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Recent results of deep convolutional networks in visual recognitionchallenges open the path to a whole new set of disruptive user experiences suchas visual search or recommendation. The list of companies offering this type ofservice is growing everyday but the adoption rate and the relevancy of resultsmay vary a lot. We believe that the availability of large and diverse datasetsis a necessary condition to improve the relevancy of such recommendationsystems and facilitate their adoption. For that purpose, we wish to share withthe community this dataset of more than 12M images of the 7M products of ouronline store classified into 5K categories. This original dataset is introducedin this article and several features are described. We also present someaspects of the winning solutions of our image classification challenge that wasorganized on the Kaggle platform around this set of images.

Large e-retailer image dataset for visual search and product classification