google-research/deeplab2
DeepLab2 is a Google TensorFlow library providing state-of-the-art models for dense pixel labeling tasks like semantic and panoptic segmentation.
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DeepLab2 provides a unified TensorFlow codebase for deep labeling, which refers to solving computer vision problems by assigning predicted values to each pixel in an image using deep neural networks. The library includes implementations of recent research models such as kMaX-DeepLab, ViP-DeepLab, and MOAT for tasks including semantic segmentation, instance segmentation, panoptic segmentation, depth estimation, and video panoptic segmentation.
Frequently asked
- What is google-research/deeplab2?
- DeepLab2 is a Google TensorFlow library providing state-of-the-art models for dense pixel labeling tasks like semantic and panoptic segmentation.
- Is deeplab2 open source?
- Yes — google-research/deeplab2 is open source, released under the Apache-2.0 license.
- What language is deeplab2 written in?
- google-research/deeplab2 is primarily written in Python.
- How popular is deeplab2?
- google-research/deeplab2 has 1k stars on GitHub.
- Where can I find deeplab2?
- google-research/deeplab2 is on GitHub at https://github.com/google-research/deeplab2.