Commercial

Grocery Shelves

A dataset of photos featuring grocery shelves, containing images of various product categories in supermarkets

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  • Data annotation The process of identifying objects in photos for training a system to recognize and interpret them
  • Computer Vision The ability to recognize and analyze images and videos
  • Retail Analytics The use of machine learning for analyzing data in the retail sector.
  • Object Detection Identifying and localizing objects in images
    5,000+
    photos

CASE DESCRIPTION

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The dataset includes images of grocery shelves taken in various supermarkets at different lighting conditions

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Each image is accompanied by an XML-annotation indicating the labeled types of product for each image in the dataset.

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Each image has an attribute of the product(boolean): facing, flipped, occluded.

Original image
Original image
Labeling of the image
Labeling of the image
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Application areas of the dataset

  • 01.

    Inventory Automation:

    Development of systems that can track the availability and quantity of products on shelves in real-time.
  • 02.

    Product Placement Optimization:

    Utilizing data to plan more effective product placement and arrangement in stores.
  • 03.

    Customer Behavior Analysis:

    Integration with data analysis systems to understand customer preferences and improve product assortment.
  • 04.

    Dynamic Pricing Strategies:

    Utilizing real-time data to implement dynamic pricing models based on product availability, demand, and competition.

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