*License: MIT*

#  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`..

Example of blood cell: 

1) ![BloodImage_00002_jpg rf 3f628ac8c9a3cccac2926e36a29d7eb5](https://user-images.githubusercontent.com/56868253/135814546-a95dd88c-f785-4154-a74d-13c3e494e61f.jpg)

2) ![BloodImage_00009_jpg rf 021700395b3abd494873446f52e302fd](https://user-images.githubusercontent.com/56868253/135814617-da166eb2-90ef-46a3-9fe4-4d5d6e196df6.jpg)

# Happy learning ML !