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Getting started with image embedding for web using MediaPipe Solutions

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The MediaPipe Image Embedder task lets you create a numeric representation of an image, which is useful in accomplishing various ML-based image tasks. This functionality is frequently used to compare the similarity of two images using mathematical comparison techniques such as Cosine Similarity. This task operates on image data with a machine learning (ML) model as static data or a continuous stream, and outputs a numeric representation of the image data as a list of high-dimensional feature vectors, also known as embedding vectors, in either floating-point or quantized form. Learn how to get started with the Image Embedder task for the web.

Resources:
View available image embedding models → https://goo.gle/48e0lWD
Try out the image embedding model options in MediaPipe Studio → https://goo.gle/48AS92L
Learn more about WebAssembly → https://goo.gle/3tdEa3n
View the complete gesture recognition code demo → https://goo.gle/48spQDi
MediaPipe Solutions → https://goo.gle/MediaPipe_Solutions

Watch more episodes on Getting Started with MediaPipe for Web → https://goo.gle/MediaPipeforWeb
Subscribe to Google for Developers → https://goo.gle/developers

#Google #mediapipe


Speaker: Jen Person
Products Mentioned: MediaPipe
Category
Project
Tags
Google, developers, pr_pr: Core ML/TensorFlow;
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