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.