fashion-mnist and fashion
The second project, `primaryobjects/fashion`, is a complementary tool that utilizes the dataset provided by the first project, `zalandoresearch/fashion-mnist`, to build and demonstrate machine learning models.
About fashion-mnist
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.
About fashion
primaryobjects/fashion
The Fashion-MNIST dataset and machine learning models.
This project helps fashion designers, e-commerce retailers, and clothing manufacturers automatically identify clothing items in images. It takes images of apparel (like shirts, pants, or shoes) and categorizes them into 10 different clothing types. E-commerce managers or anyone needing to sort large inventories of fashion images would find this useful.
Scores updated daily from GitHub, PyPI, and npm data. How scores work