Open-source alternatives to 3d Bat

napari: a fast, interactive, multi-dimensional image viewer for python

CVAT is an open-source computer vision annotation tool and visual dataset management platform. It provides a self-hosted interface for labeling images, videos, and 3D data to create datasets for vision AI models. The platform features AI-assisted data labeling to automate the creation of masks and bounding boxes, utilizing a plug-in system to connect external machine learning models. It includes a consensus-based quality assurance system that verifies label accuracy by comparing independent annotations. The system covers collaborative team management, project organization through task decomp

A graphical user interface to annotate point clouds and 3D data.

labelImg is a desktop image annotation tool and dataset preparation utility used to create labeled datasets for computer vision training. It provides a graphical interface for drawing bounding boxes around objects in images and assigning them class labels to build ground truth data for machine learning models. The software specifically supports the Pascal VOC XML annotation format, exporting image coordinates and class names into standard XML or text structures. It allows users to load predefined class lists from text files to standardize naming across an entire project. Beyond initial label

Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

Labelme is a Python-based image annotation tool used to create computer vision datasets. It serves as a visual editor for semantic segmentation, allowing users to define object boundaries using polygons, rectangles, points, and circles. The application also functions as a multispectral image annotator, supporting high-bit depth TIFF files used in satellite and scientific imagery. The tool incorporates AI-assisted labeling capabilities to automate the creation of masks and polygons. These features allow for shape generation driven by text prompts or interactive point selections, which propose

FiftyOne is a visual tool for curating, analyzing, and managing image and video datasets for machine learning model training. It serves as a platform for identifying annotation errors, refining ground truth labels, and evaluating vision model performance by comparing predictions against ground truth to identify failure modes. The system functions as a containerized data platform that supports team collaboration on large-scale visual datasets in a cloud environment. It includes specialized capabilities for exploring high-dimensional embeddings to discover data clusters and retrieve correspondi

Lichtblick is an integrated visualization and diagnosis tool for robotics, available in your browser or as a desktop app on Linux, Windows, and macOS.

A tool to turn pointcloud data from aerial lidar scans into solid meshes for 3D printing. You can find examples of meshes made with this software on Thingiverse.

blender python scripts

Code for "Leveraging ChatGPT in Pharmacovigilance Event Extraction: An Empirical Study" (EACL 2024).

Using $5 Google Cardboard to replicate HoloLens

https://aclanthology.org/2023.emnlp-main.745.pdf

Rerun is a multimodal data visualizer and robotics data logger designed for rendering synchronized streams of 3D spatial data, images, and time-series metrics. It functions as a tool for capturing high-frequency sensor data and AI outputs into a queryable columnar format, providing a dedicated interface for viewing MCAP recording files and analyzing physical environments. The project distinguishes itself as a machine learning dataset streamer, capable of feeding logged recordings directly into GPU buffers and PyTorch training pipelines without intermediate exports. It supports a high-performa

openai 0.27.4

This repo contains the code used for the EMNLP 2023 paper "Semi-automatic Data Enhancement for Document-Level Relation Extraction with Distant Supervision from Large Language Models".

This repository contains a Blender addon to import reconstruction results of several libraries.

MeshLab is an open-source 3D mesh processing system designed for editing and analyzing unstructured triangular meshes. It functions as a triangular mesh editor, a model visualization suite, and a conversion tool for transforming 3D mesh data between various file formats. The software provides tools for cleaning, healing, and optimizing large 3D models generated from raw digitization and scanning data. It enables the preparation of models for physical 3D printing and the application of surface textures to evaluate the visual appearance of digital models. The system covers a broad range of cap

Robotics visualization and debugging

CloudPeek is a lightweight, c++ single-header, cross-platform point cloud viewer, designed for simplicity and efficiency without relying on heavy external libraries like PCL or Open3D. It provides an intuitive way to visualize and interact with 3D point cloud data across multiple platforms.…

This project is the codebase used for our weak supervision experiments using E3C dataset annotated with InstructGPT-3 and dictionary.

Point cloud importer & renderer for Unity

DeepKE is a knowledge extraction toolkit and framework designed to transform unstructured text into structured knowledge graphs. It provides a pipeline for identifying and classifying named entities, semantic relations, and events, converting raw datasets into structured triples. The project utilizes large language models as tool callers through a standardized context protocol to drive automated data extraction processes. It supports schema-driven extraction across multiple domains and bilingual text, employing joint entity and relation extraction to identify components in a single structured

This is a meta-model distilled from ChatGPT-3.5-turbo for information extraction. This is an intermediate checkpoint that can be well-transferred to all kinds of downstream information extraction tasks.