Open-source alternatives to Diffusion Policy

giga-brain-0 is a robot action model framework designed to train and deploy neural networks that map multi-modal sensor data to physical robot control signals. It functions as a robot manipulation controller that processes high-dimensional observations to execute dexterous, long-horizon physical tasks. The project provides a multi-modal robot inference server using a client-server architecture to stream real-time vision and language observations for instant action prediction. It includes an embodiment fine-tuning pipeline to adapt pre-trained base models to specific robot hardware configurati

Mobile Alohas is a bimanual mobile manipulation framework designed to learn whole-body robot control. It provides an integrated imitation learning pipeline that manages the process of collecting human demonstration data and training behavior models to automate complex physical tasks. The system features a robotic teleoperation interface that maps human movements to a mobile robot with dual arms. It includes a whole-body motion dataset tool used for recording, visualizing, and replaying joint and sensor data from manipulation sessions. The framework covers several capability areas, including

PaddleDetection is an object detection framework designed for the end-to-end development, training, and deployment of computer vision models. It provides a comprehensive library of modular neural network architectures and pipelines that support object detection, instance segmentation, and multi-object tracking tasks. The project distinguishes itself through a configuration-driven approach that decouples model components like backbones and heads, allowing for the flexible assembly of custom vision workflows. It incorporates advanced techniques such as anchor-free detection logic, joint detecti

This project is a PyTorch implementation of StyleGAN2, providing a library and research framework for training style-based generative adversarial networks. It serves as a toolkit for high-resolution image synthesis, utilizing competitive minimax optimization to create realistic synthetic visual content. The framework incorporates specialized architectural components such as style-based latent mapping, multi-scale feature modulation, and self-attention layers to improve structural coherence. It distinguishes itself with advanced training stability techniques, including exponential moving avera

Multimodal is a machine learning library built on PyTorch for training large-scale models that combine text, image, audio, and video data streams. It functions as a deep learning framework dedicated to generative diffusion models, multi-task training, and vision-language tasks. The library supplies modular building blocks, discrete latent codebook quantization, shared-space embeddings, and stackable adapter layers to handle diverse conditional inputs during training and inference. The framework supports specific architectures for diffusion models, text-to-video generation, image-text retrieva

ControlNet is a framework for structural image generation that extends pre-trained diffusion models with neural network architectures designed for precise spatial control. By injecting structural guidance directly into the latent-space denoising process, the system enables users to enforce geometric or semantic constraints on generated outputs while maintaining style consistency. The framework distinguishes itself through a weight-locked copying mechanism that preserves the integrity of the original model while introducing new control signals. It supports multi-condition synthesis, allowing f

This project is a diffusion model framework for training and sampling from denoising probabilistic models to generate images from noise. It functions as a generative image model that creates visual content by iteratively refining random noise into coherent images. The system includes a distributed GPU trainer designed to scale complex neural network architectures across multiple graphics processing units. It also provides an image dataset preprocessor to prepare, scale, and standardize raw image collections for training. The framework covers model training and image generation, utilizing noi

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

ManiSkill is a GPU-accelerated robot simulation framework designed for training robotic manipulation skills, benchmarking learning algorithms, and generating synthetic datasets. It serves as a reinforcement learning environment where robot control policies can be developed and evaluated using parallelized physics and rendering on the GPU. The platform is distinguished by its ability to perform sim-to-real transfer, allowing policies trained in virtual environments to be deployed onto physical robotic hardware. It features ray-traced parallel rendering for producing high-frame-rate RGBD and se

DeepMimic is a deep reinforcement learning framework and physics-based motion imitation tool designed to teach simulated characters and robots to reproduce human movements. It provides a pipeline for integrating motion capture data into physics simulations to train agents that can mimic complex physical skills. The system utilizes the PyBullet simulation environment to execute motion policies and visualize character interactions in real time. It includes a motion capture integration pipeline that imports and processes animation sequences to serve as reference targets for imitation learning ag

This is a PyTorch deep learning framework and tool for human motion synthesis that generates 3D character animations from text prompts or action descriptions. It functions as a text-to-motion generator that converts natural language and categorical labels into temporally consistent 3D skeletal movement sequences. The system utilizes a transformer-based diffusion model to iteratively denoise motion data. It includes capabilities for action-conditioned generation, monocular-to-3D motion lifting, and motion sequence editing using text constraints. The framework incorporates geometric motion con

OpenCat-Quadruped-Robot is a development framework and motion control API for building four-legged robots. It provides a comprehensive environment for quadruped robot development, featuring tools for locomotion gait design, inverse kinematics, and a layered control architecture that separates high-level intelligence from low-level motion. The project distinguishes itself as an embedded AI deployment tool, allowing users to train, quantize, and deploy machine learning models to vision modules for tasks such as object detection and visual target tracking. It further supports complex human-robot

Navigation2 is a navigation stack for ROS 2 designed for autonomous robot navigation. It provides a framework for computing optimal paths from a starting position to a goal while avoiding static and dynamic obstacles. The system utilizes a behavior tree orchestrator to coordinate complex navigation tasks and trigger recovery actions. Its architecture is plugin-based, allowing planners, controllers, and costmap layers to be swapped at runtime without recompiling the core system. The project covers path planning, motion control, and environmental mapping. It generates occupancy grids and costm

