blamm/retail_visual_rag_pipeline

A Visual RAG Pipeline for Few-Shot Fine-Grained Product Classification

Paper

Accepted at The 12th Workshop on Fine-Grained Visual Categorization (FGVC12) at IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025.

Overview

The Retail Visual RAG Pipeline Dataset is a subset of the Retail-786k (Retail-786k) image dataset, supplemented with additional textual data per image.

Data

• Image Data:

  • The images are cropped from scanned advertisement leaflets.
  • The image data is divided into train and test splits.

• Product and Promotion Data:

  Product Data:

  • Product data contains the targets: brand, product category, GTINs, product weight, and different sorts.
  • If a promotion covers a variety of different types/flavors of the product, the GTIN of each type is recorded.

  Promotion Data:

  • Promotion data contains the targets: price, regular price, and relative discount or absolute discount.

Usage

You can load and use the dataset with the Hugging Face datasets library.

import pandas as pd
from datasets import load_dataset

image_dataset = load_dataset("blamm/retail_visual_rag_pipeline", trust_remote_code=True)

product_promotion_data = load_dataset("blamm/retail_visual_rag_pipeline", data_files={'train':'train.parquet', 'test':'test.parquet'})
df_test = product_promotion_data['test'].to_pandas()

filename = '1166.jpg'
example_data = df_test.loc[df_test.filename == filename]
# Show product and promotion data
print(example_data)

image = image_dataset['test']['image'][example_data.index[0]]
# Show image
image.show()

The Dataset for Visual RAG pipeline is used to evaluate the introduced Visual RAG pipeline. See the paper for explaination and evaluation of the Visual RAG pipeline.

License

This dataset is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International