# Best Image Recognition Software - Page 3 *By [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)* Image recognition software, also known as computer vision, allows applications to understand and interpret images or videos, taking image data as input and providing outputs such as labels or bounding boxes, enabling capabilities including object recognition, facial recognition, logo detection, and scene reconstruction. ### Core Capabilities of Image Recognition Software To qualify for inclusion in the Image Recognition category, a product must: - Provide a deep learning algorithm specifically for image recognition - Connect with image data pools to learn a specific solution or function - Consume image data as an input and provide an output - Provide image recognition capabilities to other applications, processes, or services ### Common Use Cases for Image Recognition Software Data scientists and developers use image recognition software to add computer vision capabilities to applications and automate visual analysis tasks. Common use cases include: - Training custom image recognition models for object detection, facial recognition, and explicit content detection - Adding image or video recognition features to applications via machine learning libraries, APIs, or SDKs - Enabling edge-based or on-device image processing for real-time recognition without cloud dependency ### How Image Recognition Software Differs from Other Tools Image recognition software is distinct from related categories: [data science and machine learning platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) provide broad ML capabilities and are not solely focused on image recognition, while [machine learning software](https://www.g2.com/categories/machine-learning) covers other ML capabilities such as recommendation engines and pattern recognition beyond visual data. Software designed specifically for recognizing text within images belongs to the [optical character recognition (OCR)](https://www.g2.com/categories/ocr) category. ### Insights from G2 on Image Recognition Software Based on category trends on G2, API flexibility and accuracy of deep learning models stand out as standout capabilities. Faster integration of computer vision features into products stand out as a primary outcome of adoption. ## Category Overview **Total Products under this Category:** 393 ## Trust & Credibility Stats **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 1,500+ Authentic Reviews - 393+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. ## Best Image Recognition Software At A Glance - **Leader:** [Roboflow](https://www.g2.com/products/roboflow/reviews) - **Highest Performer:** [Kwikpic](https://www.g2.com/products/kwikpic/reviews) - **Easiest to Use:** [Roboflow](https://www.g2.com/products/roboflow/reviews) - **Top Trending:** [NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/products/nvidia-deep-learning-gpu-training-system-digits/reviews) - **Best Free Software:** [Roboflow](https://www.g2.com/products/roboflow/reviews) ## Top-Rated Products (Ranked by G2 Score) ### 1. [Nilearn](https://www.g2.com/products/nilearn/reviews) Nilearn is a Python module for fast and easy statistical learning on NeuroImaging data that leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. **Average Rating:** 4.2/5.0 **Total Reviews:** 3 **User Satisfaction Scores:** - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) **Seller Details:** - **Seller:** [Nilearn](https://www.g2.com/sellers/nilearn) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 67% Enterprise, 33% Small-Business ### 2. [SentiSight.ai](https://www.g2.com/products/sentisight-ai/reviews) SentiSight.ai is a web-based platform that can be used for image labeling and for developing AI-based image recognition applications. It has two major goals: the first is to make the image annotation task as convenient and efficient as possible, even for large projects with many people working on image labeling, and the second is to provide a smooth and user-friendly interface for training and deploying deep neural network models. The ability to perform both of these tasks on the same platform provides the advantage of being able to label images and then train and improve models in an iterative way. SentiSight.ai offers powerful features, such as: Image labeling. Our labeling tool allows adding classification labels, bounding boxes, polygons, points, polylines, and bitmaps. Bitmaps can be easily converted to polygons and vice versa. Moreover, each labeled object can have several child objects, such as key-points or attributes. The labeled images can be directly used for model training on the SentiSight.ai platform, or they can be downloaded and used for in-house model training. Smart labeling tool. This tool can be used to significantly increase the speed of bitmap labeling. The smart labeling tool allows users to select a few points in the foreground and the background and let the AI extract the labeled object. Shared labeling projects and time tracking. To make large annotation project handling easier, SentiSight.ai allows a project to be shared among multiple users so that multiple people can label images in the same project. The project manager can quickly filter and review the images labeled by a particular project member, track each person’s progress and time spent on labeling, as well as manage user roles and permissions. Classification model training. This type of model can be used to identify certain objects in an image, such as a cat or a dog, but without specifying their location. They can also be trained to identify more abstract concepts, such as “summer” or “winter”. Object detection model training. This type of model can be used not to only identify a certain object, but also to predict its exact location in an