Amazon Rekognition is a managed computer-vision service for analyzing images and videos, including object detection, facial analysis, text extraction, content moderation, and custom labels. Here are five strong alternatives to consider:

1. Google Cloud Vision provides image labeling, OCR, object and landmark detection, facial analysis, and content-related capabilities. It is particularly attractive for organizations already using Google Cloud and for applications that need strong image and document understanding. G2 currently identifies Google Cloud Vision API as one of the leading Rekognition alternatives.

2. Microsoft Azure Vision offers computer-vision APIs for image analysis, OCR, object detection, and related visual intelligence. It integrates naturally with Microsoft Azure services, making it a strong choice for enterprises already invested in Microsoft infrastructure, identity, and analytics.

3. IBM Maximo provides computer-vision capabilities for detecting defects, identifying objects, and analyzing images and video, with a strong focus on industrial and enterprise use cases. It is particularly suitable for manufacturing, quality control, and automated visual inspection where businesses need to integrate AI into existing operational workflows.

4. OpenCV is a powerful computer-vision library rather than a direct managed-cloud equivalent. It supports image processing, object detection, video analysis, and machine-learning workflows. It’s a good choice when you need maximum control, on-premises deployment, or want to avoid dependence on a cloud vendor.

5. Face++ specializes in facial detection, recognition, verification, and related analysis. It can be a compelling alternative when facial recognition is the primary requirement rather than broad image and video understanding.

Bottom line: Choose Google Cloud Vision for a general-purpose cloud replacement, Azure AI Vision for Microsoft environments, Clarifai for customization, OpenCV for open-source control, and Face++ for face-focused applications.