Cartoonify github
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As an animation enthusiast who struggles to master the complex art of character animation, I saw hope and was really excited to experiment using these models for interactive, body-co….
Return to TensorFlow Home. Pose Animator - An open source tool to bring SVG characters to life in the browser via motion capture. May 27, As an animation enthusiast who struggles to master the complex art of character animation, I saw hope and was really excited to experiment using these models for interactive, body-controlled animation.
The result is Pose Animator , an open-source web animation tool that brings SVG characters to life with body detection results from webcam. This blog post covers the technical design of Pose Animator, as well as the steps for designers to create and animate their own characters.
To achieve this, Pose Animator borrows the idea of skeleton-based animation from computer graphics and applies it to vector characters. In skeletal animation a character is represented in two parts: a surface used to draw the character, and a hierarchical set of interconnected bones used to animate the surface. For the bone structure, Pose Animator provides a predefined rig bone hierarchy representation, based on the key points from PoseNet and FaceMesh. Iterate through every segment in vector paths to compute the weight influence and transformation from each bone using Linear Blend Skinning explained later in this post.
In real time, run FaceMesh and PoseNet on each input frame and use result keypoints to update the bone positions. Compute new positions of vector segments from the updated bone positions, bone weights and transformations. There are other tools that provide similar puppeteering functionality, however, most of them only update asset bounding boxes and do not deform the actual geometry of characters with recognition key points.
Also, few tools provide full body recognition and animation. By deforming individual curves, Pose Animator is good at capturing the nuances of facial and full body movement and hopefully provides more expressive animation. PoseNet returns 17 key points for the full body, which is simple enough to directly include in the rig. FaceMesh however provides keypoints, so I needed to be more selective about which ones to include. In the end I selected 73 key points from the FaceMesh output and together we have a full body rig of 90 keypoints and 78 bones as shown below: The 90 keypoints, 78 bones full body rig Every input SVG file is expected to contain this skeleton in default position.
A sample rig SVG can be found here. Designers have the freedom to move the joints around in their design files to best embed the rig into the character. Pose Animator will compute skinning according to the default position in the SVG file, although extreme cases e.
In our case, a vertex refers to an anchor point on a vector path, and bones are defined by two connected keypoints in the above rig e. The influence of bones can be automatically generated or manually assigned through weight painting. Pose Animator currently only supports auto weight assignment.
The raw influence of bone j on vertex i is calculated as: Where d is the distance from vi to the nearest point on bone j. Finally we normalize the weight of all bones for a vertex to sum up to 1.
Now, to apply LBS on 2D vector paths, which are composed of straight lines and bezier curves , we need some special treatment for bezier curve segments with in and out handles.
We need to compute weights separately for curve points, in control point, and out control point. This produces better looking results because the bone influence for control points are more accurately captured. There is one exception case. When the in control point, curve point, and out control point are collinear, we use the curve point weight for all three points to guarantee that they stay collinear when animated.
This helps to preserve the smoothness of curves. To reduce the jitter and get smoother animation, we can use the confidence scores from prediction results to weigh each input frame unevenly, granting less influence to low-confidence frames.
Following this idea, Pose Animator computes the smoothed position of joint i at frame t as where The smoothed confidence score of frame i is computed as Consider extreme cases. To further play with responsiveness, you can tweak the approach speed by changing the weight on the latest frame. When the latest frame has confidence score 0, its influence is completely ignored, preventing low confidence results from introducing sudden jerkiness. Confidence score based clipping In addition to interpolating joint positions with confidence scores, we also introduce a minimum threshold to decide if a path should be rendered at all.
The whole path is hidden for a particular frame when its score is below a certain threshold. This is useful for hiding paths in low confidence areas, which are often body parts out of the camera view. Imagine an upper body shot: PoseNet will always return keypoint predictions for legs and hips though they will have low confidence scores. With this clamping mechanism we can make sure lower body parts are properly hidden instead of showing up as strangely distorted paths.
Looking ahead To mesh or not to mesh The current rigging algorithm is heavily centered around 2D curves. This is because the 2D rig constructed from PoseNet and FaceMesh has a large range of motion and varying bone lengths - unlike animation in games where bones have relatively fixed length. I am keen to improve the rigging algorithm for meshes. Besides, I want to explore a more advanced rigging algorithm than Linear Blend Skinning, which has limitations such as volume thinning around the bent areas.
