Datasets:

LakoreAI
/

human-nonhuman-face-classification

license: mit
task_categories:
  - image-classification
tags:
  - human-detection
  - face-classification
  - computer-vision
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': human
            '1': non_human
  splits:
    - name: train
      num_bytes: 58130594.868
      num_examples: 5973
    - name: validation
      num_bytes: 17288633.048
      num_examples: 1706
    - name: test
      num_bytes: 9426595
      num_examples: 855
  download_size: 88469762
  dataset_size: 84845822.91600001

Human vs Non-Human Face Dataset

A robust dataset for binary classification between real human faces and non-human face-like objects (statues, art, gaming, anime).

📊 Dataset Statistics

Split	Human	Non-Human	Total
Train	3,024	2,949	5,973
Validation	864	842	1,706
Test	433	422	855
Total			8,534

📁 Format

Images are decodable as PIL.Image objects.
Labels: 0: human, 1: non_human.

🚀 Quick Start

from datasets import load_dataset
ds = load_dataset("8Opt/human-nonhuman-face-classification")

# Access test set
example = ds['test'][0]
img, label = example['image'], example['label']
img.show()