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TrainingDataPro/facial-hair-classification-dataset

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Hugging Face2024-04-24 更新2024-03-04 收录
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--- license: cc-by-nc-nd-4.0 task_categories: - image-classification language: - en tags: - code --- # Facial Hair Classification & Object Detection dataset The Facial Hair Classification Dataset is a comprehensive collection of high-resolution images showcasing individuals **with and without** a beard. The dataset includes a diverse range of individuals of various ages, ethnicities, and genders. # 💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on **[TrainingData](https://trainingdata.pro/datasets/facial-hair-classification?utm_source=huggingface&utm_medium=cpc&utm_campaign=facial-hair-classification-dataset)** to buy the dataset The dataset also contains images of individuals **without facial hair**, serving as a valuable reference for comparison and contrast. These images showcase clean-shaven faces, enabling research into distinguishing facial hair patterns from those without any beard growth. Each image in the dataset is carefully curated to showcase the subject's face prominently and with optimal lighting conditions, ensuring clarity and accuracy in the classification and analysis of facial hair presence. ### Types of photos in the dataset: - **beard** - photos of people **with** a beard. - **no beard** - photos of people **without** a beard. ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F72e33b9bbe0a8539635aba2fd997eb99%2Fbb.png?generation=1690557438276163&alt=media) The Facial Hair Classification Dataset offers a robust collection of images that accurately represent the diverse range of facial hair styles found in the real world. This dataset provides ample opportunities for training facial recognition algorithms, identifying facial hair patterns, and conducting research on facial hair classification and analysis. # 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[https://trainingdata.pro/datasets](https://trainingdata.pro/datasets/facial-hair-classification?utm_source=huggingface&utm_medium=cpc&utm_campaign=facial-hair-classification-dataset) to discuss your requirements, learn about the price and buy the dataset** # Content The dataset is splitted in three folders: **train**, **validate** and **test** to build a classification model. Each of these folders includes: - **beard** folder: includes photos of people **with** a beard - **no_beard** folder: includes photos of people **without** a beard ### File with the extension .csv - **file**: link to access the media file, - **type**: does a person has or has not a beard # Files for Facial Hair Classification might be collected in accordance with your requirements. ## **[TrainingData](https://trainingdata.pro/datasets/facial-hair-classification?utm_source=huggingface&utm_medium=cpc&utm_campaign=facial-hair-classification-dataset)** provides high-quality data annotation tailored to your needs More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets** TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets** *keywords: facial hair classification, image classification, mustaches, beard detection, beard segmentation, beard recognition, biometric dataset, biometric data dataset,face detection dataset, facial analysis, human images dataset, face images, multi-task learning approach, facial hair types*
提供机构:
TrainingDataPro
原始信息汇总

Facial Hair Classification & Object Detection dataset 概述

数据集描述

  • 名称: Facial Hair Classification Dataset
  • 内容: 包含高分辨率图像,展示有胡须和无胡须的个体。图像涵盖不同年龄、种族和性别的多样性。
  • 图像类型:
    • 有胡须:展示有胡须的人的照片。
    • 无胡须:展示无胡须的人的照片。

数据集结构

  • 文件夹结构: 分为 train, validate, test 三个文件夹。
    • train 文件夹: 包含 beardno_beard 子文件夹。
    • validate 文件夹: 包含 beardno_beard 子文件夹。
    • test 文件夹: 包含 beardno_beard 子文件夹。
  • CSV文件: 包含每个图像的链接和胡须类型(有或无)。

数据集用途

  • 用于训练面部识别算法。
  • 用于识别面部胡须模式。
  • 用于面部胡须分类和分析的研究。

许可

  • 许可证: cc-by-nc-nd-4.0

语言

  • 语言: 英文 (en)

标签

  • 标签: 代码 (code)
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