Wake Vision is a new, high-quality dataset for person detection, seamlessly accessible with a single line of code via TensorFlow Datasets.

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TensorFlow

Wake Vision is a new large-scale dataset created to advance research and development in TinyML, which focuses on running machine learning models on low-power devices like microcontrollers. The dataset contains approximately 6 million images, nearly 100 times larger than the previous Visual Wake Words (VWW) dataset. Wake Vision offers high-quality labeled images, beneficial for under-parameterized models, and includes fine-grained benchmarks for real-world applications. The dataset is freely available under a permissive license, aiming to help researchers build better person detection models for ultra-low-power devices.

Introducing Wake Vision: A High-Quality, Large-Scale Dataset for TinyML Computer Vision Applications

Why Data Quality Matters for TinyML Models

Real-World Testing: Wake Vision's Fine-Grained Benchmarks

Wake Vision Leaderboard: Track and Submit New Top-Performing Models