Datasets:
dataset_info:
features:
- name: prompt
dtype: string
- name: image1
dtype: image
- name: image2
dtype: image
- name: model1
dtype: string
- name: model2
dtype: string
- name: weighted_results_image1_preference
dtype: float32
- name: weighted_results_image2_preference
dtype: float32
- name: detailed_results_preference
dtype: string
- name: weighted_results_image1_coherence
dtype: float32
- name: weighted_results_image2_coherence
dtype: float32
- name: detailed_results_coherence
dtype: string
- name: weighted_results_image1_alignment
dtype: float32
- name: weighted_results_image2_alignment
dtype: float32
- name: detailed_results_alignment
dtype: string
splits:
- name: train
num_bytes: 32462670063
num_examples: 13000
download_size: 6565441182
dataset_size: 32462670063
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cdla-permissive-2.0
task_categories:
- text-to-image
- image-to-text
- image-classification
- reinforcement-learning
language:
- en
tags:
- Human
- Preference
- Coherence
- Alignment
- country
- language
- flux
- midjourney
- dalle3
- stabeldiffusion
- alignment
- flux1.1
- flux1
- imagen3
- aurora
- lumina
- recraft
- recraft v2
- ideogram
- frames
- reve ai
- halfmoon
- hidream
- Imagen4
- imagen-4.0-ultra-generate-exp-05-20
size_categories:
- 100K<n<1M
pretty_name: >-
Hidream-I1-full vs. Halfmoon / OpenAI 4o / Ideogram V2 / Recraft V2 /
Lumina-15-2-25 / Frames-23-1-25 / Aurora / imagen-3 / Flux-1.1-pro /
Flux-1-pro / Dalle-3 / Midjourney-5.2 / Stabel-Diffusion-3 - Human Preference
Dataset
Rapidata Imagen 4 Preference
This T2I dataset contains over 195k human responses from over 70k individual annotators, collected in just ~1 Day using the Rapidata Python API, accessible to anyone and ideal for large scale evaluation. Evaluating Imagen 4 (imagen-4.0-ultra-generate-exp-05-20) across three categories: preference, coherence, and alignment.
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Overview
This T2I dataset contains over 195k human responses from over 70k individual annotators, collected in just ~1 Day. Evaluating Imagen 4 (imagen-4.0-ultra-generate-exp-05-20) across three categories: preference, coherence, and alignment.
The evaluation consists of 1v1 comparisons between Imagen 4 (imagen-4.0-ultra-generate-exp-05-20) and 15 other models: Hidream I1 full, Halfmoon-4-4-2025, OpenAI 4o-26-3-25, Ideogram V2, Recraft V2, Lumina-15-2-25, Frames-23-1-25, Imagen-3, Flux-1.1-pro, Flux-1-pro, DALL-E 3, Midjourney-5.2, Stable Diffusion 3, Aurora and Janus-7b.
Note: The number following the model name (e.g., Halfmoon-4-4-2025) represents the date (April 4, 2025) on which the images were generated to give an understanding of what model version was used.
Alignment
The alignment score quantifies how well an video matches its prompt. Users were asked: "Which image matches the description better?".
A blue cup and a green cell phone.
Imagen 4
Frames-23-1-25
A person is walking with a guidebook and taking a tour of a historic site.
Imagen 4
Aurora
Coherence
The coherence score measures whether the generated video is logically consistent and free from artifacts or visual glitches. Without seeing the original prompt, users were asked: "Which image has more glitches and is more likely to be AI generated?"
Imagen 4
Stable Diffusion 3
Imagen 4
Ideogram
Preference
The preference score reflects how visually appealing participants found each image, independent of the prompt. Users were asked: "Which image do you prefer?"
Imagen 4
Frames-23-1-25
Imagen 4
Frames-23-1-25
About Rapidata
Rapidata's technology makes collecting human feedback at scale faster and more accessible than ever before. Visit rapidata.ai to learn more about how we're revolutionizing human feedback collection for AI development.