image. For each object predicted to be inside the image, the model also predicts a rectangular bounding box that denotes the object’s location. This is very useful when you need to know not only what is inside the image, but also the relative location and number of objects. Online and offline models (free 30-day trial available). SentiSight.ai offers a possibility to use your deep learning models both online and offline. Online models can be used via REST API or web interface. Both of these options require internet connection. Another option is to download and use the image recognition model offline. An offline model can be downloaded as a free 30-day trial after which the user has an option to buy a license. The price of the license depends on the speed of the model, and it is a single time payment. Pre-trained models. In addition to the possibility of training image recognition models yourself, SentiSight.ai also provides several pre-trained models that can be used out-of-the-box without any additional training. These pre-trained models can be used for several tasks, such as content moderation, goods classification, automatic hashtags, people counting and more. Image Similarity search. This is another ready-to-use feature that allows users to upload an image and find all similar images to this query in their data set. It also allows users to perform NvN similarity searches in their data set where all similar image pairs are retrieved. **Average Rating:** 4.8/5.0 **Total Reviews:** 3 **User Satisfaction Scores:** - **Object Detection:** 8.3/10 (Category avg: 8.7/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) - **Custom Image Detection:** 8.3/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [NeuroTechnology](https://www.g2.com/sellers/neurotechnology) - **Year Founded:** 1990 - **HQ Location:** Vilnius, LT - **Twitter:** @StockGeist (272 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/neurotechnology/ (89 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 67% Small-Business ### 3. [Vize.ai - Custom Image Classification](https://www.g2.com/products/vize-ai-custom-image-classification/reviews) Vize.ai AI is custom image recognition and classification API, designed to allow developers and businesses to analyze image data. **Average Rating:** 4.8/5.0 **Total Reviews:** 3 **User Satisfaction Scores:** - **Object Detection:** 8.3/10 (Category avg: 8.7/10) - **Ease of Use:** 9.4/10 (Category avg: 8.8/10) - **Custom Image Detection:** 8.3/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [Vize](https://www.g2.com/sellers/vize) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 67% Small-Business, 33% Mid-Market #### Pros & Cons **Pros:** - AI Technology (1 reviews) - Annotation Efficiency (1 reviews) - Ease of Use (1 reviews) ### 4. [AForge.NET](https://www.g2.com/products/aforge-net/reviews) AForge.MachineLearning is a namespace that contains interfaces and classes for different algorithms of machine learning. **Average Rating:** 3.8/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Ease of Use:** 6.7/10 (Category avg: 8.8/10) **Seller Details:** - **Seller:** [Accord.NET](https://www.g2.com/sellers/accord-net) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 50% Enterprise, 50% Mid-Market ### 5. [AscenderAI](https://www.g2.com/products/ascenderai/reviews) Ascender AI LLC was founded in 2019 by a visionary research scientist and two well established AI entrepreneurs.  Braddock Gaskill, the CEO, has over 25 years of experience in AI and machine learning. Co-founders Mudar Yaghi and Mohammad Shihadah have spent the past 30 years bringing a family of pioneering AI-driven companies to life. **Average Rating:** 4.5/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Object Detection:** 10.0/10 (Category avg: 8.7/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) - **Custom Image Detection:** 10.0/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [Braddock Gaskill](https://www.g2.com/sellers/braddock-gaskill) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market ### 6. [Azure AI Video Indexer](https://www.g2.com/products/azure-ai-video-indexer/reviews) Azure AI Video Indexer is a cloud and edge video analytics service that uses AI to extract actionable insights from stored videos. Enhance ad insertion, digital asset management, and media libraries by analyzing audio and video content—no machine learning expertise necessary. **Average Rating:** 4.5/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Object Detection:** 8.3/10 (Category avg: 8.7/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) - **Custom Image Detection:** 10.0/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [Microsoft](https://www.g2.com/sellers/microsoft) - **Year Founded:** 1975 - **HQ Location:** Redmond, Washington - **Twitter:** @microsoft (13,105,844 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/microsoft/ (227,697 employees on LinkedIn®) - **Ownership:** MSFT **Reviewer Demographics:** - **Company Size:** 100% Small-Business #### Pros & Cons **Pros:** - Features (2 reviews) - Automation (1 reviews) - Facial Recognition (1 reviews) - Object Recognition (1 reviews) **Cons:** - Expensive (1 reviews) - Privacy Issues (1 reviews) ### 7. [Catchoom CraftAR Image Recognition & Augmented Reality](https://www.g2.com/products/catchoom-craftar-image-recognition-augmented-reality/reviews) CraftAR by Catchoom is an image recognition and augmented reality platform for mobile and web applications. **Average Rating:** 4.8/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Object Detection:** 10.0/10 (Category avg: 8.7/10) - **Ease of Use:** 6.7/10 (Category avg: 8.8/10) - **Custom Image Detection:** 8.3/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [Partium](https://www.g2.com/sellers/partium) - **Year Founded:** 2020 - **HQ Location:** Philadelphia, US - **Twitter:** @partiumio (2,105 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/partium-io/ (49 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 50% Mid-Market, 50% Small-Business ### 8. [DagsHub](https://www.g2.com/products/dagshub/reviews) DagsHub is a platform that allows you to easily create high-quality datasets for better model performance A single AI platform to curate vision, audio, and document data - automate labeling workflows, and evaluate models. Enterprises with sensitive data, can run on their own infrastructure on-prem and get a full AI platform. Data curation - create the very best datasets. Data annotation - annotate your vision, audio, and document data. Auto labeling - automate your annotation flow with pre-built templates and active learning. Data versioning - version your datasets for reproducibility. Experiment tracking - track your experiment progress, understand trends, and compare results. Model registry - manage your models and deployments in one place. The top data scientists build AI with DagsHub including teams at: Google, Harvard Medicine, Beewise, Macso, and Mana.bio **Average Rating:** 4.8/5.0 **Total Reviews:** 14 **User Satisfaction Scores:** - **Object Detection:** 10.0/10 (Category avg: 8.7/10) - **Ease of Use:** 9.2/10 (Category avg: 8.8/10) - **Custom Image Detection:** 6.7/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [DagsHub](https://www.g2.com/sellers/dagshub) - **HQ Location:** San Francisco, US - **LinkedIn® Page:** https://www.linkedin.com/company/dagshub (14 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Computer Software - **Company Size:** 50% Small-Business, 43% Mid-Market #### Pros & Cons **Pros:** - Data Management (12 reviews) - Model Management (12 reviews) - Collaboration (11 reviews) - Features (10 reviews) - Integrated Platform (10 reviews) **Cons:** - Limited Functionality (2 reviews) - Error Handling (1 reviews) - Expensive (1 reviews) - Limited Customization (1 reviews) - Limited Free Access (1 reviews) ### 9. [EBLearn](https://www.g2.com/products/eblearn/reviews) Eblearn is an object-oriented C++ library that implements various machine learning models, including energy-based learning, gradient-based learning for machine composed of multiple heterogeneous modules. **Average Rating:** 3.8/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Object Detection:** 10.0/10 (Category avg: 8.7/10) - **Ease of Use:** 9.2/10 (Category avg: 8.8/10) - **Custom Image Detection:** 9.2/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [EBLearn](https://www.g2.com/sellers/eblearn) - **HQ Location:** New York, NY - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market ### 10. [KBY-AI Face Recognition](https://www.g2.com/products/kby-ai-face-recognition/reviews) The Face Recognition SDK is designed to be efficient, using low memory and delivering high performance. This solution stands for face recognition, facial recognition, face liveness check, spoofing prevention, face matching, face comparison, face search engine, face identification on biometric authentication system. We offer multi-platform solutions including face recognition Android, face recognition iOS, face recognition Flutter, face recognition React-Native, face recognition docker, face recognition server(Linux/Windows) **Average Rating:** 5.0/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Object Detection:** 10.0/10 (Category avg: 8.7/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) - **Custom Image Detection:** 10.0/10 (Category avg: 8.4/10) - **Bounding Boxes:** 10.0/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [KBY-AI](https://www.g2.com/sellers/kby-ai) - **Year Founded:** 2020 - **HQ Location:** Essex, GB - **LinkedIn® Page:** https://www.linkedin.com/company/kby-ai-identity-verification-sdk (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Small-Business ### 11. [MobileEngine](https://www.g2.com/products/mobileengine/reviews) MobileEngine makes it easy for you to add image recognition to your app. You provide a reference database of images (e.g. artwork, consumer packaged goods, book covers, catalog pages, etc.) and when your users photograph that object, MobileEngine finds your matching reference image. **Average Rating:** 4.5/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Object Detection:** 6.7/10 (Category avg: 8.7/10) - **Ease of Use:** 9.2/10 (Category avg: 8.8/10) - **Custom Image Detection:** 8.3/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [TinEye](https://www.g2.com/sellers/tineye) - **HQ Location:** Toronto, CA - **Twitter:** @TinEye (7,652 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1455004/ (15 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 50% Mid-Market, 50% Small-Business ### 12. [muse.ai](https://www.g2.com/products/muse-ai/reviews) muse.ai is a video search platform that enables anyone to quickly find particular moments in large amounts videos. It is also a complete video storage and streaming platform that allows users to embed the most advanced video search in any website. **Average Rating:** 4.9/5.0 **Total Reviews:** 15 **User Satisfaction Scores:** - **Ease of Use:** 9.2/10 (Category avg: 8.8/10) **Seller Details:** - **Seller:** [muse.ai](https://www.g2.com/sellers/muse-ai) - **HQ Location:** San Ramon, US - **Twitter:** @video_ai (1,031 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/33434227/ (2 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 87% Small-Business ### 13. [Partium](https://www.g2.com/products/partium/reviews) Partium’s story began in 2020 with the idea of creating a lightning-fast, instant, and reliable search experience for everyone looking for spare parts. We reduced the need for technicians and users of parts catalogs and web shops to spend endless time searching for the