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--- |
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license: cc-by-nc-nd-4.0 |
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task_categories: |
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- visual-question-answering |
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size_categories: |
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- 1K<n<10K |
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--- |
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# A Visual RAG Pipeline for Few-Shot Fine-Grained Product Classification |
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## Paper |
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Accepted at *The 12th Workshop on Fine-Grained Visual Categorization* ([FGVC12](https://sites.google.com/view/fgvc12)) at *IEEE/CVF Conference on Computer Vision and Pattern Recognition* ([CVPR](https://cvpr.thecvf.com/)) 2025. |
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## Overview |
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The **Retail Visual RAG Pipeline Dataset** is a subset of the *Retail-786k* ([Retail-786k](https://www.retail-786k.org/)) image dataset, supplemented with additional textual data per image. |
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### Data |
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- **Image Data:** |
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- The images are cropped from scanned advertisement leaflets. |
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- The image data is divided into `train` and `test` splits. |
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- **Product and Promotion Data:** |
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Product Data: |
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- Product data contains the targets: brand, product category, GTINs, product weight, and different sorts. |
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- If a promotion covers a variety of different types/flavors of the product, the GTIN of each type is recorded. |
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Promotion Data: |
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- Promotion data contains the targets: price, regular price, and relative discount or absolute discount. |
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## Usage |
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You can load and use the dataset with the Hugging Face `datasets` library. |
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```python |
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import pandas as pd |
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from datasets import load_dataset |
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image_dataset = load_dataset("blamm/retail_visual_rag_pipeline", trust_remote_code=True) |
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product_promotion_data = load_dataset("blamm/retail_visual_rag_pipeline", data_files={'train':'train.parquet', 'test':'test.parquet'}) |
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df_test = product_promotion_data['test'].to_pandas() |
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filename = '1166.jpg' |
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example_data = df_test.loc[df_test.filename == filename] |
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# Show product and promotion data |
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print(example_data) |
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image = image_dataset['test']['image'][example_data.index[0]] |
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# Show image |
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image.show() |
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``` |
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<img src="figures/example_dataset_sample.png" alt="data_sample" width="300"/> |
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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. |
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## License |
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This dataset is licensed under a [Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International](https://creativecommons.org/licenses/by-nc-nd/4.0/) |
