Best 74 AI image detection and recognition Tools of 2025

eSearch is a cross-platform screen search and screenshot software developed based on Electron, supporting Linux, Windows, and Mac systems. It integrates features such as screenshotting, OCR text recognition, search, translation, sticky notes, screen translation, image search, scrolling screenshots, and screen recording. eSearch aims to provide a convenient and quick way to acquire information from the screen, converting text in images into editable text using OCR technology, supporting multilingual recognition and translation, greatly enhancing work efficiency.

The Image Describer image description generator is a tool that utilizes artificial intelligence technology to provide image descriptions based on user uploads and needs. It comprehends the content of images and generates detailed descriptions or explanations, which helps users better understand the meaning of the images. This tool is not only applicable for general users but also assists visually impaired individuals in understanding image content through text-to-speech functionality. The importance of the image description generator lies in its ability to enhance the accessibility of image content and improve the efficiency of information dissemination.

Viewly is a powerful AI image recognition application that can identify content within images and utilize AI technology for poetry generation and translation into multiple languages. It represents cutting-edge technology in the fields of image recognition and language processing, with key advantages including high recognition accuracy, multilingual support, and a creative AI poetry feature. The background information indicates that it is an ever-evolving product dedicated to providing users with more innovative features. Currently, the product is offered to users for free.

PimEyes is a website that offers reverse image search services using facial recognition technology. Users can upload photos to find similar images or personal information on the internet. This service holds significant value in areas such as privacy protection, locating missing persons, and copyright verification. PimEyes provides users with a powerful tool to help identify and locate images online through its advanced algorithms.

Ultralytics YOLO11 is further developed from the previous YOLO series models, introducing new features and improvements to enhance performance and flexibility. YOLO11 is designed to be fast, accurate, and easy to use, making it ideal for a wide range of tasks including object detection, tracking, instance segmentation, image classification, and pose estimation.

Revisit Anything is a visual location recognition system that utilizes image segment retrieval technology to identify and match locations across different images. It combines SAM (Spatial Attention Module) and DINO (Distributed Knowledge Distillation) technologies to enhance the accuracy and efficiency of visual recognition. This technology holds significant application value in fields such as robotic navigation and autonomous driving.

Joy Caption Alpha One is an AI-powered image description generator that transforms image content into textual descriptions. Utilizing deep learning technology, it understands objects, scenes, and actions in images to produce accurate and vivid descriptions. This technology plays a vital role in assisting visually impaired individuals in understanding image content, enhancing image search capabilities, and improving the accessibility of social media content.

OpenCV is a cross-platform open-source software library for computer vision and machine learning. It provides a wide range of programming features, including but not limited to image processing, video analysis, feature detection, and machine learning. The library is widely used in academic research and commercial projects, favored by developers for its powerful capabilities and flexibility.

GOT-OCR2.0 is an open-source OCR model aimed at advancing optical character recognition technology towards OCR-2.0 through a unified end-to-end framework. This model supports various OCR tasks, including but not limited to standard text recognition, formatted text recognition, fine-grained OCR, multi-crop OCR, and multi-page OCR. It is based on cutting-edge deep learning techniques, capable of handling complex text recognition scenarios with high accuracy and efficiency.

bonding_w_geimini is an image processing application developed on the Streamlit framework, allowing users to upload images for object detection via the Gemini API and draw bounding boxes directly on the images. This application leverages machine learning models to identify and locate objects within images, playing a significant role in fields like image analysis, data annotation, and automated image processing.

Pixel Screenshots is a feature exclusive to Google Pixel phones, utilizing the Gemini Nano AI model to help users save, organize, and quickly recall information embedded in screenshots. This feature automatically recognizes text within the screenshots, such as restaurant addresses, item prices on receipts, and more, while providing intelligent action suggestions based on the content, such as setting reminders or adding details to Google Calendar. Users can also query screenshot information through conversational prompts, such as asking for package tracking numbers for quick and accurate responses.

labelU-Kit is an open-source front-end annotation component library that provides annotation capabilities for images, videos, and audio. It supports various annotation methods including 2D boxes, points, lines, polygons, and 3D boxes. Offered in the form of NPM packages, it allows developers to seamlessly integrate it into their own annotation platforms, enhancing the efficiency and flexibility of data annotation.

LabelU is an open-source data labeling tool designed for efficient annotation of image, video, and audio data, aimed at improving the performance and quality of machine learning models. It supports various annotation types, including label classification, text description, and bounding box, to meet diverse labeling needs.

SAM-guided Graph Cut for 3D Instance Segmentation is a deep learning approach utilizing 3D geometry and multi-view image information for 3D instance segmentation. By employing a 3D-to-2D query framework, this method effectively leverages 2D segmentation models to perform 3D instance segmentation, constructing a superpoint graph through graph cut problems and training via graph neural networks to achieve robust segmentation performance across diverse scene types.

The SA-V Dataset is an open-world video dataset specifically designed for training general object segmentation models, containing 51,000 diverse videos and 643,000 spatio-temporal segmentation masks (masklets). This dataset is intended for computer vision research and is available under a CC BY 4.0 license. The video content covers a wide variety of themes, including locations, objects, and scenes, with masks ranging from large-scale objects like buildings to intricate details like indoor decorations.

