tf-keras added to requirements & created Readme

README.md

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+# FaceMatch
+
+FaceMatch is an AI-powered Django application that uses the DeepFace library to find facial similarities by comparing image embeddings. The project offers two endpoints: one for saving user images as embeddings and another for comparing a given image against saved embeddings to find a matching face. This tool is ideal for applications such as identity verification, duplicate detection, or face matching in various organizational contexts.
+
+## Features
+
+- **Facial Embedding Generation**: Converts uploaded images into numerical embeddings using deep learning models.
+- **Face Similarity Comparison**: Compares new images with stored embeddings to find similar faces, providing a similarity score.
+- **Multiple Model Support**: Leverages various models like Facenet, VGG-Face, and others from the DeepFace library.
+- **Organizational Segmentation**: Manages embeddings on a per-organization basis for better data isolation.
+
+## Tech Stack
+
+- **Backend**: Django, Django REST Framework
+- **Machine Learning**: DeepFace for facial recognition
+- **Database**: SQLite (default) or any other supported by Django ORM
+
+## Installation
+
+1. **Clone the repository**:
+    ```bash
+    git clone https://github.com/your-username/FaceMatch.git
+    cd FaceMatch
+    ```
+
+2. **Set up a virtual environment**:
+    ```bash
+    python -m venv venv
+    source venv/bin/activate # On Windows use `venv\Scripts\activate`
+    ```
+
+3. **Install dependencies**:
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+4. **Apply migrations**:
+    ```bash
+    python manage.py migrate
+    ```
+
+5. **Run the server**:
+    ```bash
+    python manage.py runserver
+    ```
+
+## API Endpoints
+
+### 1. Embedding Endpoint
+   - **URL**: `/api/embeddings/`
+   - **Method**: `POST`
+   - **Description**: Saves images for a specific organization and generates embeddings.
+   - **Request**:
+     ```json
+     {
+       "organization": "string",
+       "images": [file]
+     }
+     ```
+   - **Response**:
+     ```json
+     {
+       "embed_id": "integer",
+       "organization": "string",
+       "embedding": "string",
+       "created_at": "datetime"
+     }
+     ```
+
+### 2. Face Comparison Endpoint
+   - **URL**: `/api/face-compare/`
+   - **Method**: `POST`
+   - **Description**: Compares an uploaded image with the saved embeddings for a specific organization.
+   - **Request**:
+     ```json
+     {
+       "organization": "string",
+       "image": file
+     }
+     ```
+   - **Response**:
+     ```json
+     {
+       "embed_id": "integer",
+       "similarity_score": "float"
+     }
+     ```
+
+## Project Structure
+
+- **views.py**: Contains API views for embedding generation and face comparison.
+- **services.py**: Handles core logic for embedding generation, comparison, and utility functions for processing images.
+- **utils.py**: Provides helper functions for saving images, embedding processing, and finding similar faces.
+- **models.py**: Defines database models for storing embeddings and associated image metadata.
+- **serializers.py**: Serializes input data for the API endpoints.
+
+## Example Usage
+
+### Save Embeddings
+To save embeddings for an organization, send a `POST` request to `/api/embeddings/` with the following body:
+```bash
+curl -X POST http://localhost:8000/api/embeddings/ \
+-F "organization=MyOrganization" \
+-F "images=@/path/to/image1.jpg" \
+-F "images=@/path/to/image2.jpg"
+```
+### Compare Faces
+To compare a face, send a POST request to /api/face-compare/:
+
+```bash
+curl -X POST http://localhost:8000/api/face-compare/ \
+-F "organization=MyOrganization" \
+-F "image=@/path/to/query_image.jpg"
+```
+
+## Contributing
+
+Feel free to open issues or submit pull requests for improvements. Contributions to enhance functionality or fix bugs are always welcome.

requirements.txt

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 deepface==0.0.93
 Django==5.1.2
-djangorestframework==3.15.2
+djangorestframework==3.15.2
+tf-keras==2.17.0