Scrawl-canvas VS Konva

> working with glyphs and iterating them in reverse for RTL is brain-breaking. And line wrapping gets really complicated. It's also the most obscure because nobody has written down everything you need to know in one place

I can confirm this. I've been working on a (much simpler!) text layout engine for my canvas library over the past couple of months and the amount of complexity associated with just stamping some glyphs onto a canvas has left me screaming at my laptop on an almost daily basis. Getting a decent underline was a proud moment!

Question: did you ever find out what algorithm the various browsers are using to calculate how many words can fit on a given line? I'm almost there, except words will occasionally jump between lines when I scale the text. Really annoying!

The PR's still a work in progress, but I've got all the functionality I want in there (shaping lines to fit in non-rectangular containers, styling text, text along a non-straight line, dynamic updates, etc). Just need to test and document it all now ... https://github.com/KaliedaRik/Scrawl-canvas/pull/75

I've got myself organised and prepared a List Of Things To Do[1] to make my 2D Javascript library even better than it already is. Given that I've been working on the library for over 10 years now, and have never before set out such a list, I call this Progress!

[1] https://github.com/KaliedaRik/Scrawl-canvas/discussions/cate...

'Kay, I don't know if this anywhere close to what the OP wants, but this sort of live browser tab manipulation is possible to do using a mix of a a canvas element and the browser's Screen Capture API[1] (plus my JS canvas library, once I merge and publish the changes into its next release[2]).

This solution[3] shows the modified browser tab in a separate browser tab. I've got no idea whether it's possible to do the same sort of trick in the same tab (but probably not). I also have no idea how secure the Screen Capture API is - I'd get very nervous about doing this sort of thing when looking at my bank's online portal!

[1] https://developer.mozilla.org/en-US/docs/Web/API/Screen_Capt...

[2] https://github.com/KaliedaRik/Scrawl-canvas/pull/57

[3] Youtube video of the effect: https://www.youtube.com/watch?v=hCi6LmKMAo0

My canvas library's README[1] has a video embedded in it. FWIW I'm not convinced it adds anything to the library's sales pitch.

[1] https://github.com/KaliedaRik/Scrawl-canvas

> And I’m just mentioning some of the unfixable problems with this approach

I agree that using a canvas instead of leveraging existing accessibility supplied by HTML/CSS/JS and the DOM is an accessibility nightmare.

However, I disagree that canvas accessibility issues are "unfixable". Difficult? Yes. But not unfixable. In my view, the element works best in partnership with its wider environment (HTML/CSS/JS and the DOM), not as a replacement for it. With that in mind, we can start to tackle the accessibility issues you raise - fonts, links, interactions, etc.[1][2]

I have an ambition to one day become intelligent enough to understand/code in Rust, and I'm really glad to see that people are thinking about accessibility as a fundamental part of UIs being developed in Rust.

[1] - Which is what my JS 2d canvas library tries to do: https://scrawl-v8.rikweb.org.uk/

[2] - My thoughts on accessibility, and how I try to fix them using my library: https://scrawl-v8.rikweb.org.uk/learn/eleventh-lesson/

If, however, your company is set on this course, I very strongly suggest you use a canvas library - if only for the MVP. Here's my canvas library (spam alert!) ... even if you don't use it in your product, the library might help give you some ideas on how to overcome some of the responsive, interactive and accessibility issues you'll be facing.

Scrawl-canvas - example and another example (links to code at bottom of each page)

My personal experience as a library developer, who has written my library in JS, not TS ...

TS is an excellent choice for a lib dev starting a new project today. I can see the advantages of using TS for the library code - in particular for a library that gets popular and welcomes contributions from other developers. However TS is a nightmare for someone like me who: 1. started writing the library 9 years ago; 2. has let the library get "quite" big; and 3. has only learned to use TS in the past year (for the day job) and is nowhere near to becoming a types expert.