Segment Anything Model 2 (SAM 2) is a visual segmentation model launched by Meta's AI research division, FAIR. It achieves real-time video processing through a simple transformer architecture and streaming memory design. The model builds a loop data engine through user interaction, gathering the largest video segmentation dataset to date, SA-V. SAM 2 is trained on this dataset, delivering outstanding performance across a wide range of tasks and visual domains.

Meta Segment Anything Model 2 (SAM 2) is a next-generation model developed by Meta for real-time, promptable object segmentation in videos and images. It achieves state-of-the-art performance and supports zero-shot generalization, allowing it to be applied to previously unseen visual content without needing custom adaptation. The release of SAM 2 follows an open science approach, with code and model weights shared under the Apache 2.0 license, and the SA-V dataset shared under the CC BY 4.0 license.

RapidLayout is an open-source tool focused on layout analysis of document images, capable of analyzing the structural layout of document category images and locating elements such as titles, paragraphs, tables, and images. It supports layout analysis in multiple languages and scenarios, including Chinese and English, to meet diverse business needs.

roboflow/sports is an open-source computer vision toolkit focused on applications in the sports domain. It employs advanced image processing techniques, such as object detection, image segmentation, and keypoint detection, to tackle challenges in sports analysis. Developed by Roboflow, this toolkit aims to promote the application of computer vision technologies in sports and is continuously optimized through community contributions.

RapidOCR is a multilingual OCR toolkit based on ONNXRuntime, OpenVINO, and PaddlePaddle. It converts PaddleOCR models into ONNX format, supporting multi-platform deployment in Python, C++, Java, and C#. It is characterized by speed, lightweight design, and intelligence, addressing memory leakage issues present in PaddleOCR.

Album AI is an experimental project that uses gpt-4o-mini as the visual model, automatically recognizes the metadata of image files in the album, and uses RAG technology to realize dialogue with the album. It can be used as a traditional album, or as an image knowledge base to assist large language models in content generation.

TruthPix is an AI image detection tool designed to help users identify photos that have been manipulated with AI. The application uses advanced AI technology to quickly and accurately identify cloned and manipulated traces in images, thus avoiding users from being misled by false information on social media platforms. The main advantages of the application include: high security, all detections are performed on the device and data is not uploaded; fast performance, analyzing an image takes less than 400 milliseconds; supports multiple AI-generated image detection technologies, such as GANs, Diffusion Models, etc.

OnnxOCR is a lightweight OCR model restructured from PaddleOCR, which frees itself from the PaddlePaddle deep learning training framework to achieve rapid inference speeds. The model supports inference in over 80 languages and, after being converted to an ONNX model, its inference speed is up to 5 times faster than when using the PaddlePaddle framework. OnnxOCR is independent of the deep learning training framework and can be directly deployed, making it suitable for scenarios with limited computational power but a need for accuracy, and it can be deployed on both ARM and x86 architectures.

MASt3R is an advanced 3D image matching model developed by Naver Corporation that specializes in improving geometric 3D vision tasks within the realm of computer vision. Leveraging the latest deep learning technologies, it is capable of achieving precise 3D matching between images, which is of significant importance for fields such as augmented reality, autonomous driving, and robotic navigation.

TF-ID is an object detection model series created by Yifei Hu for extracting tables and figures from academic papers. These models are fine-tuned based on the microsoft/Florence-2 checkpoint, offering versions with or without title text. Their aim is to enhance the accessibility and processing efficiency of information in academic literature.

image-textualization is an automated framework for generating rich and detailed image descriptions. This framework utilizes deep learning technology, enabling it to automatically extract information from images and generate accurate, comprehensive textual descriptions. This technology holds significant application value in areas such as image recognition, content generation, and assisting individuals with visual impairments.

PixelProse, created by the tomg-group-umd, is a large-scale dataset generating over 16 million detailed image descriptions using the advanced vision-language model Gemini 1.0 Pro Vision. This dataset is crucial for developing and improving image-to-text conversion technologies and can be used for tasks like image captioning and visual question answering.

PlantIdentify is an application that utilizes artificial intelligence technology to rapidly identify plant species from user-uploaded photos or pictures taken with their mobile camera. It is suitable for gardening enthusiasts, nature lovers, and anyone interested in the plants around them. Key features include instant plant recognition, free usage, multi-language support, and the ability to save recognition history.

emo-visual-data is a publicly available emoji visual annotation dataset. It collects 5329 emojis through visual annotation completed using the glm-4v and step-free-api projects. This dataset can be used to train and test multimodal large models and is crucial for understanding the relationship between image content and textual descriptions.

Grounding DINO 1.5, developed by IDEA Research, is a series of advanced models designed to push the boundaries of open-world object detection technology. The series includes two models: Grounding DINO 1.5 Pro and Grounding DINO 1.5 Edge, optimized for diverse applications and edge computing scenarios, respectively.