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CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
[ICCV 2023] Tracking Anything with Decoupled Video Segmentation
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) fo…
SAM with text prompt
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
BTGenBot: a system to generate behavior trees for robots using lightweight (~7 billion parameters) large language models (LLMs)
Behavior Trees Library in C++. Batteries included.
DORA (Dataflow-Oriented Robotic Architecture) is middleware designed to streamline and simplify the creation of AI-based robotic applications. It offers low latency, composable, and distributed dat…
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
llama.cpp (GGUF LLMs) and llava.cpp (GGUF VLMs) for ROS 2
Motion planning and Navigation of AGV/AMR：python implementation of Dijkstra, A*, JPS, D*, LPA*, D* Lite, (Lazy)Theta*, RRT, RRT*, RRT-Connect, Informed RRT*, ACO, Voronoi, PID, DWA, APF, LQR, MPC, …
A quick guide (especially) for trending instruction finetuning datasets
The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.
The simplest, fastest repository for training/finetuning medium-sized GPTs.
An autoregressive character-level language model for making more things
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
MATLAB sample codes for mobile robot navigation
Python sample codes for robotics algorithms.
Motion Planning using Tree Algorithms - Udemy Course Assignments
This package computes the likelihood field of a map.
A solutions manual for Topology by James Munkres (2nd Edition)
A collection of optimized ray cast methods for 2D occupancy grids including the CDDT algorithm. Written in C++ and CUDA with Python wrappers.
Using particle filter to fuse the wheel encoder, IMU and 2D lidar to localize the robot and create an occupancy grid map.
Arduino library for easy communication with MPU6050