right part. Instead, we help users to find the right spare part in seconds. Today, Partium handles millions of spare part searches every month and helps countless technicians find the right part to get the job done. The power of the Partium search is being used in spare part web shops, part catalogs, and spare part portals across the world. Our customers introduce Partium into their digital Aftersales environments to provide the best-in-class part-search experience to their users and give them a fast and convenient process to search, confirm and order spare parts from them. Caterpillar, Parker, Liebherr, Deutsche Bahn, New Holland, The Home Depot, ENGEL, and many other companies use Partium to provide not just a great search for their customers but a search that converts at higher rates because of relevancy, accuracy, and ease-of-use. We help their customers to find the right parts faster – and help them to enhance their online experience, increase conversion rates and generate profitable growth for their online aftersales business. With offices in the US, Canada, and Europe, we are a global company committed to changing the way Aftersales is done. **Average Rating:** 3.3/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Object Detection:** 10.0/10 (Category avg: 8.7/10) - **Ease of Use:** 6.7/10 (Category avg: 8.8/10) - **Custom Image Detection:** 10.0/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [Partium](https://www.g2.com/sellers/partium) - **Year Founded:** 2020 - **HQ Location:** Philadelphia, US - **Twitter:** @partiumio (2,105 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/partium-io/ (49 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market, 33% Small-Business #### Pros & Cons **Pros:** - AI Technology (1 reviews) - Efficiency (1 reviews) - User Interface (1 reviews) **Cons:** - Limited Search Features (1 reviews) ### 14. [Plainsight](https://www.g2.com/products/plainsight/reviews) Plainsight is the leader in proven vision AI. Providing the unique combination of AI strategy, a vision AI platform, and deep learning expertise, Plainsight develops, implements, and oversees transformative computer vision solutions for enterprises. Through the widest breadth of managed services and a vision AI platform for centralized processes and standardized pipelines, Plainsight makes computer vision repeatable and accountable across all enterprise vision AI initiatives. Plainsight solves problems where others have failed and empowers businesses across industries to realize the full potential of their visual data with the lowest barriers to production, fastest value generation, and monitoring for long-term success. For more information, visit https://plainsight.ai. **Average Rating:** 4.5/5.0 **Total Reviews:** 5 **User Satisfaction Scores:** - **Object Detection:** 8.3/10 (Category avg: 8.7/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) - **Custom Image Detection:** 6.7/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [Plainsight](https://www.g2.com/sellers/plainsight) - **Year Founded:** 2024 - **HQ Location:** Greater Seattle Area, US - **Twitter:** @PlainsightAI (1,466 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/plainsightai/ (22 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 80% Small-Business, 20% Mid-Market #### Pros & Cons **Pros:** - AI Capabilities (1 reviews) - AI Integration (1 reviews) - AI Modeling (1 reviews) - AI Technology (1 reviews) - Innovation (1 reviews) **Cons:** - Required Expertise (1 reviews) - Required Knowledge (1 reviews) ### 15. [SentiVeillance Cluster](https://www.g2.com/products/neurotechnology-sentiveillance-cluster/reviews) SentiVeillance Cluster Persons or vehicles recognition and tracking for video management systems (VMS) SentiVeillance Cluster is a ready-to-use software for easy integration of biometric face identification, vehicle and pedestrian classification and tracking, as well as automatic license plate recognition into operating video management systems (VMS). The software analyzes live video streams, which are served by a VMS from surveillance cameras. **Average Rating:** 4.3/5.0 **Total Reviews:** 5 **User Satisfaction Scores:** - **Ease of Use:** 9.3/10 (Category avg: 8.8/10) **Seller Details:** - **Seller:** [NeuroTechnology](https://www.g2.com/sellers/neurotechnology) - **Year Founded:** 1990 - **HQ Location:** Vilnius, LT - **Twitter:** @StockGeist (272 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/neurotechnology/ (89 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 60% Small-Business, 20% Mid-Market #### Pros & Cons **Pros:** - Tracking (2 reviews) - AI Technology (1 reviews) - Facial Recognition (1 reviews) - Helpful (1 reviews) - Monitoring (1 reviews) **Cons:** - Difficult Training (1 reviews) - Expensive (1 reviews) - Inefficient Resource Management (1 reviews) - Limited Functionality (1 reviews) - Limited Storage (1 reviews) ### 16. [Ultralytics](https://www.g2.com/products/ultralytics/reviews) Ultralytics is a prominent player in the field of vision AI, specializing in advanced computer vision solutions through its innovative YOLO (You Only Look Once) models. Designed to assist users in various industries, Ultralytics' technology enables real-time object detection and image analysis, making it an essential tool for businesses looking to leverage artificial intelligence for enhanced operational efficiency and decision-making. Targeted at a diverse audience that includes professionals in manufacturing, healthcare, transportation, agriculture, and retail, Ultralytics' offerings cater to organizations seeking to implement AI-driven solutions. The versatility of the YOLO models allows users to address a wide range of use cases, from automating quality control in manufacturing to improving patient outcomes in healthcare settings. By