Amazon Rekognition might be a bit more popular than AWS CodePipeline. We know about 33 links to it since March 2021 and only 28 links to AWS CodePipeline. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / 2 months ago
I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 11 months ago
For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 11 months ago
Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / about 1 year ago
Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year ago
AWS CodePipeline is a fully managed CI/CD service offered by AWS. It automates the build, test, and deployment features of your release process. It is designed to provide a seamless integration experience with other AWS services and popular third-party tools. AWS Code Pipeline ensures rapid and reliable application and infrastructure updates, empowering developers to iterate swiftly and maintain high software... - Source: dev.to / about 2 months ago
AWS CodePipeline for streamlined continuous integration and delivery, ensuring security checks are automated at every stage. - Source: dev.to / 2 months ago
Build – Used for all CodeCommit repositories and CodePipelines that are deployed within the landing zone. - Source: dev.to / 5 months ago
Familiarity with CI/CD pipelines such as AWS CodePipeline and IaC (Infrastructure as a Service) such as AWS CloudFormation or Terraform is crucial for streamlining the software development and deployment processes. - Source: dev.to / 12 months ago
AWS CodePipeline: fully managed continuous delivery service that helps you automate your release pipelines for fast and reliable application and infrastructure updates. - Source: dev.to / about 1 year ago
Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.
Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development
Clarifai - The World's AI
CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.
Kairos - Facial recognition & mood detection API
Travis CI - Focus on writing code. Let Travis CI take care of running your tests and deploying your apps.