Best AI tools for< Segment Cell Instances >

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.

Segmently is an AI-powered image segmentation tool that allows users to segment images in any desired way and edit them using Generative AI. It eliminates the need for manual pixel-by-pixel image splitting, saving users time and effort. The tool offers extremely accurate segmentation and provides controllability and editability features through text prompts or clicks. Users can segment objects, human figures, body parts, or anything else they desire, and then edit the segmented images with ease. Segmently is designed for post-editability, allowing users to download the segmented images as layered PSD files for further editing.

DeepMake is a powerful AI tool that empowers users to unleash their creativity by providing control over Open Source AI tools for enhancing visual content. With DeepMake, users can create, edit, and enhance images and videos without any usage limits or reliance on cloud services. The application runs locally on the user's computer, offering a higher level of control over AI-generated output and introducing new AI tools regularly to stay at the forefront of AI capabilities.

Spatial.ai is a customer segmentation platform that helps businesses understand their customers' social, mobile, and web behaviors. This data can be used to create targeted marketing campaigns, make better location decisions, and develop predictive models. Spatial.ai's data is built directly from organic consumer behavior, which means richer insights and higher accuracy.

Cargo is a revenue operations platform that helps businesses grow their revenue by providing them with the tools they need to segment, enrich, score, and assign leads, as well as automate their revenue operations. Cargo is designed to be easy to use, even for non-technical users, and it can be integrated with a variety of other business tools. With Cargo, businesses can improve their sales performance, increase their efficiency, and make better decisions about their revenue operations.

Meta AI is an intelligent assistant that offers a range of AI experiences for users, including answering questions, providing advice, creating images, and more. Users can also create their own AI characters or explore AIs made by others through AI Studio. The platform aims to empower users to connect with what matters to them and discover new possibilities through AI technology.

Zeta Global is an AI-powered marketing cloud that helps businesses acquire, grow, and retain customers more efficiently. The Zeta Marketing Platform (ZMP) is a cloud-based system that provides tools for data management, messaging, activation, and more. ZMP is powered by proprietary data and AI, which enables businesses to create individualized experiences and drive outcomes throughout the customer lifecycle.

Show by Animaker is an AI-powered email marketing tool that helps businesses create personalized and engaging email campaigns. With Show, you can automate interactive email creation, define unlimited custom user journeys and audience segments, and track campaign performance with advanced analytics. Show also offers deliverability features such as in-built hard stops, deliverability alerts, and domain warm-up capabilities.

Inventoro is a smart inventory forecasting and replenishment tool that helps businesses optimize their inventory management processes. By analyzing past sales data, the tool predicts future sales, recommends order quantities, reduces inventory size, identifies profitable inventory items, and ensures customer satisfaction by avoiding stockouts. Inventoro offers features such as sales forecasting, product segmentation, replenishment, system integration, and forecast automations. The tool is designed to help businesses decrease inventory, increase revenue, save time, and improve product availability. It is suitable for businesses of all sizes and industries looking to streamline their inventory management operations.

Kursaha is an AI-powered customer engagement and acquisition platform that helps businesses connect with their audiences in a personalized and meaningful way. It offers a range of features such as chat automation, OTP automation, real-time analytics, audience segmentation, and content generation. Kursaha integrates with various tools and systems, making it a comprehensive solution for marketing, data, and product teams.

KLING AI is an advanced artificial intelligence tool designed to streamline and enhance various business processes. It leverages cutting-edge machine learning algorithms to provide accurate insights and predictions for data analysis, customer segmentation, and personalized recommendations. With a user-friendly interface, KLING AI empowers users to make informed decisions and optimize their operations efficiently.

ActiveCampaign is an all-in-one marketing automation platform that helps businesses create and automate personalized customer experiences. It offers a wide range of features, including email marketing, dynamic content, segmentation, sales CRM, landing pages, and forms. ActiveCampaign also integrates with over 900 other marketing apps, making it a powerful tool for businesses of all sizes.

Roboflow is a platform that provides tools for building and deploying computer vision models. It offers a range of features, including data annotation, model training, and deployment. Roboflow is used by over 250,000 engineers to create datasets, train models, and deploy to production.

ScoreApp is a quiz marketing platform that helps businesses attract warm leads, gain powerful insights, and increase sales. With ScoreApp, businesses can create customized quiz funnels that engage customers and deliver personalized results based on their answers. ScoreApp also offers a variety of features to help businesses promote their quizzes and track their results.

