README.md

---
task_categories:
- image-classification
tags:
- roboflow
- roboflow2huggingface
- Gaming
---

<div align="center">
  <img width="640" alt="fcakyon/pokemon-classification" src="https://huggingface.co/datasets/fcakyon/pokemon-classification/resolve/main/thumbnail.jpg">
</div>

### Dataset Labels

```
['test', 'train', 'valid', 'valid-mini']
```


### Number of Images

```json
{'train': 4869, 'test': 732, 'valid': 1390}
```


### 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("fcakyon/pokemon-classification", name="full")
example = ds['train'][0]
```

### Roboflow Dataset Page
[https://universe.roboflow.com/robert-demo-qvail/pokedex/dataset/14](https://universe.roboflow.com/robert-demo-qvail/pokedex/dataset/14?ref=roboflow2huggingface)

### Citation

```
@misc{ pokedex_dataset,
    title = { Pokedex Dataset },
    type = { Open Source Dataset },
    author = { Lance Zhang },
    howpublished = { \\url{ https://universe.roboflow.com/robert-demo-qvail/pokedex } },
    url = { https://universe.roboflow.com/robert-demo-qvail/pokedex },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { dec },
    note = { visited on 2023-01-14 },
}
```

### License
Public Domain

### Dataset Summary
This dataset was exported via roboflow.com on December 20, 2022 at 5:34 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 6991 images.
Pokemon are annotated in folder format.

The following pre-processing was applied to each image:
* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Resize to 224x224 (Fit (black edges))

No image augmentation techniques were applied.