PyImageSearch - Alternatives & Competitors

Ranked by Relevance

• 1
  OpenCV Open Source Computer Vision Library

  OpenCV is the world's largest open-source computer vision library, offering over 2500 optimized algorithms for real-time applications. It's free for commercial use and supports multiple platforms and programming languages.

  • Free
• 2
  AIOnlineCourse An Interactive Learning Platform for AI

  AIOnlineCourse offers interactive learning resources for artificial intelligence, including projects, tutorials, and quizzes. Dive into AI basics and start live coding today.

  • Free
• 3
  Dragoneye Computer vision for everyone

  Dragoneye offers a no-code platform for building custom computer vision models. Easily create AI models for image recognition with just a few clicks.

  • Usage Based
• 4
  EyePop.ai Your hassle-free AI vision partner built for innovators

  EyePop.ai is a platform that enables users to create and own custom AI-powered vision models without requiring machine learning expertise. It offers both pre-trained models and custom solutions starting at $99/month.

  • Freemium
  • From 99$
• 5
  GreenEyes.AI Computer Vision APIs and Products

  GreenEyes.AI provides enterprise-grade Computer Vision APIs and SaaS products, focusing on AI Object Search and Object Labeling. Their solutions are designed for scalability, security, and a low-carbon footprint.

  • Paid
• 6
  Tenyks Conversational Visual Search

  Tenyks offers a visual intelligence platform that transforms unstructured visual data into actionable intelligence. Leverage GenAI to make videos searchable and gain insights with human-level precision.

  • Usage Based
  • From 27$
• 7
  Supervisely All Computer Vision in One Platform

  Supervisely is a comprehensive computer vision platform to curate, label, and build production models for images, videos, 3D, medical imagery, and more.

  • Freemium
  • From 199$
• 8
  Albumentations Do more with less data

  Albumentations is a fast and flexible Python library for image augmentation, boosting the performance of deep convolutional neural networks. It's widely used in industry and research for various computer vision tasks.

  • Free