metadata

annotations_creators: []
language: en
size_categories:
  - 1K<n<10K
task_categories:
  - image-classification
task_ids: []
pretty_name: pokemon
tags:
  - fiftyone
  - image
  - image-classification
dataset_summary: |


  ## Installation

  If you haven't already, install FiftyOne:

  ```bash
  pip install -U fiftyone
  ```

  ## Usage

  ```python
  import fiftyone as fo
  from fiftyone.utils.huggingface import load_from_hub

  # Load the dataset
  # Note: other available arguments include 'max_samples', etc
  dataset = load_from_hub("TheSteve0/pokemon")

  # Launch the App
  session = fo.launch_app(dataset)
  ```

Dataset Card for pokemon

This is a FiftyOne dataset with 6991 samples.

All I did was

download the splits of this dataset from Hugging Face https://huggingface.co/datasets/fcakyon/pokemon-classification
Imported them into FiftyOne using ImageClassificationDirectoryTree. See the file pokemon2fo.py
Added tags to the dataset for each split
Merged all the samples into one data set
Pushed the data to Hugging Face Hub using FiftyOne push_to_hub. See the file fo2hub.py

Installation

If you haven't already, install FiftyOne:

pip install -U fiftyone

Usage

import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub

# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("TheSteve0/pokemon")

# Launch the App
session = fo.launch_app(dataset)

Dataset Details

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