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README.md
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@@ -19,7 +19,7 @@ Full credits go to [François Chollet](https://twitter.com/fchollet).
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This repository contains the model from [this notebook on segmenting pets using U-net-like architecture](https://keras.io/examples/vision/oxford_pets_image_segmentation/). We've changed the inference part to enable segmentation widget on the Hub. (see ```pipeline.py```)
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## Background Information
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Image classification task tells us about a class assigned to an image, and object detection task creates a boundary box on an object in an image. But what if we want to know about the shape of the image? Segmentation models helps us segment images and reveal their shapes. It has many variants, including, panoptic segmentation, instance segmentation and semantic segmentation.This post is on hosting your Keras semantic segmentation models on Hub.
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Semantic segmentation models classify pixels, meaning, they assign a class (can be cat or dog) to each pixel. The output of a model looks like following.
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This repository contains the model from [this notebook on segmenting pets using U-net-like architecture](https://keras.io/examples/vision/oxford_pets_image_segmentation/). We've changed the inference part to enable segmentation widget on the Hub. (see ```pipeline.py```)
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## Background Information
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Image classification task tells us about a class assigned to an image, and object detection task creates a boundary box on an object in an image. But what if we want to know about the shape of the image? Segmentation models helps us segment images and reveal their shapes. It has many variants, including, panoptic segmentation, instance segmentation and semantic segmentation.This post is on hosting your Keras semantic segmentation models on Hub.
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Semantic segmentation models classify pixels, meaning, they assign a class (can be cat or dog) to each pixel. The output of a model looks like following.
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