providing accessible and efficient AI tools, Ultralytics empowers businesses to harness the power of computer vision, ultimately driving innovation and growth. Key features of Ultralytics' technology include its remarkable speed and accuracy in image processing, which allows for the analysis of 1.6 billion images daily. This capability is complemented by the ability to train 5 million models per day, ensuring that users have access to the most up-to-date and effective AI tools. The YOLO models are designed to be user-friendly, enabling users with varying levels of technical expertise to implement and benefit from the technology without extensive training or resources. The unique selling points of Ultralytics lie in its commitment to AI accessibility and efficiency. By providing open-source solutions with extensive community support, the company fosters collaboration and innovation within the AI space. The impressive track record of over 110,000 GitHub stars and more than 100 million downloads highlights the widespread adoption and trust in Ultralytics' models. As industries continue to evolve and embrace digital transformation, Ultralytics remains at the forefront, offering cutting-edge solutions that meet the demands of a rapidly changing technological landscape. **Average Rating:** 5.0/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Object Detection:** 10.0/10 (Category avg: 8.7/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) - **Custom Image Detection:** 9.2/10 (Category avg: 8.4/10) - **Bounding Boxes:** 9.2/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [Ultralytics](https://www.g2.com/sellers/ultralytics) - **Company Website:** https://ultralytics.com - **Year Founded:** 2022 - **HQ Location:** 5001 Judicial Way Frederick, MD 21703, USA - **Twitter:** @ultralytics (8,197 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/ultralytics (37 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market #### Pros & Cons **Pros:** - Deployment Ease (2 reviews) - Ease of Use (2 reviews) - Efficiency (2 reviews) - AI Technology (1 reviews) - Automation (1 reviews) **Cons:** - Poor Documentation (2 reviews) - AI Limitations (1 reviews) - Confusing Documentation (1 reviews) - Deployment Issues (1 reviews) - Insufficient Learning Resources (1 reviews) ### 17. [VizSeek Visual Search](https://www.g2.com/products/vizseek-visual-search/reviews) The VizSeek visual search engine lets you find products, parts, and drawings in your database using a photo or even a hand-sketch. **Average Rating:** 4.5/5.0 **Total Reviews:** 2 **Seller Details:** - **Seller:** [Imaginestics](https://www.g2.com/sellers/imaginestics) - **HQ Location:** N/A - **Twitter:** @VizSeek (50 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 50% Mid-Market, 50% Small-Business ### 18. [VLFeat](https://www.g2.com/products/vlfeat/reviews) VLFeat is an open source library that implements popular computer vision algorithms specializing in image understanding and local features extraction and matching, it include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. **Average Rating:** 4.0/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Object Detection:** 6.7/10 (Category avg: 8.7/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) - **Custom Image Detection:** 8.3/10 (Category avg: 8.4/10) - **Bounding Boxes:** 6.7/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [VLFeat](https://www.g2.com/sellers/vlfeat) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market ### 19. [ANPR / ALPR - Number Plate Reading](https://www.g2.com/products/anpr-alpr-number-plate-reading/reviews) Extremely accurate and fast AI license plate recognition software that uses artificial intelligence methods specifically trained for this task. The software detects all license plates captured in an image, i.e. a photo or video file, and recognizes their content, including special characters and states of registration. It supports single-line and multi-line number plates, including ADR plates with dangerous goods codes. Each latest version of ANPR is always extended to support new types of licence plates newly introduced on the market. Advantages of this technology: accurate location of license plates from a wide range of views, error-free reading even from low quality data, state/country recognition, prediction of the "unreadable" flag, prediction of the "obstructed" flag, including ADR plates reading. Typical applications: e-tolling, law enforcement, parking and entrance solutions, parking zones systems, traffic safety and surveillance systems, police and governmental applications, traffic infrastructure planning systems, smart cities and others. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **User Satisfaction Scores:** - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Seller Details:** - **Seller:** [Eyedea Recognition](https://www.g2.com/sellers/eyedea-recognition) - **Year Founded:** 2006 - **HQ Location:** Praha 2, CZ - **LinkedIn® Page:** https://www.linkedin.com/company/1281906/ (8 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Small-Business #### Pros & Cons **Pros:** - Accuracy (1 reviews) - Object Recognition (1 reviews) **Cons:** - Accuracy Issues (1 reviews) - Inaccurate Recognition (1 reviews) ### 20. [brighter AI](https://www.g2.com/products/brighter-ai/reviews) Protect identities. Preserve data quality. Innovate faster. brighter AI provides the world’s most advanced image and video anonymization software. We help organizations turn personal data into compliant, usable assets for analytics and machine learning. Our deep learning solutions ensure full compliance with GDPR, CCPA, and APPI by protecting identities in public spaces—all without compromising the data quality needed for video analytics. Privacy and performance, combined. **Average Rating:** 4.5/5.0 **Total Reviews:** 23 **User Satisfaction Scores:** - **Object Detection:** 10.0/10 (Category avg: 8.7/10) - **Ease of Use:** 8.9/10 (Category avg: 8.8/10) - **Custom Image Detection:** 8.3/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [BrighterAi](https://www.g2.com/sellers/brighterai) - **Year Founded:** 2017 - **HQ Location:** Berlin, Germany - **Twitter:** @brighterAI (636 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/18144227 (30 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Information Technology and Services - **Company Size:** 48% Small-Business, 26% Mid-Market #### Pros & Cons **Pros:** - AI Technology (1 reviews) - Data Privacy (1 reviews) - Ease of Setup (1 reviews) - Quality Control (1 reviews) **Cons:** - Complexity (1 reviews) - Lack of Guidance (1 reviews) - Not User-Friendly (1 reviews) ### 21. [CloudSight API](https://www.g2.com/products/cloudsight-api/reviews) Cloudsight is an image recognition API providing true understanding for your digital media. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **User Satisfaction Scores:** - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Seller Details:** - **Seller:** [CloudSight](https://www.g2.com/sellers/cloudsight) - **Year Founded:** 2012 - **HQ Location:** Los Angeles, US - **Twitter:** @CloudSightAPI (222 Twitter followers) - **LinkedIn® Page:** http://www.linkedin.com/company/cloudsight-inc (11 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market ### 22. [CompreFace](https://www.g2.com/products/compreface/reviews) CompreFace is a free face recognition service from Exadel that can be easily integrated into any system using simple REST API. CompreFace starts quickly with one docker command and could be used by any developer without prior machine learning skills. We use one of the most popular face recognition methods based on deep neural networks, and provide a convenient API for Face Collection training and face recognition. We also provide a convenient roles system with which you can easily control who has access to the Face Collection. Every user can create several Face Collections trained on different subsets of people. The benefits of CompreFace are: 1. Opensource code and fully on-premise (security of your data) 2. Fast start with one docker command 3. Can be set up and used without machine learning knowledge 4. CompreFace uses one of the most popular face recognition methods with high accuracy face-recognizing. The system shows sufficient accuracy even if only one example for each face is used. 5. UI panel with roles for access control **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **User Satisfaction Scores:** - **Object Detection:** 8.3/10 (Category avg: 8.7/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) - **Custom Image Detection:** 10.0/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [Exadel inc.](https://www.g2.com/sellers/exadel-inc) - **Year Founded:** 1998 - **HQ Location:** Walnut Creek, California, United States - **LinkedIn® Page:** https://www.linkedin.com/company/exadel (1,808 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Small-Business ### 23. [CoreViz Lab](https://www.g2.com/products/coreviz-lab/reviews) Enables teams, organizations and governments to search through and analyze large image and video datasets with Visual AI. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **User Satisfaction Scores:** - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Seller Details:** - **Seller:** [CoreViz](https://www.g2.com/sellers/coreviz) - **Year Founded:** 2024 - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/105614537 (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Small-Business #### Pros & Cons **Pros:** - Accuracy (1 reviews) - AI Technology (1 reviews) - Features (1 reviews) **Cons:** - Expensive (1 reviews) ### 24. [DeepSight](https://www.g2.com/products/deepsight/reviews) We are committed to empowering smart manufacturing with leading AI technology, machine vision and automation capabilities, solving challenging industrial quality inspection problems, and providing support for the intelligent and digital transformation and upgrading of the manufacturing industry. **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **User Satisfaction Scores:** - **Object Detection:** 8.3/10 (Category avg: 8.7/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) - **Custom Image Detection:** 10.0/10 (Category avg: 8.4/10) - **Bounding Boxes:** 8.3/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [DeepSight](https://www.g2.com/sellers/deepsight) - **Year Founded:** 2017 - **HQ Location:** shanghai, CN - **LinkedIn® Page:** http://www.linkedin.com/company/deepsightinc (11 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market ### 25. [EasyPicky](https://www.g2.com/products/easypicky/reviews) EasyPicky has developed an instant image recognition technology by video that accelerates, facilitates and enhances store planogram checks from any embedded system without internet connection. Stop Snapshot switch to instant video ! **Average Rating:** 4.0/5.0 **Total Reviews:** 1 **User Satisfaction Scores:** - **Object Detection:** 6.7/10 (Category avg: 8.7/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) - **Custom Image Detection:** 5.0/10 (Category avg: 8.4/10) - **Bounding Boxes:** 6.7/10 (Category avg: 8.3/10) **Seller Details:** - **Seller:** [EasyPicky](https://www.g2.com/sellers/easypicky) - **Year Founded:** 2017 - **HQ Location:** Montpellier, FR - **LinkedIn® Page:** https://www.linkedin.com/company/easypicky (35 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Small-Business ## Parent Category [Deep Learning Software](https://www.g2.com/categories/deep-learning) ## Related Categories - [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) - [MLOps