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DeepLab

Rating:

4.7 / 5.0

Tags

Computer Vision, Image Segmentation, Semantic Segmentation, Deep Learning, Algorithm, Open Source, Google

Categories:
Computer visionMachine learning and neural networks
Creator Google
Date 2014-01-01
Platforms Frameworks
Status Active (Development)
Website github.com
Price Model Free (model)
Sections:
DL FrameworksImage AnalysisImage Segmentation

Pricing Details

Free (open source). Costs may apply when using third-party services or cloud resources to run the model.

Features

Semantic segmentation, pixel-level classification, atrous convolution, multiple versions, open-source.

Integrations

Used as a model or library in Python and other language projects using frameworks (TensorFlow, PyTorch).

Preview

DeepLab is a family of deep learning models developed by Google, designed for semantic image segmentation. Semantic segmentation involves assigning a class label (e.g., "person", "car", "sky") to every pixel in an image. DeepLab models use convolutional neural networks with atrous convolution to effectively capture image context without losing resolution. Various versions of DeepLab (v1, v2, v3, v3+) improve accuracy and efficiency. DeepLab is open-source and widely used in academic research and industrial applications requiring detailed, pixel-level understanding of image content.