Best AI tools for< Generate Objects >

Luma Dream Machine is an AI video generator tool that creates high-quality, realistic videos from text and images. It is a scalable and efficient transformer model trained directly on videos, capable of generating physically accurate and eventful shots. The tool aims to build a universal imagination engine, enabling users to bring their creative visions to life effortlessly.

Luma AI is a 3D capture platform that allows users to create interactive 3D scenes from videos. With Luma AI, users can capture 3D models of people, objects, and environments, and then use those models to create interactive experiences such as virtual tours, product demonstrations, and training simulations.

Hive AI provides a suite of AI models and solutions for understanding, searching, and generating content. Their AI models can be integrated into applications via APIs, enabling developers to add advanced content understanding capabilities to their products. Hive AI's solutions are used by businesses in various industries, including digital platforms, sports, media, and marketing, to streamline content moderation, automate image search and authentication, measure sponsorships, and monetize ad inventory.

MostArt is an AI-powered image generator that allows users to create unique and realistic images from scratch. With MostArt, you can generate images of people, animals, objects, and landscapes, all with just a few clicks. The app is easy to use and requires no prior experience with image editing or graphic design. Simply enter a few keywords into the search bar, and MostArt will generate a variety of images that match your criteria. You can then choose the image you like best and download it to your computer.

Boximator is an AI-powered tool that allows users to generate rich and controllable motions for video synthesis. It uses a combination of deep learning and computer vision techniques to analyze and interpret text prompts, and then generate realistic and visually appealing motions that match the user's intent. Boximator is particularly well-suited for creating videos of human characters, but it can also be used to generate motions for other objects, such as animals, vehicles, and even abstract shapes.

Dzine (formerly Stylar.ai) is a powerful AI image generation and design tool that provides users with unparalleled control over image composition and style. It offers predefined styles for effortless design customization, layering, positioning, and sketching tools for intuitive design, and an 'Enhance' feature to address common challenges with AI-generated images. With a user-friendly interface suitable for all skill levels, Dzine makes it easy to create stunning and stylish images. It supports high-resolution exports and provides free credits for new users to try out its features.

Image Bear AI is an advanced image recognition tool that utilizes artificial intelligence to analyze and identify objects within images. The application is designed to assist users in various industries such as e-commerce, security, and healthcare by providing accurate and efficient image analysis capabilities. With its cutting-edge technology, Image Bear AI offers a user-friendly interface and fast processing speeds, making it a valuable tool for businesses looking to streamline their image recognition processes.

SceneryAI is an AI-powered image editing tool that allows users to quickly and easily edit images. With SceneryAI, users can remove unwanted objects, change the background, and adjust the lighting and colors of their images. SceneryAI is also able to generate new images from scratch, making it a powerful tool for creating unique and eye-catching visuals.

Peqaboo is an AI-powered pet social app designed to help pet owners with various aspects of pet care. The app allows users to ask Boo AI questions about their pets, identify toxic plants or foods, and receive instant answers based on their pet's profile. Peqaboo also offers a feature to train a new Boo AI, enabling users to transform their knowledge into AI tools. The app aims to make pet life easier and more enjoyable by providing personalized pet care advice and fostering a global pet community.

Magic Studio is an AI-powered image editing tool that allows users to create beautiful images effortlessly. With features like instant clean-up, background removal, and image transformation, Magic Studio simplifies the process of editing photos for both personal and commercial projects. The tool is designed to be user-friendly, making it accessible to individuals with no design skills. Magic Studio is trusted by millions worldwide and offers a range of AI-powered editing tools to enhance images with ease.

Photoleap is a powerful and creative photo editing app that utilizes AI technology to enhance your photos. With a wide range of AI-powered tools, you can transform your photos into works of art, remove unwanted objects, change backgrounds, and more. Photoleap also offers a variety of editing tools, filters, and effects to help you unleash your creativity and create stunning images. Whether you're a professional photographer or just starting out, Photoleap has everything you need to take your photos to the next level.

PhotoEditor.ai is a cutting-edge visual AI platform powered by Artificial Intelligence that revolutionizes photo editing. It offers a powerful AI toolset for creative photo and design editing needs, with features like image generation, detail enhancement, uncropping, inpainting, background removal, object cleanup, image enhancement, and upscaling. The application is easy to use, works on web and mobile platforms, and is free for images up to 720px. It prioritizes user privacy by deleting uploaded images within 1 hour. PhotoEditor.ai is suitable for personal projects, creative agencies, real estate, e-commerce, photography, and logo/watermark editing.