Landing AI is a computer vision platform and AI software company that provides a cloud-based platform for building and deploying computer vision applications. The platform includes a library of pre-trained models, a set of tools for data labeling and model training, and a deployment service that allows users to deploy their models to the cloud or edge devices. Landing AI's platform is used by a variety of industries, including automotive, electronics, food and beverage, medical devices, life sciences, agriculture, manufacturing, infrastructure, and pharma.

Fibr AI is a personalized landing page platform that uses AI to deliver ultra-personalized experiences for every ad, email, or audience. With Fibr, businesses can create relevant landing pages for every ad and deliver personalized experiences dynamically, without any coding or hassle. Fibr's key features include a WYSIWYG editor, dynamic web personalization, ad connect, bulk creation, audience building, AI personalizations at scale, A/B testing, reporting and analytics, and integrations with popular marketing platforms. Fibr's benefits include increased conversions, reduced customer acquisition costs, and improved ROI. Fibr is suitable for businesses of all sizes and industries, and is particularly beneficial for businesses with high customer acquisition costs or low conversion rates.

MeDA School is an educational platform dedicated to promoting and nurturing talents in the field of Medical Artificial Intelligence (AI). The platform aims to establish a solid foundation for intelligent and precision medical talent pools in Taiwan and globally. MeDA School facilitates interaction and communication among members of the intelligent medical ecosystem, fostering deep understanding and trust in the operation and tasks of medical AI. The platform offers a blend of virtual and physical courses, inviting domain experts to share cutting-edge knowledge and integrating interdisciplinary knowledge to be practically applied in various fields.

Looti is a B2B lead generation tool that uses AI to find and qualify leads. It offers a variety of features to help businesses find the right leads for their needs, including the ability to fine-tune filters, segment data, and integrate with other tools. Looti is easy to use and provides hyper-qualified leads with contact information.

Evolv AI is an AI-powered platform that focuses on enhancing e-commerce operations and customer experience through the implementation of artificial intelligence. The platform offers solutions for personalization, audience segmentation, marketing strategies, and user experience design, aiming to optimize e-commerce websites and drive revenue growth for businesses.

Contlo is an AI-powered marketing platform that helps businesses create personalized campaigns and automated customer journeys across multiple channels, including email, SMS, WhatsApp, web push, and social media. It uses a brand's own generative AI model to optimize marketing efforts and drive customer engagement. Contlo also offers audience management, data collection, and business insights to help businesses make informed decisions.

cellseg-models.pytorch is a Python library built upon PyTorch for 2D cell/nuclei instance segmentation models. It provides multi-task encoder-decoder architectures and post-processing methods for segmenting cell/nuclei instances. The library offers high-level API to define segmentation models, open-source datasets for training, flexibility to modify model components, sliding window inference, multi-GPU inference, benchmarking utilities, regularization techniques, and example notebooks for training and finetuning models with different backbones.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.

Quantus is a toolkit designed for the evaluation of neural network explanations. It offers more than 30 metrics in 6 categories for eXplainable Artificial Intelligence (XAI) evaluation. The toolkit supports different data types (image, time-series, tabular, NLP) and models (PyTorch, TensorFlow). It provides built-in support for explanation methods like captum, tf-explain, and zennit. Quantus is under active development and aims to provide a comprehensive set of quantitative evaluation metrics for XAI methods.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

BIA `bob` is a Jupyter-based assistant for interacting with data using large language models to generate Python code. It can utilize OpenAI's chatGPT, Google's Gemini, Helmholtz' blablador, and Ollama. Users need respective accounts to access these services. Bob can assist in code generation, bug fixing, code documentation, GPU-acceleration, and offers a no-code custom Jupyter Kernel. It provides example notebooks for various tasks like bio-image analysis, model selection, and bug fixing. Installation is recommended via conda/mamba environment. Custom endpoints like blablador and ollama can be used. Google Cloud AI API integration is also supported. The tool is extensible for Python libraries to enhance Bob's functionality.

The Segment Anything Model (SAM) is a powerful tool that allows users to segment any object in an image with just a few clicks. This makes it a great tool for a variety of tasks, such as object detection, tracking, and editing. SAM is also very easy to use, making it a great option for both beginners and experienced users.

This repository contains an implementation of the Segment-Anything Model (SAM) within the SD WebUI. It allows users to divide layers in the SD WebUI and save them as PSD files. Users can adjust parameters, click 'Generate', and view the output below. A PSD file will be saved in the designated folder. The tool provides various parameters for customization, such as points_per_side, pred_iou_thresh, stability_score_thresh, crops_n_layers, crop_n_points_downscale_factor, and min_mask_region_area.

