Datasets:
Tasks:
Object Detection
Size:
< 1K
File size: 2,160 Bytes
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---
task_categories:
- object-detection
tags:
- roboflow
- roboflow2huggingface
- Biology
---
<div align="center">
<img width="640" alt="keremberke/blood-cell-object-detection" src="https://huggingface.co/datasets/keremberke/blood-cell-object-detection/resolve/main/thumbnail.jpg">
</div>
### Dataset Labels
```
['platelets', 'rbc', 'wbc']
```
### Number of Images
```json
{'train': 255, 'test': 36, 'valid': 73}
```
### How to Use
- Install [datasets](https://pypi.org/project/datasets/):
```bash
pip install datasets
```
- Load the dataset:
```python
from datasets import load_dataset
ds = load_dataset("keremberke/blood-cell-object-detection", name="full")
example = ds['train'][0]
```
### Roboflow Dataset Page
[https://universe.roboflow.com/team-roboflow/blood-cell-detection-1ekwu/dataset/3](https://universe.roboflow.com/team-roboflow/blood-cell-detection-1ekwu/dataset/3?ref=roboflow2huggingface)
### Citation
```
@misc{ blood-cell-detection-1ekwu_dataset,
title = { Blood Cell Detection Dataset },
type = { Open Source Dataset },
author = { Team Roboflow },
howpublished = { \\url{ https://universe.roboflow.com/team-roboflow/blood-cell-detection-1ekwu } },
url = { https://universe.roboflow.com/team-roboflow/blood-cell-detection-1ekwu },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { nov },
note = { visited on 2023-01-18 },
}
```
### License
Public Domain
### Dataset Summary
This dataset was exported via roboflow.com on November 4, 2022 at 7:46 PM GMT
Roboflow is an end-to-end computer vision platform that helps you
* collaborate with your team on computer vision projects
* collect & organize images
* understand unstructured image data
* annotate, and create datasets
* export, train, and deploy computer vision models
* use active learning to improve your dataset over time
It includes 364 images.
Cells are annotated in COCO format.
The following pre-processing was applied to each image:
* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Resize to 416x416 (Stretch)
No image augmentation techniques were applied.
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