Renovate AI is an advanced AI-powered home design application that revolutionizes interior and exterior designing. It offers real-time visualizations, intelligent object recognition, customizable styles, object removal, infinite design variations, and professional remodeling tools. Renovate AI is a versatile tool suitable for designers, homeowners, and real estate agents, providing unparalleled detail and accuracy in design planning.

Magic Studio is an AI-powered image editing tool that allows users to create professional-looking images, product pages, ads, and social media posts in minutes, without any design skills. It offers a range of features such as object and background removal, image upscaling, and AI-generated art, making it a versatile tool for both personal and commercial use.

The AI-Powered Image to Caption Generator is a revolutionary tool that utilizes artificial intelligence to analyze images and generate engaging captions tailored to each image. By recognizing key objects, scenes, and emotional tones in the image, the tool crafts captivating narratives that spark conversation and boost engagement. Users can save time, maintain brand consistency, and stay ahead of social media marketing trends with this innovative AI application.

jsonAI is an AI tool that allows users to easily transform data into structured JSON format. Users can define their schema, add custom prompts, and receive AI-structured JSON responses. The tool enables users to create complex schemas with nested objects, control the response JSON on the fly, and test their JSON data in real-time. jsonAI offers a free trial plan, seamless integration with existing apps, and ensures data security by not storing user data on their servers.

This website provides a curated collection of AI tools specifically designed for designers, including tools for UI & UX, colors, images, typography, marketing, and productivity. These tools leverage artificial intelligence to enhance and streamline the design workflow, enabling designers to create stunning visuals, generate content, automate tasks, and improve their overall productivity.

Stork is an AI App Directory & Marketplace that provides a comprehensive listing of over 9000 AI tools and agents. The platform allows users to search and discover AI tools based on their specific needs and preferences. Stork also offers a variety of resources and support to help users get the most out of AI technology.

Segment Anything by Meta AI is an advanced AI model that specializes in image segmentation, allowing users to easily 'cut out' any object in an image with a single click. The model, known as SAM, offers zero-shot generalization to unfamiliar objects and images without the need for additional training. SAM's promptable design enables a wide range of segmentation tasks through input prompts, making it a versatile tool for various applications.

Stability AI is an AI application that offers a suite of models for various modalities such as image, video, audio, 3D, and language. It provides cutting-edge generative AI technology with a focus on stability and quality. Users can access advanced AI models for tasks like text-to-image generation, video modeling, audio generation, and more. The application also offers licensing options for commercial use and self-hosting benefits.

Chrome AI is a Vercel AI provider for Chrome's built-in model (Gemini Nano). It allows users to create language models using Chrome's AI capabilities. The tool is under development and may contain errors and frequent changes. Users can install the ChromeAI provider module and use it to generate text, stream text, and generate objects. To enable AI in Chrome, users need to have Chrome version 127 or greater and turn on specific flags. The tool is designed for developers and researchers interested in experimenting with Chrome's built-in AI features.

Here we will keep track of the AI Game Development Tools, including LLM, Agent, Code, Writer, Image, Texture, Shader, 3D Model, Animation, Video, Audio, Music, Singing Voice and Analytics. 🔥 * Tool (AI LLM) * Game (Agent) * Code * Framework * Writer * Image * Texture * Shader * 3D Model * Avatar * Animation * Video * Audio * Music * Singing Voice * Speech * Analytics * Video Tool

A simple and convenient interface for using various neural network models. Users can interact with LLM using text, voice, and image input to generate images, videos, 3D objects, music, and audio. The tool supports a wide range of models for different tasks such as image generation, video generation, audio file separation, voice conversion, and more. Users can also view files from the outputs directory in a gallery, download models, change application settings, and check system sensors. The goal of the project is to create an easy-to-use application for utilizing neural network models.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

ModelFusion is an abstraction layer for integrating AI models into JavaScript and TypeScript applications, unifying the API for common operations such as text streaming, object generation, and tool usage. It provides features to support production environments, including observability hooks, logging, and automatic retries. You can use ModelFusion to build AI applications, chatbots, and agents. ModelFusion is a non-commercial open source project that is community-driven. You can use it with any supported provider. ModelFusion supports a wide range of models including text generation, image generation, vision, text-to-speech, speech-to-text, and embedding models. ModelFusion infers TypeScript types wherever possible and validates model responses. ModelFusion provides an observer framework and logging support. ModelFusion ensures seamless operation through automatic retries, throttling, and error handling mechanisms. ModelFusion is fully tree-shakeable, can be used in serverless environments, and only uses a minimal set of dependencies.

