AlphaRotate: A Rotation Detection Benchmark using TensorFlow
Xue Yang, Yue Zhou, Junchi Yan
TL;DR
AlphaRotate is a comprehensive TensorFlow benchmark platform that offers a wide range of rotation detection models, emphasizing performance, robustness, and ease of use for researchers and practitioners.
Contribution
It provides the first unified benchmark with over 18 models for rotation detection in TensorFlow, including extensive testing and analysis tools.
Findings
Supports scalable rotation detection across datasets
Includes over 18 models with a unified API
Ensures high code quality and maintainability
Abstract
AlphaRotate is an open-source Tensorflow benchmark for performing scalable rotation detection on various datasets. It currently provides more than 18 popular rotation detection models under a single, well-documented API designed for use by both practitioners and researchers. AlphaRotate regards high performance, robustness, sustainability and scalability as the core concept of design, and all models are covered by unit testing, continuous integration, code coverage, maintainability checks, and visual monitoring and analysis. AlphaRotate can be installed from PyPI and is released under the Apache-2.0 License. Source code is available at https://github.com/yangxue0827/RotationDetection.
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Taxonomy
TopicsTime Series Analysis and Forecasting · Handwritten Text Recognition Techniques · Anomaly Detection Techniques and Applications