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Automate the process to change image backgrounds using Amazon Bedrock and AWS Step Functions

AWS Machine Learning

Many customers, including those in creative advertising, media and entertainment, ecommerce, and fashion, often need to change the background in a large number of images. Typically, this involves manually editing each image with photo software. This can take a lot of effort, especially for large batches of images.

APIs 116
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Semantic segmentation data labeling and model training using Amazon SageMaker

AWS Machine Learning

In computer vision, semantic segmentation is the task of classifying every pixel in an image with a class from a known set of labels such that pixels with the same label share certain characteristics. It generates a segmentation mask of the input images. For example, the following images show a segmentation mask of the cat label.

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Image augmentation pipeline for Amazon Lookout for Vision

AWS Machine Learning

Amazon Lookout for Vision provides a machine learning (ML)-based anomaly detection service to identify normal images (i.e., images of objects without defects) vs anomalous images (i.e., images of objects with defects), types of anomalies (e.g., In Section 3, we present the image augmentation pipeline for normal images.

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Fine-tune your Amazon Titan Image Generator G1 model using Amazon Bedrock model customization

AWS Machine Learning

Amazon Titan lmage Generator G1 is a cutting-edge text-to-image model, available via Amazon Bedrock , that is able to understand prompts describing multiple objects in various contexts and captures these relevant details in the images it generates. It is available in US East (N.

APIs 84
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Build a vaccination verification solution using the Queries feature in Amazon Textract

AWS Machine Learning

The image is uploaded to an Amazon Simple Storage Service (Amazon S3) bucket. Amazon Textract analyzes the image and sends the answers of these queries back to the Lambda function. In the terminal, choose Upload Local Files on the File menu. Solution overview The following diagram illustrates the solution architecture.

Finance 97
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Implement smart document search index with Amazon Textract and Amazon OpenSearch

AWS Machine Learning

Documents in PDF, TIFF, JPEG or PNG format are put in an Amazon Simple Storage Service ( Amazon S3 ) bucket and subsequently indexed into OpenSearch using this Step Functions workflow. Because the TextractAsy nc task can produce multiple paginated output files, the TextractAsyncToJSON2 process combines them into one JSON file.

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Introducing one-step classification and entity recognition with Amazon Comprehend for intelligent document processing

AWS Machine Learning

Today, Amazon Comprehend supports classification for plain text documents, which requires you to preprocess documents in semi-structured formats (scanned, digital PDF or images such as PNG, JPG, TIFF) and then use the plain text output to run inference with your custom classification model.

APIs 71