SKU-110k Dataset

The SKU-110k dataset is a collection of densely packed retail shelf images, designed to support research in object detection tasks. Developed by Eran Goldman et al., the dataset contains over 110,000 unique store keeping unit (SKU) categories with densely packed objects, often looking similar or even identical, positioned in proximity.

Key Features

• SKU-110k contains images of store shelves from around the world, featuring densely packed objects that pose challenges for state-of-the-art object detectors.
• The dataset includes over 110,000 unique SKU categories, providing a diverse range of object appearances.
• Annotations include bounding boxes for objects and SKU category labels.

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("PrashantDixit0/SKU-110K")

# Access splits
train_data = dataset['train']

# Example: Load first image
from PIL import Image
import io

sample = train_data[0]
image = Image.open(BytesIO(base64.b64decode(sample["image"]["bytes"]))
image.show()

Applications

The SKU-110k dataset is widely used for training and evaluating deep learning models in object detection tasks, especially in densely packed scenes such as retail shelf displays. Its applications include:

• Retail inventory management and automation
• Product recognition in e-commerce platforms
• Planogram compliance verification
• Self-checkout systems in stores
• Robotic picking and sorting in warehouses