The AirBnB Clone - The Console project is the first segment of the AirBnB project at Holberton School, aiming to cover fundamental concepts of higher level programming. The goal is to deploy a server as a simple copy of the AirBnB Website (HBnB). The project includes a command interpreter to manage objects for the AirBnB website, allowing users to create new objects, retrieve objects, perform operations on objects, update object attributes, and destroy objects. The project is interpreted/tested on Ubuntu 14.04 LTS using Python 3.4.3.

AnyLabeling is a tool for effortless data labeling with AI support from YOLO and Segment Anything. It combines features from LabelImg and Labelme with an improved UI and auto-labeling capabilities. Users can annotate images with polygons, rectangles, circles, lines, and points, as well as perform auto-labeling using YOLOv5 and Segment Anything. The tool also supports text detection, recognition, and Key Information Extraction (KIE) labeling, with multiple language options available such as English, Vietnamese, and Chinese.

MoneyPrinterTurbo is a tool that can automatically generate video content based on a provided theme or keyword. It can create video scripts, materials, subtitles, and background music, and then compile them into a high-definition short video. The tool features a web interface and an API interface, supporting AI-generated video scripts, customizable scripts, multiple HD video sizes, batch video generation, customizable video segment duration, multilingual video scripts, multiple voice synthesis options, subtitle generation with font customization, background music selection, access to high-definition and copyright-free video materials, and integration with various AI models like OpenAI, moonshot, Azure, and more. The tool aims to simplify the video creation process and offers future plans to enhance voice synthesis, add video transition effects, provide more video material sources, offer video length options, include free network proxies, enable real-time voice and music previews, support additional voice synthesis services, and facilitate automatic uploads to YouTube platform.

FunClip is an open-source, locally deployable automated video editing tool that utilizes the FunASR Paraformer series models from Alibaba DAMO Academy for speech recognition in videos. Users can select text segments or speakers from the recognition results and click the clip button to obtain the corresponding video segments. FunClip integrates advanced features such as the Paraformer-Large model for accurate Chinese ASR, SeACo-Paraformer for customized hotword recognition, CAM++ speaker recognition model, Gradio interactive interface for easy usage, support for multiple free edits with automatic SRT subtitles generation, and segment-specific SRT subtitles.

MaterialSearch is a tool for searching local images and videos using natural language. It provides functionalities such as text search for images, image search for images, text search for videos (providing matching video clips), image search for videos (searching for the segment in a video through a screenshot), image-text similarity calculation, and Pexels video search. The tool can be deployed through the source code or Docker image, and it supports GPU acceleration. Users can configure the tool through environment variables or a .env file. The tool is still under development, and configurations may change frequently. Users can report issues or suggest improvements through issues or pull requests.

FunClip is an open-source, locally deployed automated video clipping tool that leverages Alibaba TONGYI speech lab's FunASR Paraformer series models for speech recognition on videos. Users can select text segments or speakers from recognition results to obtain corresponding video clips. It integrates industrial-grade models for accurate predictions and offers hotword customization and speaker recognition features. The tool is user-friendly with Gradio interaction, supporting multi-segment clipping and providing full video and target segment subtitles. FunClip is suitable for users looking to automate video clipping tasks with advanced AI capabilities.

AudioLLMs is a curated collection of research papers focusing on developing, implementing, and evaluating language models for audio data. The repository aims to provide researchers and practitioners with a comprehensive resource to explore the latest advancements in AudioLLMs. It includes models for speech interaction, speech recognition, speech translation, audio generation, and more. Additionally, it covers methodologies like multitask audioLLMs and segment-level Q-Former, as well as evaluation benchmarks like AudioBench and AIR-Bench. Adversarial attacks such as VoiceJailbreak are also discussed.

MOOSE 2.0 is a leaner, meaner, and stronger tool for 3D medical image segmentation. It is built on the principles of data-centric AI and offers a wide range of segmentation models for both clinical and preclinical settings. MOOSE 2.0 is also versatile, allowing users to use it as a command-line tool for batch processing or as a library package for individual processing in Python projects. With its improved speed, accuracy, and flexibility, MOOSE 2.0 is the go-to tool for segmentation tasks.

Guides B2B startups in a structured customer segment evaluation process. Stop guessing! Ideate, Evaluate & Make data-driven decision.

A storyteller AI that draws a new illustration for every story segment.

Assists with biological image processing tools.

Summarizes academic books by chapters or segments, with user prompts.

Expert in medical imaging AI, adept in machine learning tools.

Assists with personalized, effective email marketing for e-commerce, focusing on engaging content and trends.

Creates detailed, data-driven buyer personas.

I assist salespeople in crafting industry-specific outreach emails.

Guides asset allocation in family segments, focusing on investments.