Showing 135 open source projects for "autonomous"

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  • 1
    YoloV3 Implemented in TensorFlow 2.0

    YoloV3 Implemented in TensorFlow 2.0

    YoloV3 Implemented in Tensorflow 2.0

    ...The project supports both pretrained models and full training pipelines, enabling researchers and developers to adapt YOLOv3 for tasks such as surveillance, robotics, autonomous driving, and image analysis.
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  • 2
    LangChain Apps on Production with Jina

    LangChain Apps on Production with Jina

    Langchain Apps on Production with Jina & FastAPI

    Jina is an open-source framework for building scalable multi-modal AI apps on Production. LangChain is another open-source framework for building applications powered by LLMs. long-chain-serve helps you deploy your LangChain apps on Jina AI Cloud in a matter of seconds. You can benefit from the scalability and serverless architecture of the cloud without sacrificing the ease and convenience of local development. And if you prefer, you can also deploy your LangChain apps on your own...
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  • 3
    Free-Auto-GPT

    Free-Auto-GPT

    Free AutoGPT enables autonomous AI tasks without paid APIs

    Free Auto GPT is an open source project that delivers a simplified version of an autonomous AI agent capable of completing tasks independently. It allows users to run an AutoGPT-style system without relying on paid OpenAI APIs, making it more accessible for experimentation and personal use. Free Auto GPT can take a goal, break it into smaller steps, and execute actions in a loop to achieve results with minimal human input.
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  • 4
    AB3DMOT

    AB3DMOT

    Official Python Implementation for "3D Multi-Object Tracking

    AB3DMOT is a real-time 3D multi-object tracking framework designed for applications such as autonomous driving and robotics perception. The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. ...
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  • 5
    AEA Framework

    AEA Framework

    A framework for autonomous economic agent (AEA) development

    agents-aea by Fetch.ai is a framework for building autonomous economic agents (AEAs) that can act independently, communicate, and transact on decentralized networks. It focuses on enabling AI-driven agents to participate in digital marketplaces and ecosystems.
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  • 6
    BEVFormer

    BEVFormer

    Implementation of BEVFormer, a camera-only framework

    3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries. ...
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  • 7
    Couler

    Couler

    Unified Interface for Constructing and Managing Workflows

    ...Couler endeavors to provide a unified interface for constructing and optimizing workflows across various workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow. Couler enhances workflow efficiency through features like Autonomous Workflow Construction, Automatic Artifact Caching Mechanisms, Big Workflow Auto Parallelism Optimization, and Automatic Hyperparameters Tuning.
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  • 8
    Deep Learning Drizzle

    Deep Learning Drizzle

    Drench yourself in Deep Learning, Reinforcement Learning

    ...Computer Vision courses which are DL & ML heavy. Speech recognition courses which are DL heavy. Structured Courses on Geometric, Graph Neural Networks. Section on Autonomous Vehicles. Section on Computer Graphics with ML/DL focus.
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  • 9
    Coach

    Coach

    Enables easy experimentation with state of the art algorithms

    ...With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments to solve. Coach collects statistics from the training process and supports advanced visualization techniques for debugging the agent being trained. Coach supports many state-of-the-art reinforcement learning algorithms, which are separated into three main classes - value optimization, policy optimization, and imitation learning. ...
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  • 10
    The RoboCup competition is an international event in which teams of autonomous robots play soccer against one another. This project provides resources for the RoboCup F180, or small-sized league. It also provides a mechanism through which teams can c
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