I've had experience of people suggesting I rewrite the library in TS. Sometimes those suggestions have been quite 'evangelical' in their tone. As an (essentially) solo developer I just don't have the time, capacity or willingness to do that work - however much the end results might please others.

I also understand that having type definitions file for the library's interface is, nowadays, a critical factor if the lib dev wants others to use the library in their projects. But writing a .d.ts file for a large, mature repo to at least help those potential users can quickly turn into a World of Hurt. I know this because I've done that work[1] and I never want to do it again.

As much as I know that TS is a Force for Good in the JS coding world, there are days when I detest it!

[1] - link to the Scrawl-canvas .d.ts file on GitHub - https://github.com/KaliedaRik/Scrawl-canvas/blob/master/sour...

Based on this, I found that some of the libraries are dead and no longer have any support. Only two libraries are still alive and have significant amount of stars on GitHub and downloads on NPM. They are Fabric.js and Konva.js.

I have been assigned a task to create a sort of a canva clone which will have almost same features as canva with authentication, access control and rating system(not in this phase). I need help in finding libraries similar to https://konvajs.org/ which has updated docs and great support for Nextjs.

I'm currently using konva (& react-konva) package, to utilize it in Node.js enviroment I also need canvas package installed in. However, when running the code encountering this error:

used goJS in one project and konva in another

All the UI part would make sense to do in React. The actual drawing board you likely would need to implement in canvas or SVG. It still could be a React component, but for actual drawing, you'd probably use something like Konva (https://konvajs.org/).

Konvajs - is an HTML5 Canvas JavaScript framework that enables high performance animations, transitions, node nesting, layering, filtering, caching, event handling for desktop and mobile applications, and much more.

During the development of a complex interactive UI for the configuration of a digital laboratory ecosystem, we were utilizing the Konva.js library. Konva is a wrapper around the HTML canvas that simplifies working with shapes and interacting with the canvas a lot. Everybody dealing with the plain canvas API knows how much code certain tasks require, especially when user interaction with the drawn shapes is required. The most important features Konva offers to me are

Konva.js - example

Have a go at petswitch.com if you wish... I made the original Petswitch almost ten years ago, and it's had mild success since then, including CNET writing an article about it and it receiving the prestigious honour of 'most useless website' in week 41 of 2018, as determined by theuselesswebindex.com. Aside from the obvious question of why I even made this, it was getting pretty creaky – I originally built it with PHP and ImageMagick, with the facial features being manually selected via jQuery UI. So I decided to rebuild the whole thing with a full face-to-pet ML pipeline, on static hosting. To get the human face features, the app renders the upload to a temporary img element. This is a handy way to orient the image correctly via the browser, and saves having to deal with EXIF data. It's then resized, rendered to a canvas element, converted to a base64 string, then sent via fetch to Google's Cloud Vision API, which returns landmark coordinates of the face. I use these coordinates to correct any tilt on the face, mask the eyes and mouth via a mask image, then store each masked element as an additional canvas. Detecting pet faces was trickier. Google, Amazon and Microsoft all offer object detection APIs via transfer learning, and the approach is largely the same: you supply a series of images with bounding boxes around the objects you want to detect, either added via a web interface or uploaded via their API. You train a model online from these supplied images, then the service will return the estimated coordinates of any detected objects in an uploaded image. I found a dataset of both cats and dogs that had been labelled with landmarks on their faces, then wrote a script to convert the landmarks into bounding boxes around their eyes and nose, the dimensions based on a simple formula around the distance between the eyes in each image. All in all it's been trained on about 17,000 images of cats and dogs, and the accuracy seems to be pretty good. I was pleased to discover it actually works pretty well on other pets too. I've also added some friendly pets to the Petswitch family for those that don't have a pet on hand. I decided not to use a framework for this, it's written from scratch using a series of ES6 modules – although I did use Konva to handle the manual selection of facial features if the API can't detect a face. I used ParcelJS as my task runner, and my detection APIs are hosted on Firebase Cloud Functions. Let me know if you have any questions, although I can offer no good explanation for why I created this monstrosity...