Platforms](https://www.g2.com/categories/mlops-platforms) - [Data Labeling Software](https://www.g2.com/categories/data-labeling) --- ## Buyer Guide ### What You Should Know About Image Recognition Software ### What is About Image Recognition Software? Image recognition software, also known as computer vision software, gives users the ability to input images and receive data back in the form of a label. This process, done through [machine learning (ML)](https://www.g2.com/categories/machine-learning), enables end users to gain an understanding of images which they might not be able to do with their naked eye. Since videos are fundamentally composed of a series of images, image recognition software can also be used to analyze video feeds. The possible uses for this technology are broad and varied. For example, health care professionals can use it to assess if a tumor is malignant or benign. In addition, automotive companies can use image recognition software to further the development of self-driving cars, as image recognition allows the car to “see" by providing labels for what the camera on the car captures. Another popular use case is image search, where users can take a picture of an object and receive search results as a result. Retailers can use this as an alternative to text search. Finally, facial recognition software utilizes image recognition: The algorithm takes a face as an input and produces information as an output. Key Benefits of Image Recognition Software - Empower users to gain understanding of images through labeling - Give end users an opportunity to make meaning out of image data - Create smarter applications with computer vision capabilities ### Why Use Image Recognition Software? Business applications with image recognition functionality provide end users with the tools they need to succeed. For example, if a retail company wants to build a smarter search function or a medical institution seeks to supercharge their disease detecting abilities, image recognition algorithms or software can come to the rescue. **Engaged users —** Incorporating image recognition into applications results in higher productivity for end users, since they can make meaning of the images within the application they use. **Better applications —** Users spend more time using applications when they are enhanced with image recognition capabilities, leading to enhanced productivity and better deployment of the applications. **Cut costs —** Building out a robust image recognition function can be a costly endeavor and could take a significant amount of time. While this software might require additional development work in the long run, it helps businesses save money and develop insights. ### Who Uses Image Recognition Software? Images are just pixels. As a result, with the advancement of AI techniques like deep learning, we are able to grasp the meaning behind these pixels through advanced computer vision techniques. Thanks to the aforementioned technology, image analysis and image-based insights are open to many. However, there are still specific positions that utilize this software more than others. **Software developers —** Developers that want to create the next generation of products and services can use image recognition software to build computer vision capabilities into their applications, including object recognition, facial recognition, image search, and more . **Marketers —** Image recognition solutions can provide insights into images for marketers looking to understand the impact and reach of their brand. For example, a marketing professional can use the technology to detect and track their logo across social media platforms. **Health care professionals —** As the health care industry becomes more digital and image recognition techniques gain traction in the industry, it will be easier for doctors to quickly identify and diagnose maladies to support quick, accurate clinical decision-making. **Retailers—** Image search is the new text search. As a result, smart retailers are building applications with search powered by image recognition to give end users a more powerful search experience. ### Kinds of Image Recognition Software By using image recognition software, users can better understand images—unlocking the meaning contained within them. As a result, they can make important business decisions, create better applications, and improve functionality of existing tools. **Image restoration —** Uses machine learning to improve the quality of images through techniques such as improving focus and reducing blur. **Object recognition —** Allows for the recognition of objects or object classes for either pre-specified or learned objects. **Scene reconstruction —** Given images of a scene, or a video, scene reconstruction computes a 3D model of a scene. **Motion analysis —** Processes video, or image sequences, to track objects or individuals. ### Image Recognition Software Features Image recognition software tends to have a wide range of features, including image labeling, text detection, and more. These features help end users understand their images better and unlock insights. The following features are found in many image recognition software offerings. **Image labeling —** Image recognition software allows users to identify objects in an image and can help provide labels for these detected objects. More robust solutions allow users to create custom labels, letting them tailor the labels to their particular industry or use case. By training the machine learning model on data, the software can accurately detect objects based on these inputted labels. **Text detection —** Many image recognition tools recognize text and can translate it into a machine readable format. **Facial recognition —** Takes an image of a face and provides the identity of the individual as an