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toilaluan/JourneyDB-recaption

JourneyDB Recaption Recaptioned version of the JourneyDB dataset using Qwen vision-language models. Dataset Description JourneyDB is a large-scale dataset of AI-generated images from Midjourney. This recaptioned version provides detailed visual descriptions generated by a vision-language model, which are more accurate than the original generation prompts for describing actual image content. Statistics Metric Count Total rows 3,389,605… See the full description on the dataset page: https://huggingface.co/datasets/toilaluan/JourneyDB-recaption.

sourceHugging Facecc-by-nc-4.0updated 10d agoView on Hugging Face
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JourneyDB Recaption

Recaptioned version of the JourneyDB dataset using Qwen vision-language models.

Dataset Description

JourneyDB is a large-scale dataset of AI-generated images from Midjourney. This recaptioned version provides detailed visual descriptions generated by a vision-language model, which are more accurate than the original generation prompts for describing actual image content.

Statistics

MetricCount
Total rows3,389,605
File size~246 MB (Parquet)

Columns

ColumnTypeDescription
img_pathstringRelative path to image in JourneyDB
widthintImage width in pixels
heightintImage height in pixels
aesthetic_scorefloatAesthetic score (may be null for some)
captionstringGenerated visual description
modelstringModel used for recaptioning

Recaption Models

ModelCount
Qwen/Qwen3-VL-8B-Instruct2,249,747
Qwen/Qwen2.5-VL-7B-Instruct1,139,858
  • —Prompt style: COCO-style short caption ("Describe this image in one simple sentence...")

Preprocessing

Before recaptioning, the following filters were applied to the original JourneyDB dataset:

  • —Resolution filter: min(width, height) >= 512
  • —Aspect ratio filter: max(width, height) / min(width, height) <= 2.0

Example

python
{
    "img_path": "./000/728deb7c-a5e2-463c-8f75-5f62dae521ac.jpg",
    "width": 1024,
    "height": 1024,
    "aesthetic_score": 7.276855,
    "caption": "A girl sits at a table with books, looking directly at the camera.",
    "model": "Qwen/Qwen2.5-VL-7B-Instruct"
}

Usage

python
from datasets import load_dataset

dataset = load_dataset("undefined443/JourneyDB-recaption")

Access the data:

python
for sample in dataset["train"]:
    img_path = sample["img_path"]
    caption = sample["caption"]
    width, height = sample["width"], sample["height"]
    aesthetic_score = sample["aesthetic_score"]
    # Use with JourneyDB images

License

This dataset inherits the license from JourneyDB (CC-BY-NC-4.0).

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