Facial-Landmarks-Detection-with-DLIB

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Facial-Landmarks-Detection-with-DLIB

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# Facial Landmarks Detection with DLIB
### Detects the face landmarks such as nose, eyes, etc. using just Python, OpenCV and dlib

Amazing and easy face landmarks detector with dlib library.

All thanks to Adrian Rosebrock (from [pyimagesearch](https://www.pyimagesearch.com/)) for making
great tutorials. This project is inspired from his blog: [Facial landmarks with dlib, OpenCV, and Python](https://www.pyimagesearch.com/2017/04/03/facial-landmarks-dlib-opencv-python/). I have included the author's code and the one i wrote my self as well.

## **Key Points**
1. Steps involved:
    1. Localize the face in the image
    2. Detect the key facial structures on the face ROI
2. Assumptions:
    1. We already have the trained face detector and face landmark detector.
3. Variety of things the face detector detects:
    1. Nose
    2. Mouth
    3. Left eye
    4. Right eye
    5. Left eyebrow
    6. Right eyebrow
    7. Jaw
4. Data required for training of dlib's facial landmark detector:
    1. Training set of labeled facial landmarks on the image.
    2. Priors: Probability on distance between pairs of input pixels
5. The dlib's face detector is an implementation of **One Millisecond Face Alignment with an Ensemble of Regression Trees** paper by Kazemi and Sullivan (2014).
6. 68 coordinates are detected for the given face by the face detector. The image is shown below.
![Face landmarks coordinates image](https://raw.githubusercontent.com/Practical-CV/Facial-Landmarks-Detection-with-DLIB/master/images/facial_landmarks_68markup-768x619.jpg)
7. dlib's framework can be trained to predict any shape. Hence it can be used for custom shape detections as well.
8. Used dlib's pre-trained face detector based on the modification of the standard **Histogram of Oriented Gradients + Linear SVM method** for object detection.
9. The face detector used up-scaling before face detection for better results.
10. This method works even for multiple faces in the image.

## **Requirements: (with versions i tested on)**
 1. python          (3.7.3)
 2. opencv          (4.1.0)
 3. numpy           (1.61.4)
 4. imutils         (0.5.2)
 5. dlib            (19.17.0)

## **Commands to run the detection:**
 ```
python facial_landmarks_mine.py --shape-predictor shape_predictor_68_face_landmarks.dat --image images/example_01.jpg
```

## **Results:**
The results are awesome. We can see pretty accurate face landmark detections.

**Input**

![Example input 1](https://raw.githubusercontent.com/Practical-CV/Facial-Landmarks-Detection-with-DLIB/master/images/example_01.jpg)

**Output**

![Example output 1](https://raw.githubusercontent.com/Practical-CV/Facial-Landmarks-Detection-with-DLIB/master/images/output_01.jpg)

**Input**

![Example input 2](https://raw.githubusercontent.com/Practical-CV/Facial-Landmarks-Detection-with-DLIB/master/images/example_02.jpg)

**Output**

![Example output 2](https://raw.githubusercontent.com/Practical-CV/Facial-Landmarks-Detection-with-DLIB/master/images/output_02.jpg)

## **The limitations**
None

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