README.md

metadata

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

Dataset Labels

['Porygon', 'Goldeen', 'Hitmonlee', 'Hitmonchan', 'Gloom', 'Aerodactyl', 'Mankey', 'Seadra', 'Gengar', 'Venonat', 'Articuno', 'Seaking', 'Dugtrio', 'Machop', 'Jynx', 'Oddish', 'Dodrio', 'Dragonair', 'Weedle', 'Golduck', 'Flareon', 'Krabby', 'Parasect', 'Ninetales', 'Nidoqueen', 'Kabutops', 'Drowzee', 'Caterpie', 'Jigglypuff', 'Machamp', 'Clefairy', 'Kangaskhan', 'Dragonite', 'Weepinbell', 'Fearow', 'Bellsprout', 'Grimer', 'Nidorina', 'Staryu', 'Horsea', 'Electabuzz', 'Dratini', 'Machoke', 'Magnemite', 'Squirtle', 'Gyarados', 'Pidgeot', 'Bulbasaur', 'Nidoking', 'Golem', 'Dewgong', 'Moltres', 'Zapdos', 'Poliwrath', 'Vulpix', 'Beedrill', 'Charmander', 'Abra', 'Zubat', 'Golbat', 'Wigglytuff', 'Charizard', 'Slowpoke', 'Poliwag', 'Tentacruel', 'Rhyhorn', 'Onix', 'Butterfree', 'Exeggcute', 'Sandslash', 'Pinsir', 'Rattata', 'Growlithe', 'Haunter', 'Pidgey', 'Ditto', 'Farfetchd', 'Pikachu', 'Raticate', 'Wartortle', 'Vaporeon', 'Cloyster', 'Hypno', 'Arbok', 'Metapod', 'Tangela', 'Kingler', 'Exeggutor', 'Kadabra', 'Seel', 'Voltorb', 'Chansey', 'Venomoth', 'Ponyta', 'Vileplume', 'Koffing', 'Blastoise', 'Tentacool', 'Lickitung', 'Paras', 'Clefable', 'Cubone', 'Marowak', 'Nidorino', 'Jolteon', 'Muk', 'Magikarp', 'Slowbro', 'Tauros', 'Kabuto', 'Spearow', 'Sandshrew', 'Eevee', 'Kakuna', 'Omastar', 'Ekans', 'Geodude', 'Magmar', 'Snorlax', 'Meowth', 'Pidgeotto', 'Venusaur', 'Persian', 'Rhydon', 'Starmie', 'Charmeleon', 'Lapras', 'Alakazam', 'Graveler', 'Psyduck', 'Rapidash', 'Doduo', 'Magneton', 'Arcanine', 'Electrode', 'Omanyte', 'Poliwhirl', 'Mew', 'Alolan Sandslash', 'Mewtwo', 'Weezing', 'Gastly', 'Victreebel', 'Ivysaur', 'MrMime', 'Shellder', 'Scyther', 'Diglett', 'Primeape', 'Raichu']

Number of Images

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

How to Use

• Install datasets:

pip install datasets

• Load the dataset:

from datasets import load_dataset

ds = load_dataset("keremberke/pokemon-classification", name="full")
example = ds['train'][0]

Roboflow Dataset Page

https://universe.roboflow.com/robert-demo-qvail/pokedex/dataset/14

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.