---
title: Face Recognition Dataset (105 Classes)
emoji: 📸
colorFrom: yellow
colorTo: orange
sdk: python
tags:
- dataset
- face-recognition
- embeddings
- computer-vision
license: mit
---

# 📸 Face Recognition Dataset (105 Classes)

A curated and cleaned celebrity face dataset used for training and evaluating:

- **Face Recognition Model (CNN Embeddings + SVM)**
- **Face Recognition Demo App (Streamlit)**

This dataset contains **105 identities** and **~18,000 manually organized images**, formatted for deep-learning–based face recognition pipelines.

---

## 📁 Dataset Structure

The dataset follows a simple folder-based classification format:

```
face_recognition_dataset/
  ├── person_1/
  ├── person_2/
  ├── ...
  └── person_105/
```

Each folder contains multiple face images for that identity.  
This structure is compatible with most ML frameworks and embedding-based models.

---

## 📦 Contents

- **18k+ images**
- **105 celebrity identities**
- Cleaned, resized, organized folder structure
- Suitable for:
  - Embedding extraction (FaceNet, ArcFace, etc.)
  - Classification (SVM, kNN, cosine similarity)
  - Clustering
  - Evaluation & benchmarking

---

## 🧠 Model Trained on This Dataset

The official model trained on this dataset is available at:

**Model Repository:** `AI-Solutions-KK/face_recognition`  
Contains:
- `svc_model.pkl`
- `classes.npy`
- `centroids.npy`
- Metadata + reproducible training pipeline

The model achieves **~99% accuracy** on this dataset.

---

## 🚀 Demo App Using This Dataset

A complete interactive app using this dataset is available at:

**App Repository:** `AI-Solutions-KK/face_recognition_model_demo_app`

Features:
- Image selection browser  
- Real-time prediction  
- Training report  
- Prediction report  
- Confusion matrix display  

The app automatically downloads this dataset inside the Space using `snapshot_download()`.

---

## 🧩 Recommended Usage

```python
from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="AI-Solutions-KK/face_recognition_dataset",
    repo_type="dataset",
    local_dir="my_dataset",
    local_dir_use_symlinks=False,
)
```

After download, the dataset will be available at:

```
my_dataset/face_recognition_dataset/<class>/<image>.jpg
```

---

## 🔧 Suitable For

- Face recognition research  
- Deep metric learning  
- Identity classification  
- Transfer learning experiments  
- Benchmarking models like:
  - FaceNet  
  - ArcFace  
  - MobileFaceNet  
  - InsightFace  

---

## 👤 Author

Developed and organized by **Karan (AI-Solutions-KK)**  
Please ⭐ the repo if you find it useful.