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README.md
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---
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library_name: keras-hub
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---
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## Model Overview
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DeepLabv3+ model is developed by Google for semantic segmentation. This guide demonstrates how to finetune and use DeepLabv3+ model for image semantic segmentaion with KerasCV. Its architecture that combines atrous convolutions, contextual information aggregation, and powerful backbones to achieve accurate and detailed semantic segmentation. The DeepLabv3+ model has been shown to achieve state-of-the-art results on a variety of image segmentation benchmarks. This model is supported in both KerasCV and KerasHub. KerasCV will no longer be actively developed, so please try to use KerasHub.
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segmenter.preprocessor.image_size = (96, 96)
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segmenter.fit(images, labels, epochs=3)
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segmenter.predict(images) # Trained 2 class segmentation.
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```
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---
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library_name: keras-hub
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license: apache-2.0
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tags:
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- image-segmentation
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---
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## Model Overview
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DeepLabv3+ model is developed by Google for semantic segmentation. This guide demonstrates how to finetune and use DeepLabv3+ model for image semantic segmentaion with KerasCV. Its architecture that combines atrous convolutions, contextual information aggregation, and powerful backbones to achieve accurate and detailed semantic segmentation. The DeepLabv3+ model has been shown to achieve state-of-the-art results on a variety of image segmentation benchmarks. This model is supported in both KerasCV and KerasHub. KerasCV will no longer be actively developed, so please try to use KerasHub.
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segmenter.preprocessor.image_size = (96, 96)
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segmenter.fit(images, labels, epochs=3)
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segmenter.predict(images) # Trained 2 class segmentation.
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```
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