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--- |
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language: |
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- en |
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task_categories: |
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- image-classification |
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- object-detection |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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dataset_info: |
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features: |
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- name: image_id |
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dtype: string |
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- name: image |
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dtype: image |
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- name: label_cat_dog |
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dtype: string |
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- name: label_breed |
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dtype: string |
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- name: label_bbox_enriched |
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list: |
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- name: bbox |
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sequence: float64 |
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- name: confidence |
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dtype: float64 |
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- name: label |
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dtype: string |
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- name: caption_enriched |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 378674920.2 |
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num_examples: 3680 |
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- name: test |
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num_bytes: 413573829.357 |
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num_examples: 3669 |
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download_size: 790823158 |
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dataset_size: 792248749.5569999 |
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--- |
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|
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[](https://app.visual-layer.com/dataset/3972b3fc-1809-11ef-bb76-064432e0d220/data?p=1&page=1) |
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# Oxford-IIIT-Pets-VL-Enriched |
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An enriched version of the Oxford IIIT Pets Dataset with image caption and bounding boxes. |
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With this additional information, the Oxford IIIT Pet dataset can be extended to a variety of tasks such as image retrieval or visual question answering. |
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## Description |
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The dataset consists of 6 columns: |
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+ `image_id`: Unique identifier for each image. `image_id` is the original filename of the image from Oxford IIIT Pets dataset. |
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+ `image`: Image data in the form of PIL Image. |
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+ `label_cat_dog`: Label for the image, whether it is a cat or a dog. Provided by the authors of the original dataset. |
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+ `label_breed`: Label for the breed of the cat or dog in the image. Consists of 37 pet breeds of cats and dogs. Provided by the authors of the original dataset. |
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+ `label_bbox_enriched`: Enriched labels for the image. Consists of bounding box coordinates, confidence score and label for the bounding box. Generated by in-house and customized YOLOv8 model. |
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+ `caption_enriched`: Enriched captions for the image. Generated by BLIP2 captioning model. |
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## Usage |
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This dataset can be used with the Hugging Face Datasets library.: |
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```python |
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import datasets |
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ds = datasets.load_dataset("visual-layer/oxford-iiit-pet-vl-enriched") |
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``` |
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More in this [notebook](usage.ipynb). |
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## Interactive Visualization |
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Visual Layer provides a platform to interactively visualize the dataset. |
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Check it out [here](https://app.visual-layer.com/vl-datasets). No sign-up required. |
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/6195f404c07573b03c61702c/ik52fzk8FqeHNP2K2_ARM.mp4"></video> |
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## License & Disclaimer |
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We provide no warranty of the dataset, and the user takes full responsibility for the usage of the dataset. By using the dataset, you agree to the terms of the Oxford IIIT Pets dataset license. |
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## About Visual Layer |
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<div style="text-align: center; margin-top:50px;"> |
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<a href="https://visual-layer.com/" style="padding:10px; display: inline-block;"> |
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<a href="https://github.com/visual-layer/fastdup" style="padding:10px; display: inline-block;"> |
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<img alt="youtube" src="https://vl-blog.s3.us-east-2.amazonaws.com/imgs/youtube.png" width="50"></a> |
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<a href="https://twitter.com/visual_layer" style="padding:10px; display: inline-block;"> |
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<img alt="twitter" src="https://vl-blog.s3.us-east-2.amazonaws.com/imgs/x.png" width="50"></a> |
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</div> |
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<div style="text-align: center;"> |
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<img style="width:200px; display: block; margin: 0 auto;" alt="logo" src="https://d2iycffepdu1yp.cloudfront.net/design-assets/VL_horizontal_logo.png"> |
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<div style="margin-top:20px;">Copyright © 2024 Visual Layer. All rights reserved.</div> |
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</div> |
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