Based on our record, GitHub seems to be a lot more popular than Amazon Rekognition. While we know about 2083 links to GitHub, we've tracked only 33 mentions of Amazon Rekognition. 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 / 3 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 / 12 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: 12 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 $0.10 per minute of... Source: over 1 year ago
I know sometime you might have wondered how websites such as GitHub and Dev do to make their image and description appear when you share their links through social medias on even some messaging applications as illustrated here in WhatsApp. - Source: dev.to / about 22 hours ago
GitHub: Explore repositories and projects to see how others are using TypeScript and Angular for Gantt chart development. - Source: dev.to / about 23 hours ago
If you don't already have a GitHub account, go to GitHub's website and sign up for free. Once you have your account, you're ready to create a new repository. - Source: dev.to / 2 days ago
Another standout talk for me was from GitHub, which discussed challenges with its design system, Primer. They went into detail about how organisational changes have altered the course of its development and how they've had to adjust to the needs of the business over time to adapt and grow. As an engineering lead, I really resonated with this talk. - Source: dev.to / 4 days ago
I have a script that looks at your github org/team and generates/updates users on-demand then lets you connect. The script is pretty straightforward, see AuthorizedKeysCommand and https://github.com/{$user}.keys. - Source: Hacker News / 4 days ago
Kairos - Facial recognition & mood detection API
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Clarifai - The World's AI
Visual Studio Code - Build and debug modern web and cloud applications, by Microsoft