GPT4Point is a unified framework for point-language understanding and generation. It aligns 3D point clouds with language, providing a comprehensive solution for tasks such as 3D captioning and controlled 3D generation. The project includes an automated point-language dataset annotation engine, a novel object-level point cloud benchmark, and a 3D multi-modality model. Users can train and evaluate models using the provided code and datasets, with a focus on improving models' understanding capabilities and facilitating the generation of 3D objects.

The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured output (objects). It provides a simple yet robust interface and supports llama-cpp-python and OpenAI endpoints with GBNF grammar support (like the llama-cpp-python server) and the llama.cpp backend server. It works by generating a formal GGML-BNF grammar of the user defined structures and functions, which is then used by llama.cpp to generate text valid to that grammar. In contrast to most GBNF grammar generators it also supports nested objects, dictionaries, enums and lists of them.

AI-TOD is a dataset for tiny object detection in aerial images, containing 700,621 object instances across 28,036 images. Objects in AI-TOD are smaller with a mean size of 12.8 pixels compared to other aerial image datasets. To use AI-TOD, download xView training set and AI-TOD_wo_xview, then generate the complete dataset using the provided synthesis tool. The dataset is publicly available for academic and research purposes under CC BY-NC-SA 4.0 license.

Swirl is an open-source software that allows users to simultaneously search multiple content sources and receive AI-ranked results. It connects to various data sources, including databases, public data services, and enterprise sources, and utilizes AI and LLMs to generate insights and answers based on the user's data. Swirl is easy to use, requiring only the download of a YML file, starting in Docker, and searching with Swirl. Users can add credentials to preloaded SearchProviders to access more sources. Swirl also offers integration with ChatGPT as a configured AI model. It adapts and distributes user queries to anything with a search API, re-ranking the unified results using Large Language Models without extracting or indexing anything. Swirl includes five Google Programmable Search Engines (PSEs) to get users up and running quickly. Key features of Swirl include Microsoft 365 integration, SearchProvider configurations, query adaptation, synchronous or asynchronous search federation, optional subscribe feature, pipelining of Processor stages, results stored in SQLite3 or PostgreSQL, built-in Query Transformation support, matching on word stems and handling of stopwords, duplicate detection, re-ranking of unified results using Cosine Vector Similarity, result mixers, page through all results requested, sample data sets, optional spell correction, optional search/result expiration service, easily extensible Connector and Mixer objects, and a welcoming community for collaboration and support.

Cohere's Build-Your-Own-Connector framework allows integration of Cohere's Command LLM via the Chat API endpoint to any datastore/software holding text information with a search endpoint. Enables user queries grounded in proprietary information. Use-cases include question/answering, knowledge working, comms summary, and research. Repository provides code for popular datastores and a template connector. Requires Python 3.11+ and Poetry. Connectors can be built and deployed using Docker. Environment variables set authorization values. Pre-commits for linting. Connectors tailored to integrate with Cohere's Chat API for creating chatbots. Connectors return documents as JSON objects for Cohere's API to generate answers with citations.

