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What are some user-friendly and reliable visual AI systems that allow businesses and individuals to build and deploy their own machine learning models for image and video processing?

Google Cloud Vision API: Allows users to analyze images, identify objects, and detect faces with auto-tagging and labeling features.

Clarifai: Offers custom image recognition with pre-trained models for various applications, like general, food, apparel, and NSFW detection.

Amazon Rekognition: Provides image and video analysis, object and scene detection, and facial recognition capabilities for businesses.

OpenCV: An open-source computer vision library for real-time image and video processing, popular for its versatility and extensive functions.

TensorFlow: A popular open-source machine learning framework developed by Google, offering a robust platform for building and deploying custom visual AI models.

PyTorch: An open-source machine learning library developed by Facebook, providing a user-friendly interface and flexibility for visual AI projects.

IBM Watson Visual Recognition: Allows users to build custom models for image recognition and analysis using pre-trained models and a low-code interface.

Caffe: An open-source deep learning framework, known for its expressiveness, extensibility, and speed, suitable for visual AI projects.

Microsoft Azure Computer Vision: Provides image and video analysis, object detection, and OCR capabilities through its cloud-based platform.

YOLO (You Only Look Once): A popular real-time object detection system, efficient at identifying and locating objects within images, and available as an open-source project.

Create photorealistic images of your products in any environment without expensive photo shoots! (Get started for free)