| --- |
| 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) |
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| A curated and cleaned celebrity face dataset used for training and evaluating: |
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| - **Face Recognition Model (CNN Embeddings + SVM)** |
| - **Face Recognition Demo App (Streamlit)** |
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| This dataset contains **105 identities** and **~18,000 manually organized images**, formatted for deep-learning–based face recognition pipelines. |
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| --- |
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| ## 📁 Dataset Structure |
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| The dataset follows a simple folder-based classification format: |
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| ``` |
| face_recognition_dataset/ |
| ├── person_1/ |
| ├── person_2/ |
| ├── ... |
| └── person_105/ |
| ``` |
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| Each folder contains multiple face images for that identity. |
| This structure is compatible with most ML frameworks and embedding-based models. |
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| --- |
|
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| ## 📦 Contents |
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| - **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 |
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| --- |
|
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| ## 🧠 Model Trained on This Dataset |
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| The official model trained on this dataset is available at: |
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| **Model Repository:** `AI-Solutions-KK/face_recognition` |
| Contains: |
| - `svc_model.pkl` |
| - `classes.npy` |
| - `centroids.npy` |
| - Metadata + reproducible training pipeline |
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| The model achieves **~99% accuracy** on this dataset. |
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| --- |
|
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| ## 🚀 Demo App Using This Dataset |
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| A complete interactive app using this dataset is available at: |
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| **App Repository:** `AI-Solutions-KK/face_recognition_model_demo_app` |
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| Features: |
| - Image selection browser |
| - Real-time prediction |
| - Training report |
| - Prediction report |
| - Confusion matrix display |
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| The app automatically downloads this dataset inside the Space using `snapshot_download()`. |
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| --- |
|
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| ## 🧩 Recommended Usage |
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| ```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, |
| ) |
| ``` |
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| After download, the dataset will be available at: |
|
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| ``` |
| my_dataset/face_recognition_dataset/<class>/<image>.jpg |
| ``` |
|
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| --- |
|
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| ## 🔧 Suitable For |
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| - Face recognition research |
| - Deep metric learning |
| - Identity classification |
| - Transfer learning experiments |
| - Benchmarking models like: |
| - FaceNet |
| - ArcFace |
| - MobileFaceNet |
| - InsightFace |
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| --- |
|
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| ## 👤 Author |
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| Developed and organized by **Karan (AI-Solutions-KK)** |
| Please ⭐ the repo if you find it useful. |
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