Mint

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Mint is an open-source multi-modal content creation model training infrastructure that includes the FACT model (AI Choreographer) implementation. It supports music-conditioned 3D dance generation.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is mint?

Mint provides a comprehensive training infrastructure for multi-modal content creation models, specifically focusing on music-conditioned 3D dance generation. It includes the implementation of the FACT model, also known as the AI Choreographer. This open-source project offers the necessary tools and code to get started with generating 3D dance sequences based on musical input. Users can pull the code, install dependencies, preprocess datasets into TFRecord format, and then run training, testing, and evaluation processes. The project also provides instructions for downloading pre-trained checkpoints and calculating performance scores like FIDs.

Best used for

Ideal for developers and data scientists who need to implement and train AI models for music-conditioned 3D dance generation, preprocess large datasets, and evaluate model performance. Especially valuable for researchers and practitioners in the field of AI-driven content creation and choreography.

Common actions

generate 3D dance

train AI models

evaluate AI models

preprocess datasets

github copilot"AI Agents"face swappingcollaborationopen-sourceautomated workflowworkflowslow-code/no-codedeepfake

Capabilities

Key features

FACT model implementation
Music-conditioned 3D dance generation
Model training infrastructure
Dataset preprocessing
Model evaluation

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What is the FACT model mentioned in Mint?

The FACT model, also referred to as AI Choreographer, is a core component within Mint. It is an implementation designed for music-conditioned 3D dance generation, allowing the system to create dance sequences that are synchronized and responsive to musical input.

What are the primary dependencies required to run Mint?

To run Mint, you'll need Python (specifically 3.7), conda for environment management, and several key libraries including TensorFlow, protobuf, numpy, absl-py, tensorflow-datasets, and librosa. It also requires specific installations like libopenexr-dev and tensorflow-graphics.

How do I get the necessary data and checkpoints for Mint?

Users need to obtain the AIST++ dataset for training and evaluation, with specific directories for annotations and audio. Pre-trained model checkpoints can be downloaded from a Google Drive link provided in the documentation and placed into the designated './checkpoints/' folder.

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