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--- |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: prompt |
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dtype: string |
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- name: label |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 23257283614.36 |
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num_examples: 153128 |
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download_size: 23241036646 |
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dataset_size: 23257283614.36 |
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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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task_categories: |
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- object-detection |
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language: |
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- tr |
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--- |
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This dataset is combined and deduplicated version of [coco-2014](https://huggingface.co/datasets/detection-datasets/coco) and [coco-2017](https://huggingface.co/datasets/rafaelpadilla/coco2017) datasets for object detection. The labels are in Turkish and the dataset is in an instruction-tuning format with separate columns for prompts and completion labels. |
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For the bounding boxes, a similar annotation scheme to that of [PaliGemma](https://huggingface.co/blog/paligemma#Detection) annotation is used. That is, |
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``` |
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The bounding box coordinates are in the form of special <loc[value]> tokens, where value is a number that represents a normalized coordinate. Each detection is represented by four location coordinates in the order x_min(left), y_min(top), x_max(right), y_max(bottom), followed by the label that was detected in that box. To convert values to coordinates, you first need to divide the numbers by 1024, then multiply y by the image height and x by its width. This will give you the coordinates of the bounding boxes, relative to the original image size. |
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``` |
