Biggest GenderFace Recognition Dataset
This dataset includes over 27,000 images of human faces divided into two categories: men and women. The files are renamed to indicate the category, making them easier to use in supervised learning.
27,167 JPG images, classified as male (17,678) and female (9,489)
CC0: Public Domain
Description
Biggest GenderFace Recognition Dataset contains 27,167 JPG photos of human faces, classified into men and women. This corpus is intended to train and test gender recognition models based on facial image analysis.
What is this dataset for?
- Train facial classification models by gender
- Develop automatic gender recognition systems
- Testing CNN and vision transformers architectures for facial recognition
Can it be enriched or improved?
This dataset can be completed with additional annotations (age, expression, ethnicity) to enrich the models. Increasing images can also improve robustness.
🔎 In summary
🧠 Recommended for
- Computer vision researchers
- Students
- AI developers
🔧 Compatible tools
- TensorFlow
- PyTorch
- Keras
- OpenCV
💡 Tip
Add additional annotations to improve the diversity of trained models.
Frequently Asked Questions
How many images does this dataset contain and how are they distributed?
The dataset contains 27,167 images, divided into 17,678 images of men and 9,489 images of women.
Are the images already prepared for use in supervised learning?
Yes, the files are renamed to clearly indicate their male/female category, making it easy to use.
Can this dataset be used for commercial purposes?
Yes, the CC0 license allows unrestricted commercial use.
