### Install RetinaFace Python Library

Source: https://github.com/serengil/retinaface/blob/master/README.md

Installs the retina-face library and its dependencies from PyPI using pip. This is the recommended method for easy setup.

```shell
pip install retina-face
```

--------------------------------

### Import RetinaFace Library

Source: https://github.com/serengil/retinaface/blob/master/README.md

Imports the necessary RetinaFace class from the installed library to enable its use in Python scripts. This is a prerequisite for all other functionalities.

```python
from retinaface import RetinaFace
```

--------------------------------

### Perform Face Recognition with DeepFace and RetinaFace

Source: https://github.com/serengil/retinaface/blob/master/README.md

Performs face verification between two images using the DeepFace library, with RetinaFace as the chosen face detector and ArcFace as the recognition model. The function returns a boolean indicating whether the faces are verified as the same person. This requires installing the deepface library and assumes the availability of RetinaFace.

```python
#!pip install deepface
from deepface import DeepFace
obj = DeepFace.verify("img1.jpg", "img2.jpg"
          , model_name = 'ArcFace', detector_backend = 'retinaface')
print(obj["verified"])
```

--------------------------------

### Detect Faces in an Image

Source: https://github.com/serengil/retinaface/blob/master/README.md

Performs face detection on a given image file. The function takes the image path as input and returns a JSON object containing bounding box coordinates, confidence scores, and facial landmarks for each detected face. The output format is a dictionary where keys are face identifiers (e.g., 'face_1').

```python
resp = RetinaFace.detect_faces("img1.jpg")
```

--------------------------------

### Extract and Align Faces

Source: https://github.com/serengil/retinaface/blob/master/README.md

Extracts detected faces from an image and optionally applies alignment based on facial landmarks. This function takes an image path and a boolean for alignment as input. It returns a list of face image arrays, which can then be displayed or further processed. Dependencies include matplotlib for displaying images.

```python
import matplotlib.pyplot as plt
faces = RetinaFace.extract_faces(img_path = "img.jpg", align = True)
for face in faces:
  plt.imshow(face)
  plt.show()
```

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