This Helm chart bootstraps an Airflow deployment on a Kubernetes cluster using the Helm package manager. The version of this chart does not correlate to any other component. Users should not expect feature parity between OSS airflow chart and the Astronomer airflow-chart for identical version numbers. To install this helm chart remotely (using helm 3) kubectl create namespace airflow helm repo add astronomer https://helm.astronomer.io helm install airflow --namespace airflow astronomer/airflow To install this repository from source sh kubectl create namespace airflow helm install --namespace airflow . Prerequisites: Kubernetes 1.12+ Helm 3.6+ PV provisioner support in the underlying infrastructure Installing the Chart: sh helm install --name my-release . The command deploys Airflow on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation. Upgrading the Chart: First, look at the updating documentation to identify any backwards-incompatible changes. To upgrade the chart with the release name `my-release`: sh helm upgrade --name my-release . Uninstalling the Chart: To uninstall/delete the `my-release` deployment: sh helm delete my-release The command removes all the Kubernetes components associated with the chart and deletes the release. Updating DAGs: Bake DAGs in Docker image The recommended way to update your DAGs with this chart is to build a new docker image with the latest code (`docker build -t my-company/airflow:8a0da78 .`), push it to an accessible registry (`docker push my-company/airflow:8a0da78`), then update the Airflow pods with that image: sh helm upgrade my-release . --set images.airflow.repository=my-company/airflow --set images.airflow.tag=8a0da78 Docker Images: The Airflow image that are referenced as the default values in this chart are generated from this repository: https://github.com/astronomer/ap-airflow. Other non-airflow images used in this chart are generated from this repository: https://github.com/astronomer/ap-vendor. Parameters: The complete list of parameters supported by the community chart can be found on the Parameteres Reference page, and can be set under the `airflow` key in this chart. The following tables lists the configurable parameters of the Astronomer chart and their default values. | Parameter | Description | Default | | :----------------------------- | :-------------------------------------------------------------------------------------------------------- | :---------------------------- | | `ingress.enabled` | Enable Kubernetes Ingress support | `false` | | `ingress.acme` | Add acme annotations to Ingress object | `false` | | `ingress.tlsSecretName` | Name of secret that contains a TLS secret | `~` | | `ingress.webserverAnnotations` | Annotations added to Webserver Ingress object | `{}` | | `ingress.flowerAnnotations` | Annotations added to Flower Ingress object | `{}` | | `ingress.baseDomain` | Base domain for VHOSTs | `~` | | `ingress.auth.enabled` | Enable auth with Astronomer Platform | `true` | | `extraObjects` | Extra K8s Objects to deploy (these are passed through `tpl`). More about Extra Objects. | `[]` | | `sccEnabled` | Enable security context constraints required for OpenShift | `false` | | `authSidecar.enabled` | Enable authSidecar | `false` | | `authSidecar.repository` | The image for the auth sidecar proxy | `nginxinc/nginx-unprivileged` | | `authSidecar.tag` | The image tag for the auth sidecar proxy | `stable` | | `authSidecar.pullPolicy` | The K8s pullPolicy for the the auth sidecar proxy image | `IfNotPresent` | | `authSidecar.port` | The port the auth sidecar exposes | `8084` | | `gitSyncRelay.enabled` | Enables git sync relay feature. | `False` | | `gitSyncRelay.repo.url` | Upstream URL to the git repo to clone. | `~` | | `gitSyncRelay.repo.branch` | Branch of the upstream git repo to checkout. | `main` | | `gitSyncRelay.repo.depth` | How many revisions to check out. Leave as default `1` except in dev where history is needed. | `1` | | `gitSyncRelay.repo.wait` | Seconds to wait before pulling from the upstream remote. | `60` | | `gitSyncRelay.repo.subPath` | Path to the dags directory within the git repository. | `~` | Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`. For example, sh helm install --name my-release --set executor=CeleryExecutor --set enablePodLaunching=false . Walkthrough using kind: Install kind, and create a cluster We recommend testing with Kubernetes 1.25+, example: sh kind create cluster --image kindest/node:v1.25.11 Confirm it's up: sh kubectl cluster-info --context kind-kind Add Astronomer's Helm repo sh helm repo add astronomer https://helm.astronomer.io helm repo update Create namespace + install the chart sh kubectl create namespace airflow helm install airflow -n airflow astronomer/airflow It may take a few minutes. Confirm the pods are up: sh kubectl get pods --all-namespaces helm list -n airflow Run `kubectl port-forward svc/airflow-webserver 8080:8080 -n airflow` to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working. Login as _admin_ and password _admin_. Build a Docker image from your DAGs: 1. Start a project using astro-cli, which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`. `sh mkdir my-airflow-project && cd my-airflow-project astro dev init` 2. Then build the image: `sh docker build -t my-dags:0.0.1 .` 3. Load the image into kind: `sh kind load docker-image my-dags:0.0.1` 4. Upgrade Helm deployment: sh helm upgrade airflow -n airflow --set images.airflow.repository=my-dags --set images.airflow.tag=0.0.1 astronomer/airflow Extra Objects: This chart can deploy extra Kubernetes objects (assuming the role used by Helm can manage them). For Astronomer Cloud and Enterprise, the role permissions can be found in the Commander role. yaml extraObjects: - apiVersion: batch/v1beta1 kind: CronJob metadata: name: "{{ .Release.Name }}-somejob" spec: schedule: "*/10 * * * *" concurrencyPolicy: Forbid jobTemplate: spec: template: spec: containers: - name: myjob image: ubuntu command: - echo args: - hello restartPolicy: OnFailure Contributing: Check out our contributing guide! License: Apache 2.0 with Commons Clause

