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README.md
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class_label:
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names:
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'0': abdomen-MRI
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'1':
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---
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# Dataset Card for "abdomen-mri"
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class_label:
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names:
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'0': abdomen-MRI
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'1': 0
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annotations_creators:
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- crowdsourced
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language_creators:
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- found
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language:
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- en
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license:
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- cc
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multilinguality:
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- monolingual
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size_categories:
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- 1K<n<10K
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source_datasets:
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- original
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task_categories:
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- object-detection
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task_ids: []
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pretty_name: abdomen-mri
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tags:
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- rf100
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---
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# Dataset Card for abdomen-mri
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** The original COCO dataset is stored at `dataset.tar.gz`**
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## Dataset Description
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- **Homepage:** https://universe.roboflow.com/object-detection/abdomen-mri
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- **Point of Contact:** francesco.zuppichini@gmail.com
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### Dataset Summary
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abdomen-mri
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### Supported Tasks and Leaderboards
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- `object-detection`: The dataset can be used to train a model for Object Detection.
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### Languages
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English
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## Dataset Structure
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### Data Instances
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A data point comprises an image and its object annotations.
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```
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{
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'image_id': 15,
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'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x640 at 0x2373B065C18>,
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'width': 964043,
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'height': 640,
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'objects': {
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'id': [114, 115, 116, 117],
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'area': [3796, 1596, 152768, 81002],
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'bbox': [
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[302.0, 109.0, 73.0, 52.0],
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[810.0, 100.0, 57.0, 28.0],
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[160.0, 31.0, 248.0, 616.0],
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[741.0, 68.0, 202.0, 401.0]
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],
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'category': [4, 4, 0, 0]
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}
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}
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```
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### Data Fields
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- `image`: the image id
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- `image`: `PIL.Image.Image` object containing the image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the `"image"` column, *i.e.* `dataset[0]["image"]` should **always** be preferred over `dataset["image"][0]`
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- `width`: the image width
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- `height`: the image height
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- `objects`: a dictionary containing bounding box metadata for the objects present on the image
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- `id`: the annotation id
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- `area`: the area of the bounding box
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- `bbox`: the object's bounding box (in the [coco](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#coco) format)
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- `category`: the object's category.
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#### Who are the annotators?
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Annotators are Roboflow users
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## Additional Information
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### Licensing Information
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See original homepage https://universe.roboflow.com/object-detection/abdomen-mri
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### Citation Information
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```
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@misc{ abdomen-mri,
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title = { abdomen mri Dataset },
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type = { Open Source Dataset },
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author = { Roboflow 100 },
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howpublished = { \url{ https://universe.roboflow.com/object-detection/abdomen-mri } },
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url = { https://universe.roboflow.com/object-detection/abdomen-mri },
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journal = { Roboflow Universe },
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publisher = { Roboflow },
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year = { 2022 },
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month = { nov },
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note = { visited on 2023-03-29 },
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}"
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```
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### Contributions
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Thanks to [@mariosasko](https://github.com/mariosasko) for adding this dataset.
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