zalandoresearch/fashion-mnist
A MNIST-like fashion product database. Benchmark :point_down:
Fashion-MNIST helps machine learning researchers and practitioners benchmark and develop algorithms for image classification. It provides a dataset of 60,000 training and 10,000 test examples of grayscale fashion product images (like t-shirts, dresses, sneakers) as input, with corresponding labels identifying the apparel type. This is ideal for those working on computer vision tasks who need a more challenging and modern dataset than the original MNIST handwritten digits.
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Use this if you are a machine learning researcher or practitioner developing and benchmarking image classification algorithms and need a standardized, more complex dataset of real-world items than basic handwritten digits.
Not ideal if you need to classify handwritten digits or if your image classification task involves highly complex, high-resolution, or multi-channel images beyond simple grayscale apparel.
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MIT
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Jun 13, 2022
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