Blood Cell Detection Dataset

Overview

This is a dataset of blood cells photos.

There are 364 images across three classes: WBC (white blood cells), RBC(red blood cells), and Platelets. There are 4888 labels across 3 classes (and 0 null examples).

Fork this dataset (upper right hand corner) to receive the raw images, or (to save space) grab the 500x500 export.

Use Cases

This is a small scale object detection dataset, commonly used to assess model performance. It's a first example of medical imaging capabilities. This dataset is mainly preprocessed for YOLOV5 Application.

Using this Dataset

I'm releasing the data as public domain. Feel free to use it for any purpose. This dataset is already splitted into train,testing and validation datasets(70% for training, 20% testing and 10% for validation). The train,testing and validation folders are further classified as IMAGES AND LABELS.

images Folder : It contains images of blood cells. labels Folder : It conatins labelling of blood cells across three classes: WBC (white blood cells), RBC (red blood cells), and Platelets.

Except for GitHub, this dataset is also published on Kaggle.