output. **Inappropriate content detection —** Allows images and videos to be moderated by identifying potentially inappropriate or unsafe content. Other features of image recognition software include: [APIs & SDKs](https://www.g2.com/categories/image-recognition/f/apis-sdks), [Machine Learning Libraries & Frameworks](https://www.g2.com/categories/image-recognition/f/machine-learning-libraries-frameworks), [On Device & Edge](https://www.g2.com/categories/image-recognition/f/on-device-edge), [Operations](https://www.g2.com/categories/image-recognition/f/operations), [Platform](https://www.g2.com/categories/image-recognition/f/platform), [Retail](https://www.g2.com/categories/image-recognition/f/retail), and [Security](https://www.g2.com/categories/image-recognition/f/security). ### Trends Related to Image Recognition Software With image recognition capabilities, the user has the ability to understand the images and glean insights from them. There are a few key trends driving this. **Machine learning —** Without machine learning, or the ability for computers to discover patterns in data and as a result to come up with actionable insights, image recognition would be naught. The improvement and advancement of machine learning directly correlates to the success of image recognition. **Image search —** As previously mentioned, text is not the only way users can query data and search for what they are looking for. With image search, powered by image recognition, users can snap a picture of an object, and receive actionable insights, product recommendations, and more. ### Potential Issues with Image Recognition Software **Plan for adoption —** At the start, image recognition tools may not seem valuable to all employees—end users might struggle to adopt the solutions. Therefore, it’s important for companies to have a plan in place to encourage and promote user adoption. **Time to market —** As with any software implementation, it’s important to think about how long it will take to implement. It’s important to consider related software that a company might need, such as [data integration software](https://www.g2.com/categories/data-integration). **Data security —** Don’t make data security an afterthought. Companies must consider security options to ensure the correct users see the correct data. They must also have security options that allow administrators to assign verified users different levels of access to the platform. **Image manipulation —** The rise of advanced computer vision algorithms has seen an increased risk of advanced image manipulation such as deepfakes. Using techniques such as Generative Adversarial Networks, bad actors can create lifelike videos and images, that are almost indistinguishable from the real thing. ### Software and Services Related to Image Recognition Software The following solutions can be used in conjunction with the products in this category to make the most comprehensive reports possible. [**Application development software**](https://www.g2.com/categories/application-development) **—** Image recognition tools can be used alongside application development tools to create computer vision-infused solutions. Developers typically use some sort of [application development software](https://www.g2.com/categories/application-development), such as [mobile development software](https://www.g2.com/categories/mobile-development) or [rapid application development (RAD) software](https://www.g2.com/categories/rapid-application-development-rad) to incorporate these image recognition capabilities. [**Storage management software**](https://www.g2.com/categories/storage-management) **—** There are a plethora of solutions for storing, organizing, and sharing large amounts of data to be accessed and analyzed later by image recognition tools. This includes everything from [object storage software](https://www.g2.com/categories/object-storage) to industry-specific solutions like [vendor-neutral archives (VNA) software](https://www.g2.com/categories/vendor-neutral-archives-vna) for health care. [**E-commerce software**](https://www.g2.com/categories/e-commerce) **—** [E-commerce platforms](https://www.g2.com/categories/e-commerce-platforms) and businesses utilize image recognition to improve search capabilities and connect different products to one another based on how they look. For example, [product information management (PIM) tools](https://www.g2.com/categories/product-information-management-pim) are a set of processes and tools that centralize and manage an e-commerce business’s product information, can be leveraged to power computer vision algorithms. An online business looking to offer personalized content or search results to the consumer can use a combination of [e-commerce personalization software](https://www.g2.com/categories/e-commerce-personalization) with image recognition to provide that personalized touch. [**Health care software**](https://www.g2.com/categories/health-care) **—** Medical professionals can benefit from image recognition technology, leveraging it to make meaning from medical images. For example, [radiology software](https://www.g2.com/categories/radiology), which is used for managing medical imaging activities, can greatly benefit from image recognition software since it provides physicians with more powerful tools for diagnosis. In addition, [clinical documentation software](https://www.g2.com/categories/clinical-documentation) might be related, if some of the information and data shared and stored between medical professionals is image-related. [**Optical character recognition (OCR) software**](https://www.g2.com/categories/ocr) **—** OCR software, also called document capture software, is designed to scan various types of documents, process the content within those documents, and extract actionable data.