I want to support more animation features through in-browser UI, including: Skinning weight painting tool, to enable tweaking individual weights on keypoints manually. This will provide more precision than auto weight assignment. Try it yourself! Try out the live demos , where you can either play with existing characters, or add in your own SVG character and see them come to life.
To create your own animatable illustration, please check out this guide! Feel free to reach out to me on twitter yemount for any questions. Alternatively if you want to view the source code directly, it is available to fork on github here.
Happy hacking! Next post. Build, deploy, and experiment easily with TensorFlow. Get started. Google Privacy Terms Contributions notice. Detection keypoints from PoseNet blue and FaceMesh red. In the end I selected 73 key points from the FaceMesh output and together we have a full body rig of 90 keypoints and 78 bones as shown below:.
The illustration with embedded rig in design software Adobe Illustrator. Collinear curve handles share the same weight to stay collinear.
pascalre/python-fu-cartoonify
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Contributing with GitHub via command-line
Cartoonito is a preschool block on Cartoon Network and HBO Max , named after the international brand of the same name. Original logo for the British channel and the Italian channel, used from In the UK and from in Italy. On September 4, , months after Tickle U ended, the now-defunct British sister channel Cartoon Network Too debuted a new programming block called Cartoonito, running from a. Series featured in Cartoonito were acquired from countries around the world, and were available in both English and French. The block was later given its own channel on 24 May Whereas Cartoon Network Too ceased operations in , the Cartoonito channel remains operational as of With the announcement of Batwheels on October 6, , Warner Bros. In a 5 February interview with Kidscreen , Ascheim revealed that Cartoon Network would be expanding its programming offerings to include series aimed at families, girls, and preschool children. On July , Cartoonito UK's YouTube channel has rebranded to match the US branding and four more shows are joining the lineup are Dylan and three acquired series Bing , Odo , and Pocoyo and the trailer for the block is released and it will be hosted by four characters named Nito, Glob, Wedge, and Itty. Cartoon Network has aired the "Alpha Bodies" segment for the block on July 30, to promote the mascots.
Open source developers urged to ditch GitHub following Copilot launch
It can be pretty challenging to know all the answers to building your game. Many great developers in our community have helped on the forums and even created examples. But in response to the needs of the majority of developers, the Cocos technical support team has organized and provided some practical technical solutions for you, all of which are free and open-source! Some of these solutions come from the Cocos engine development team and technical support team, and more are from the creations of community developers using GitHub and Gitee. Thank you for your support and sharing!
Of GitHub and Pull Requests (and comics)
Currently, the language runtime as implemented by Ball is a tree-walking interpreter, but I plan to expand it and add a JIT native code compiler that can be swapped out with different instruction sets and architectures. I plan to implement the lexer and parser according to the book, and create a module for AST walking, but from there I will add my own code to it. Ball does add a bytecode compiler in the sequel book Writing a Compiler, but I will implement my own backend for the language, possibly using LLVM. The language itself is also extremely limited. This would probably be good enough for a simple scripting language, but I plan to add my own other items to it, such as:. I have a separate programming language project involving a bytecode compiler and a register-based VM here.
Give Up GitHub!
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Git cartoons and comics
This was released with the StyleGAN2 code and paper and produces pretty fantastically high quality results. This gives good results really quickly, and even more so if the new dataset is some also of faces. Doron fine-tuned the faces model on a dataset of various characters from animated films.
Draw This is a polaroid camera that draws cartoons. You point, and shoot - and out pops a cartoon; the camera's best interpretation of what it saw. The camera is a mash up of a neural network for object recognition, the google quickdraw dataset, a thermal printer, and a raspberry pi. If you'd like to try it out for yourself, the good folks at Kapwing have created an online version! The software can run both on a desktop environment OSX, Linux such as a laptop, or an embedded environment on a raspberry pi. The following wiring diagram will get you started with a shutter button and a status LED.
We realize this is not an easy task; GitHub is ubiquitous. GitHub has warped Git — creating add-on features that turn a distributed, egalitarian, and FOSS system into a centralized, proprietary site. And, all those add-on features are controlled by a single, for-profit company. We know that many rely on GitHub every day. Giving up a ubiquitous, gratis service that has useful albeit proprietary features is perennially difficult.
Also, this dataset on GitHub is updated. Three finalists are presented in another online ballot, the winner of which makes it into the magazine. I learned about the current state of play from a great piece in The Pudding wherein the authors attempted to train an artificial intelligence to win the contest. This was what The Pudding researchers noticed, and it confirms three years of investigating wit in this newsletter: What you say matters but how you say it matters more.
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