MODEL PROFILE · 模型档案

Race-Classification-FairFace-YOLOv8

Anzhc · Race-Classification-FairFace-YOLOv8

This model is based on FairFace 0.25 padding variant dataset composed by Microsoft researchers, aiming to reduce bias by better balancing classes in dataset. > **Karkkainen, Kimmo, and Joo, Jungseock.** > *FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation.* > Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2021, pp. 1548–1558. > FairFace Dataset on GitHub This YOLOv8 training is meant only for race classification. I wanted a really really fast model for tagging, and this is likely what it's useful for! ~~I will provide a pipeline for running it on your datasets in future.~~ I've made simple scripts for you to use on your data. By default it will output .txt files(or append to existing), so modify for your specific needs: https://github.com/Anzhc/Simple-Utility-Scripts-for-YOLO/tree/main

译文排队中,当前展示来源原文。

图像分类license:agpl-3.0
上下文窗口来源未披露
输入 → 输出图像 → 待核验
模型权重待核验
档案更新时间2026/11/2 19:15:34
OVERVIEW

模型介绍

This model is based on FairFace 0.25 padding variant dataset composed by Microsoft researchers, aiming to reduce bias by better balancing classes in dataset. > **Karkkainen, Kimmo, and Joo, Jungseock.** > *FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation.* > Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2021, pp. 1548–1558. > FairFace Dataset on GitHub This YOLOv8 training is meant only for race classification. I wanted a really really fast model for tagging, and this is likely what it's useful for! ~~I will provide a pipeline for running it on your datasets in future.~~ I've made simple scripts for you to use on your data. By default it will output .txt files(or append to existing), so modify for your specific needs: https://github.com/Anzhc/Simple-Utility-Scripts-for-YOLO/tree/main

主要特点

特点摘要待依据来源补齐,不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价,不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价,请查阅来源渠道。

按月估算基础 Token 费用

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预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用?

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗?

不是实时结算价格,而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

许可证:agpl-3.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。