FastVideo is a comprehensive system for accelerated video generation, serving as a video generation inference engine, a video diffusion training framework, and a modular pipeline orchestrator. It provides a distributed transformer optimizer and a distillation toolkit designed to reduce denoising steps and model complexity to increase frame rates. The project distinguishes itself through specialized acceleration techniques, including joint distillation and sparse attention training. It implements low-step video generation and weight quantization to FP8 or FP4 precision to increase throughput a

SO-ARM100 is an open-source robot arm hardware project providing 3D-printable designs and assembly guides for building affordable robotic arms. It includes calibration software to synchronize motor communication parameters and arm positions via USB, alongside hardware designs for tactile sensing robotic grippers. The project distinguishes itself through the integration of touch-sensing and flexible filaments for adaptive grasping. It also provides a dedicated imitation learning dataset tool, featuring a web interface for labeling and visualizing robotics data to train machine learning models

Code Repository for GenDexGrasp: Generalizable Dexterous Grasping

Stable Diffusion WebUI Forge is a web-based interface and inference engine designed for the generation of AI media. It functions as a platform for executing diffusion-based models, providing a centralized environment to manage image preprocessors, custom generation logic, and hardware-accelerated sampling. The project distinguishes itself through a neural network patching framework that allows for the modification of model layers and the application of spatial conditioning during inference. By injecting custom logic and adapters directly into the network, users can influence output behaviors

This repository serves as a structured educational resource for learning to build, train, and deploy neural networks using the PyTorch framework. It provides a collection of practical code examples and tutorials designed to guide practitioners through the implementation of deep learning models. The project covers a broad range of machine learning domains, including computer vision, natural language processing, generative modeling, and reinforcement learning. By utilizing modular components and automated gradient computation, the materials demonstrate how to construct complex architectures and

swww is an animated wallpaper engine and daemon for Wayland compositors. It functions as a shared-memory wallpaper manager that renders image frames and transitions to create moving desktop backgrounds. The project enables dynamic wallpaper management across multiple monitors in real time, allowing users to update backgrounds or set solid colors without restarting the background process. It supports automated background rotation and smooth visual transitions, such as wipes and fades, when switching between images.

Napajs is an embeddable JavaScript engine and multi-threaded runtime designed to be integrated directly into other software applications as a component. It serves as a parallel computation framework that allows JavaScript code to execute across multiple threads, bypassing the standard single-threaded event loop limitation to handle CPU-intensive tasks. The runtime is distinguished by its ability to load and execute modules from the NPM ecosystem and its pluggable execution environment. This architecture allows for custom implementations of memory allocation, system logging, and performance me

Legged Gym is a high-performance simulation platform and toolkit engineered for training autonomous robotic agents in complex, physics-based environments. It provides a comprehensive framework for developing legged locomotion control policies, enabling robots to learn movement strategies for navigating uneven terrain and managing physical disturbances through reinforcement learning. The platform distinguishes itself by utilizing hardware-accelerated physics and headless execution to maximize computational throughput during training. It incorporates a domain randomization pipeline that injects

Jitsu is an open-source customer data platform designed to orchestrate event data pipelines. It captures, transforms, and routes behavioral data from web and server sources into data warehouses and analytics tools, providing a unified infrastructure for managing event streams. The platform distinguishes itself through its focus on self-hosted, containerized operations that grant users full control over their data security and privacy. It features a robust identity resolution engine that stitches disparate user identifiers into persistent profiles across sessions and devices, alongside program

Benthos is a declarative stream processor and data integration pipeline used to route, transform, and filter information between disparate services. It functions as an at-least-once message broker and change data capture engine, using a transaction model to guarantee message delivery despite system crashes or server faults. The system is defined by an observability-first approach, featuring built-in HTTP health probes, performance metrics export, and distributed request flow tracing. It utilizes a plugin architecture that allows the core engine to be extended with custom binaries for new inpu

DevLake is a DevOps data platform and analytics tool designed to orchestrate data pipelines that ingest, transform, and sync metadata from external development tools into a unified database. It functions as a system for collecting and normalizing data from source control, CI/CD pipelines, and issue trackers into a standardized schema to enable consistent software delivery analytics. The platform distinguishes itself by transforming tool-specific data into a common domain model, allowing for the calculation of engineering metrics via SQL. It provides specialized frameworks for measuring DORA m

VINS-Mono is a monocular visual-inertial odometry system and loop closure SLAM framework. It functions as a real-time state estimator that fuses data from a single camera and an inertial measurement unit to determine a robot's position and orientation. The project includes a non-linear optimizer for robotics and tools for sensor calibration. The system distinguishes itself through online sensor calibration, which automatically determines spatial extrinsics and temporal offsets between the camera and inertial unit during operation. It also incorporates rolling shutter distortion correction to

SkyWalking is an application performance monitoring system and observability platform designed to collect and analyze metrics, traces, and logs from distributed microservices. It functions as a distributed tracing platform and a telemetry data pipeline that ingests and aggregates observability data from various language agents. The project features an AI-powered anomaly detector that uses machine learning to calculate metric baselines and identify irregular URI patterns. It includes an eBPF performance profiler for diagnosing CPU and network bottlenecks at the kernel level and generates inter