ava-FLUX.1-latents-5k

# Dataset Card for AVA FLUX.1-schnell Latents 5k

<!-- Provide a quick summary of the dataset. -->

5k latents from FLUX.1-schnell VAE for the AVA dataset

## Dataset Details

### Dataset Description

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- **Curated by:** [Dave Lage](https://huggingface.com/rockerBOO)
- **License:** [Apache-2.0](https://huggingface.co/rockerBOO/ava-flux.1-schnell-latents-5k)

### Dataset Sources [optional]

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- **Repository:** [More Information Needed]

## Uses

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Latents are a sample from the AVA dataset. These latents were created using the [FLUX.1-schnell](https://github.com/black-forest-labs/FLUX.1-schnell) VAE model. Use of these latents is intended for research purposes only. Useful for Aesthetic Predictions using AVA dataset AVA.txt for aesthetic predictive modeling.

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

- image_id: image id from the AVA dataset
- latents: flattened list of latents
- shape_channels: channels of the VAE (16)
- shape_height: height of the latents
- shape_width: width of the latents
- original_width: width of the image
- original_height: height of the image
- filename: filename of the image

## Dataset Creation

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

Non-randomized dataset was collected from the AVA dataset. Latents captured from the FLUX.1-schnell VAE. Latents are flattened into a list and dimensions are stored in the dataset parquet file.

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

Latents are from the AVA dataset. Images are not included in this dataset.

## Bias, Risks, and Limitations

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- Dataset is non randomized and not a complete dataset so there is not enough data to create appropriate results.

# AVA FLUX.1-schnell 隐变量5k数据集卡片
<!-- 提供本数据集的简要概述。 -->
本数据集包含针对AVA数据集的FLUX.1-schnell变分自编码器（Variational Autoencoder, VAE）生成的5000条隐变量（latents）。

## 数据集详情
### 数据集描述

<!-- 详细描述本数据集的具体内容。 -->

- **整理者：** [Dave Lage](https://huggingface.com/rockerBOO)
- **授权协议：** [Apache-2.0](https://huggingface.co/rockerBOO/ava-flux.1-schnell-latents-5k)

### 数据集来源（可选）

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- **代码仓库：** [需补充更多信息]

## 数据集用途

<!-- 阐述本数据集的预期使用场景相关问题。 -->
本数据集的隐变量均取自AVA数据集，通过[FLUX.1-schnell](https://github.com/black-forest-labs/FLUX.1-schnell)变分自编码器（Variational Autoencoder, VAE）生成。本数据集仅可用于科研用途，适用于结合AVA数据集的AVA.txt文件开展美学预测建模的美学预测任务。

## 数据集结构

<!-- 本节描述数据集的字段信息，以及数据集结构的额外细节，例如划分数据集的标准、数据点之间的关系等。 -->

- **image_id：** 取自AVA数据集的图像ID
- **latents：** 扁平化的隐变量列表
- **shape_channels：** 变分自编码器的通道数（16）
- **shape_height：** 隐变量的高度
- **shape_width：** 隐变量的宽度
- **original_width：** 原始图像的宽度
- **original_height：** 原始图像的高度
- **filename：** 图像的文件名

## 数据集构建

#### 数据收集与处理

<!-- 本节描述数据收集与处理流程，例如数据选择标准、过滤与归一化方法、使用的工具与库等。 -->
本数据集为非随机抽样的AVA数据集子集，隐变量通过FLUX.1-schnell变分自编码器提取。隐变量被整理为扁平化列表，其维度信息存储于数据集的Parquet文件中。

#### 个人与敏感信息

<!-- 说明数据集是否包含可能被视为个人、敏感或隐私的数据（例如：泄露地址、唯一可识别的姓名或别名、种族或族裔背景、性取向、宗教信仰、政治观点、财务或健康数据等）。若已对数据进行匿名化处理，请描述匿名化流程。 -->
本数据集的隐变量取自AVA数据集，原始图像并未包含在本数据集中。

## 偏差、风险与局限性

<!-- 本节旨在阐述技术与社会技术层面的局限性。 -->

- 本数据集为非随机抽样的不完整子集，数据量不足以生成可靠的实验结果。