LLM Blueprint is an official implementation of a paper that enables text-to-image generation with complex and detailed prompts. It leverages Large Language Models (LLMs) to extract critical components from text prompts, including bounding box coordinates for foreground objects, detailed textual descriptions for individual objects, and a succinct background context. The tool operates in two phases: Global Scene Generation creates an initial scene using object layouts and background context, and an Iterative Refinement Scheme refines box-level content to align with textual descriptions, ensuring consistency and improving recall compared to baseline diffusion models.

biniou is a self-hosted webui for various GenAI (generative artificial intelligence) tasks. It allows users to generate multimedia content using AI models and chatbots on their own computer, even without a dedicated GPU. The tool can work offline once deployed and required models are downloaded. It offers a wide range of features for text, image, audio, video, and 3D object generation and modification. Users can easily manage the tool through a control panel within the webui, with support for various operating systems and CUDA optimization. biniou is powered by Huggingface and Gradio, providing a cross-platform solution for AI content generation.

Trex is a tool that transforms unstructured data into structured data by specifying a regex or context-free grammar. It intelligently restructures data to conform to the defined schema. It offers a Python client for installation and requires an API key obtained by signing up at automorphic.ai. The tool supports generating structured JSON objects based on user-defined schemas and prompts. Trex aims to provide significant speed improvements, structured custom CFG and regex generation, and generation from JSON schema. Future plans include auto-prompt generation for unstructured ETL and more intelligent models.

DotRecast is a C# port of Recast & Detour, a navigation library used in many AAA and indie games and engines. It provides automatic navmesh generation, fast turnaround times, detailed customization options, and is dependency-free. Recast Navigation is divided into multiple modules, each contained in its own folder: - DotRecast.Core: Core utils - DotRecast.Recast: Navmesh generation - DotRecast.Detour: Runtime loading of navmesh data, pathfinding, navmesh queries - DotRecast.Detour.TileCache: Navmesh streaming. Useful for large levels and open-world games - DotRecast.Detour.Crowd: Agent movement, collision avoidance, and crowd simulation - DotRecast.Detour.Dynamic: Robust support for dynamic nav meshes combining pre-built voxels with dynamic objects which can be freely added and removed - DotRecast.Detour.Extras: Simple tool to import navmeshes created with A* Pathfinding Project - DotRecast.Recast.Toolset: All modules - DotRecast.Recast.Demo: Standalone, comprehensive demo app showcasing all aspects of Recast & Detour's functionality - Tests: Unit tests Recast constructs a navmesh through a multi-step mesh rasterization process: 1. First Recast rasterizes the input triangle meshes into voxels. 2. Voxels in areas where agents would not be able to move are filtered and removed. 3. The walkable areas described by the voxel grid are then divided into sets of polygonal regions. 4. The navigation polygons are generated by re-triangulating the generated polygonal regions into a navmesh. You can use Recast to build a single navmesh, or a tiled navmesh. Single meshes are suitable for many simple, static cases and are easy to work with. Tiled navmeshes are more complex to work with but better support larger, more dynamic environments. Tiled meshes enable advanced Detour features like re-baking, hierarchical path-planning, and navmesh data-streaming.

Simple-OpenAI is a Java library that provides a simple way to interact with the OpenAI API. It offers consistent interfaces for various OpenAI services like Audio, Chat Completion, Image Generation, and more. The library uses CleverClient for HTTP communication, Jackson for JSON parsing, and Lombok to reduce boilerplate code. It supports asynchronous requests and provides methods for synchronous calls as well. Users can easily create objects to communicate with the OpenAI API and perform tasks like text-to-speech, transcription, image generation, and chat completions.

Multiple perspective 16-bit sprite/pixel art objects/characters. Just name an object. A great starting point for 2d game assets.

Pass in the attributes of Pojo entity class objects, generate corresponding addition, deletion, modification, and pagination query functions, including generating database connection configuration files yaml and database script files, as well as XML dynamic SQL concatenation statements.

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