Amazon Textract might be a bit more popular than Amazon Rekognition. We know about 34 links to it since March 2021 and only 33 links to 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 / 28 days 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 / 9 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: 10 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 / 12 months 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
Amazon Textract has an Analyze Lending API for evaluating and categorizing the documents contained in mortgage loan application packages, as well as extracting the data they contain. The new API can assist in processing applications quicker and with minimal errors, therefore improving the end-customer experience and lowering operational costs. - Source: dev.to / 3 months ago
You could try something like https://aws.amazon.com/textract/ or https://cloud.google.com/vision/docs/handwriting. Both have support for modern handwriting. I don't know if it will work with a script written a century ago though. - Source: Hacker News / 3 months ago
Create a main.js file inside the look-for-github-profile-step project folder. Implement the code that parses the resume and plucks the GitHub profile URL. This step function is responsible for using Textract (an AI service from AWS) and passing state back to the state machine. - Source: dev.to / 7 months ago
The primary challenge in processing invoices is extracting the relevant data. This is where Amazon Textract can help. It is a service provided by Amazon Web Services (AWS) that uses advanced Machine Learning (ML) algorithms to automatically extract structured and unstructured data from scanned documents, images, and PDF files. It can detect typed and handwritten text in different types of documents including... - Source: dev.to / 8 months ago
First, we’ve decided to leave open-source solutions behind. We’ve used AWS Textract to parse PDF files. This way we don’t rely on the internal structure of the PDF to get text from it (or to get nothing - like in the case of the Uber example). Textract uses OCR and machine learning to get not only text but also spatial information from the document. - Source: dev.to / 8 months ago
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