ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

Last update: Jan 04, 2023

Overview

ManimML

ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library. We want this project to be a compilation of primitive visualizations that can be easily combined to create videos about complex machine learning concepts. Additionally, we want to provide a set of abstractions which allow users to focus on explanations instead of software engineering.

Getting Started
Examples

Getting Started

First you will want to install manim.

Then install the package form source or pip install manim_ml

Then you can run the following to generate the example videos from python scripts.

manim -pqh src/vae.py VAEScene

Examples

Checkout the examples directory for some example videos with source code.

Neural Networks

This is a visualization of a Variational Autoencoder made using ManimML. It has a Pytorch style list of layers that can be composed in arbitrary order. The following video is made with the code from below.

class VariationalAutoencoderScene(Scene):

    def construct(self):
        embedding_layer = EmbeddingLayer(dist_theme="ellipse").scale(2)
        
        image = Image.open('images/image.jpeg')
        numpy_image = np.asarray(image)
        # Make nn
        neural_network = NeuralNetwork([
            ImageLayer(numpy_image, height=1.4),
            FeedForwardLayer(5),
            FeedForwardLayer(3),
            embedding_layer,
            FeedForwardLayer(3),
            FeedForwardLayer(5),
            ImageLayer(numpy_image, height=1.4),
        ], layer_spacing=0.1)

        neural_network.scale(1.3)

        self.play(Create(neural_network))
        self.play(neural_network.make_forward_pass_animation(run_time=15))

Generative Adversarial Network

This is a visualization of a Generative Adversarial Network made using ManimML.

VAE Disentanglement

This is a visualization of disentanglement with a Variational Autoencoder

You might also like...

Create animations for the optimization trajectory of neural nets

Animating the Optimization Trajectory of Neural Nets loss-landscape-anim lets you create animated optimization path in a 2D slice of the loss landscap

81 Dec 25, 2022

Testing the Facial Emotion Recognition (FER) algorithm on animations

PegHeads-Tutorial-3 Testing the Facial Emotion Recognition (FER) algorithm on animations

2 Jan 3, 2022

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl

6.1k Jan 5, 2023

tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

2.8k Jan 8, 2023

TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

912 Jan 8, 2023

A collection of 100 Deep Learning images and visualizations

A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.

65 Sep 12, 2022

This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Developed By Google!

Machine Learning Hand Detector This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Dev

3 Feb 25, 2022

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

3k Jan 8, 2023

The LaTeX and Python code for generating the paper, experiments' results and visualizations reported in each paper is available (whenever possible) in the paper's directory

This repository contains the software implementation of most algorithms used or developed in my research. The LaTeX and Python code for generating the

3 Jan 3, 2023

Comments

PyPi out of date

When I pip install manim_ml it doesn't include any of the examples in the README. It also doesn't have many of the modules you'd expect. For example, manim_ml.neural_networks doesn't exist. As a workaround I've manually installed dependencies and added a clone of the latest commit to my python path. However, it would be nice to be able to install it via pip.

opened by ElPiloto 6
[BUG] update some of the examples

I updated most of the examples, in particular: disentanglement cnn vae.

interpolation still doesn't work, and gan has some positioning issues but at least it renders.

Thanks for the cool library btw! l think having working/updated examples would increase it's visibility and usefulness :)

opened by YannDubs 1
NN scaling issue with Convolutional3DLayer
At some point there was code commited changing the behaviour of the net when scaling it. If I use the code in the pip package everything works fine (0.0.11 seems to contain only code prior to the 7th of may). https://user-images.githubusercontent.com/54776552/198372984-f704cceb-8582-4bf9-bc23-c15ebb836b34.mp4

However I'm forking the repo (with the latest commit from august) because I need to change some internal code and noticed this problem.

https://user-images.githubusercontent.com/54776552/198373792-fd672ec7-708e-4ebe-b353-e291c8a591dd.mp4

Maybe someone can pinpoint the exact commit which causes this behaviour?

Code used:

class Test(Scene): def construct(self): # Make the Layer object l1 = Convolutional3DLayer(4, 2, 2) l2 = Convolutional3DLayer(5, 1, 1) l3 = Convolutional3DLayer(2, 3, 3) layers = [l1, l2, l3] nn = NeuralNetwork(layers) nn.scale(2) nn.move_to(ORIGIN) # Make Animation self.add(nn) #self.play(Create(nn)) forward_propagation_animation = nn.make_forward_pass_animation(run_time=5, passing_flash=True) self.play(forward_propagation_animation)
opened by wand555 1

Releases(v0.0.1)

v0.0.1(Mar 28, 2022)

Basic beta version.
Source code(tar.gz)
Source code(zip)

Owner

GitHub Repository

ppo_pytorch_cpp - an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch

PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment t

59 Dec 09, 2022

A tensorflow model that predicts if the image is of a cat or of a dog.

Quick intro Hello and thank you for your interest in my project! This is the backend part of a two-repo application. The other part can be found here

0 Mar 08, 2022

"SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image", Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan, Humphrey Shi, Zhangyang Wang

SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image [Paper] [Website] Pipeline Code Environment pip install -r requirements

250 Jan 05, 2023

ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

Related tags

Overview

ManimML

Table of Contents

Getting Started

Examples

Neural Networks

Generative Adversarial Network

VAE Disentanglement

You might also like...

Create animations for the optimization trajectory of neural nets

Testing the Facial Emotion Recognition (FER) algorithm on animations

tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.

TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

A collection of 100 Deep Learning images and visualizations

This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Developed By Google!

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

The LaTeX and Python code for generating the paper, experiments' results and visualizations reported in each paper is available (whenever possible) in the paper's directory

Comments

PyPi out of date

[BUG] update some of the examples

NN scaling issue with Convolutional3DLayer

Releases(v0.0.1)

v0.0.1(Mar 28, 2022)

Owner

ppo_pytorch_cpp - an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch

A tensorflow model that predicts if the image is of a cat or of a dog.

"SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image", Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan, Humphrey Shi, Zhangyang Wang

SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.

disentanglement_lib is an open-source library for research on learning disentangled representations.

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

Implementation of Heterogeneous Graph Attention Network

the code for paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration"

PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

Code for "OctField: Hierarchical Implicit Functions for 3D Modeling (NeurIPS 2021)"

(CVPR 2021) Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds

Magisk module to enable hidden features on Android 12 Developer Preview 1.

Disentangled Lifespan Face Synthesis

Exploit ILP to learn symmetry breaking constraints of ASP programs.

Official repository of the paper 'Essentials for Class Incremental Learning'

The official PyTorch code for NeurIPS 2021 ML4AD Paper, "Does Thermal data make the detection systems more reliable?"

Fedlearn支持前沿算法研发的Python工具库 | Fedlearn algorithm toolkit for researchers

Gas detection for Raspberry Pi using ADS1x15 and MQ-2 sensors

🕵 Artificial Intelligence for social control of public administration

Course on computational design, non-linear optimization, and dynamics of soft systems at UIUC.