Datasets:
File size: 2,109 Bytes
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license: mit
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': ai_generated
'1': human_created
- name: image_name
dtype: string
splits:
- name: train
num_bytes: 831331860
num_examples: 11998
- name: test
num_bytes: 102610854
num_examples: 1500
- name: validation
num_bytes: 101540782
num_examples: 1499
download_size: 1035437916
dataset_size: 1035483496
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
task_categories:
- image-classification
language:
- en
tags:
- images
- ai
pretty_name: Skynet Detection
size_categories:
- 10K<n<100K
---
# Description
Roughly 15k images evenly split between AI generated and human generated for the purpose of training models to detect AI generated content.
Images have been converted to numpy arrays and resized to 224x224x3 for alignment with CNN models available on Tensorflow
# Sources
The following sources were used to collect the images
[AI vs Human](Hemg/AI-Generated-vs-Real-Images-Datasets)
[Open Images V7](https://storage.googleapis.com/openimages/web/index.html)
[Laion - 400M](https://laion.ai/)
# Dataset_Info
Features:
- name: image
dtype: numpy arrays (224x224x3)
- name: label
dtype: class_label
- names:
- '0': ai_generated
- '1': human_created
- name: image_name
dtype: string
description: unique index for tracking image
Splits:
- name: train
num_bytes: 831 Mb
num_examples: 11,998
- name: test
num_bytes: 102 Mb
num_examples: 1,500
- name: validation
num_bytes: 101 Mb
num_examples: 1,499
download_size: 1.04 Gb
dataset_size: 1.04 Gb
Configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-* |