motion-canvas VS parsers

Hey HN! We’re building Revideo (https://github.com/redotvideo/revideo), an open source toolkit that lets you programmatically create and export videos with the animation library Motion Canvas (https://github.com/motion-canvas/motion-canvas). This is useful whenever you want to build apps that automate certain video tasks, which is increasingly possible using AI tools - for instance, one of our first users is building an app that turns code documentation into video tutorials.

Revideo extends Motion Canvas with features that are essential for creating video, such as the ability to export audio tracks, a nodejs package for headless, parameterized & much faster rendering, and audio components that make audio editing and syncing easier. While Motion Canvas aims to be a standalone editor [1], we want to build a set of libraries that lets developers integrate video editing functionality into their apps. Our goal is to provide an open-source alternative to Remotion (https://github.com/remotion-dev/remotion).

At the start of this year, we explored a bunch of product ideas in the space of AI-based video creation. For example, we’ve built apps that automatically create educational short videos and have experimented with automatically A/B testing and personalizing video ads.

While building these products, we were frustrated with the video editing frameworks we used: Moviepy (https://github.com/Zulko/moviepy), which we relied on initially, doesn’t offer a way to preview your videos, so we’d often have to wait minutes for a video to render to test our code changes. Remotion (https://github.com/remotion-dev/remotion), which we switched to later, is really good, but we didn’t want to rely on it as it is not open source (source-available only). That’s why we decided to build Revideo.

We’d already been following Motion Canvas for some time and really liked using it, so we thought that extending it would get us to something useful much faster than building an animation library from scratch. Initially, we tried to build our features as Motion Canvas plugins, but this did not provide enough flexibility to achieve the desired functionality. Additionally, video-specific features (such as audio support) were generally considered out of scope by the Motion Canvas maintainers, which is why we ultimately ended up creating a fork. We’re unsure if this is the right way to go in the long term, and would prefer to find a way to build Revideo without diverging from Motion Canvas too much - if you have suggestions on how to solve this, we’d love your input.

Compared to Remotion, which builds on top of React, Motion Canvas uses the HTML Canvas API and makes you define animation flows with generator functions. Its API is more “procedural”, as it makes you define the things that happen in your animation as a sequence of yields, whereas Remotion gives you a frame number and lets you declare how your video should look like at that frame.

Our current focus is improving the open source project. In the long term, we want to make money by building a rendering service for developers building apps with Revideo. Such a service would offer a pretty similar deployment experience to Vercel, but instead of web apps, we let developers deploy Revideo projects and expose a rendering endpoint for them. Letting us manage the infrastructure will allow us to offer much faster rendering, as we can massively parallelize rendering jobs on our servers (e.g. spinning up 100 headless browsers that render 100 frames each to render a video with 10,000 frames).

We’d love to hear your feedback and suggestions! You can find our repo at https://github.com/redotvideo/revideo, We’ve also released an example video editing app at https://github.com/redotvideo/revideo-saas-template. Thank you!

[1] “Motion Canvas is not a normal npm package. It's a standalone tool that happens to be distributed via npm.” - https://github.com/orgs/motion-canvas/discussions/1015

I'm using https://motioncanvas.io/, but it's a little bit tough to learn

Coming to motion design, this rumour takes of due to the fact that there are programming libraries like Manim and Motion-Canvas which are actually used to generate animations from code. You can search 3Blue1Brown channel on youtube.

Personally I would look at codebased animation programs for something like this. Maybe possible with for example Motion Canvas - web github

You might also consider JavaScript to use ThreeJS or Motion Canvas.

Most of the credit goes to https://motioncanvas.io/ here 😉 But thanks anyway!

You can try to use motion Canvas its still new but amazing. Motion Canvas

Specify if also a good all-in-one tool I just found yesterday https://specifyapp.com/

Today quite some companies are already tackling similar problems. Talking of Knapsack.cloud, Backlight.dev, Specify, Supernova and many more, here. They all deliver value to simplify workflows for setup, integration, documentation and management of Design Systems. This is all super helpful in spreading the love about Design Systems to teams out there, and is a huge benefit to the process side of things. But you usually still need to create or import all of your components, which means that you still have some hard work before to you yourself, before finally benefitting from these tools. There’s also a lot (knowledge and work) going into the setup of a Design System (semantic tokens, hardened components, etc) that’s not solved by those tools, yet.

By default Specify returns design data in JSON but thanks its open source parsers you can transform your design data in any formats. I repeat, in any formats.

https://story.to.design/ https://specifyapp.com/

At Specify, We started experimenting with the Shape Up methodology a few weeks ago to define focused projects, address unknowns, and increase collaboration and engagement within the team. So, I started to learn more about how other teams implemented it, too.

here's a list of their parsers: https://github.com/Specifyapp/parsers/tree/master/parsers

For each rule we can use a different filter, such that the rule only applies to certain types of design tokens. Next to filters, we can also use parsers, which will manipulate the raw design tokens (which are in JSON format) and output a format that suits the programming language and platform more. Parsers behave like a pipeline, where each parser receives the input of the previous one. There are a lot of parsers to choose from, some perform very low level transformations such as round-number and camelcasify, but also full-blown parsers to a single technology such as to-tailwind and to-react-native.