ API keys
(8:18:28) P5. Many to many relationships
(8:39:13) P6. Aggregation worker
(9:05:28) P7. Viewing blog posts 

A set of composable and extensible Angular 2 directives for building SVGs with D3 declaritively. This library provides functionality for basic charts out of the box, but it can be easily extended to support building declarative syntaxes for just about any SVG generated by D3.  Demo

var srcImage = new Mat(@"..\..\Images\Test.jpg");
Cv2.ImShow("Source", srcImage);
Cv2.WaitKey(1); // do events
 
var grayImage = new Mat();
Cv2.CvtColor(srcImage, grayImage, ColorConversion.BgrToGray);
Cv2.EqualizeHist(grayImage, grayImage);

var cascade = new CascadeClassifier(@"..\..\Data\haarcascade_frontalface_alt.xml");
var nestedCascade = new CascadeClassifier(@"..\..\Data\haarcascade_eye_tree_eyeglasses.xml");
 
var faces = cascade.DetectMultiScale(
    image: grayImage,
    scaleFactor: 1.1,
    minNeighbors: 2,
    flags: HaarDetectionType.Zero | HaarDetectionType.ScaleImage,
    minSize: new Size(30, 30)
    );
 
Console.WriteLine("Detected faces: {0}", faces.Length);

var rnd = new Random();
var count = 1;
foreach (var faceRect in faces)
{
    var detectedFaceImage = new Mat(srcImage, faceRect);
    Cv2.ImShow(string.Format("Face {0}", count), detectedFaceImage);
    Cv2.WaitKey(1); // do events
 
    var color = Scalar.FromRgb(rnd.Next(0, 255), rnd.Next(0, 255), rnd.Next(0, 255));
    Cv2.Rectangle(srcImage, faceRect, color, 3);
  
    count++;
}
 
Cv2.ImShow("Haar Detection", srcImage);
Cv2.WaitKey(1); // do events

var rnd = new Random();
var count = 1;
foreach (var faceRect in faces)
{
    var detectedFaceImage = new Mat(srcImage, faceRect);
    Cv2.ImShow(string.Format("Face {0}", count), detectedFaceImage);
    Cv2.WaitKey(1); // do events
 
    var color = Scalar.FromRgb(rnd.Next(0, 255), rnd.Next(0, 255), rnd.Next(0, 255));
    Cv2.Rectangle(srcImage, faceRect, color, 3);
 
 
    var detectedFaceGrayImage = new Mat();
    Cv2.CvtColor(detectedFaceImage, detectedFaceGrayImage, ColorConversion.BgrToGray);
    var nestedObjects = nestedCascade.DetectMultiScale(
        image: detectedFaceGrayImage,
        scaleFactor: 1.1,
        minNeighbors: 2,
        flags: HaarDetectionType.Zero | HaarDetectionType.ScaleImage,
        minSize: new Size(30, 30)
        );
 
    Console.WriteLine("Nested Objects[{0}]: {1}", count, nestedObjects.Length);
 
    foreach (var nestedObject in nestedObjects)
    {
        var center = new Point
        {
            X = Cv.Round(nestedObject.X + nestedObject.Width * 0.5) + faceRect.Left,
            Y = Cv.Round(nestedObject.Y + nestedObject.Height * 0.5) + faceRect.Top
        };
        var radius = Cv.Round((nestedObject.Width + nestedObject.Height) * 0.25);
        Cv2.Circle(srcImage, center, radius, color, thickness: 3);
    }
 
    count++;
}
 
Cv2.ImShow("Haar Detection", srcImage);
Cv2.WaitKey(1); // do events