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---
dataset_info:
features:
- name: image_id
dtype: int64
- name: image
dtype: image
- name: objects
struct:
- name: bbox
sequence:
sequence: int64
- name: categories
sequence: string
splits:
- name: train
num_bytes: 71015506.0
num_examples: 566
download_size: 70817145
dataset_size: 71015506.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "oct-object-detection-v4"
Dataset is composed of images with multiples object detection box in coco format (xmin, ymin, xmax, ymax). Images are OCT (type of eye scaner) with boxes indicating some features associated to AMD disease.
The difference from v3 is images are grouped (not duplicated images in multiples row) and they can have multiples labels-boxes in the objects field. So there are, 566 unique images, there are 566 rows, one per image.
[Source datataset](https://doi.org/10.1101/2023.03.29.534704) |