Feature request

[sitamgithub-MSIT]

Facial Landmark Detection using Mediapipe

Problem Statement

Facial landmark detection is crucial for various applications such as face recognition, emotion analysis, and augmented reality. Current solutions for facial landmark detection may be complex and time-consuming to implement.

Solution

I will implement facial landmark detection using the Mediapipe library, as it provides an easy-to-use and efficient solution for this task. Mediapipe is a popular open-source library developed by Google, and it offers pre-trained models for various computer vision tasks, including facial landmark detection.

Alternatives Considered

1. Implementing a custom facial landmark detection model from scratch requires significant data, expertise, and computational resources.
2. Using other existing libraries for facial landmark detection, but many of them might not be as well-maintained or efficient as Mediapipe.

Approach

1. Install the necessary dependencies, including Mediapipe and relevant Python libraries.
2. Load the pre-trained facial landmark detection model from Mediapipe.
3. Capture or load an image or video stream containing faces.
4. Pass the frames through the facial landmark detection model to obtain the coordinates of facial landmarks.
5. Process the landmarks needed for the specific application (e.g., face alignment, emotion analysis).
6. Display or save the results, depending on the use case.

Additional Context

[Taken from media pipe official documentation]

Mediapipe Documentation: Documentation

[sitamgithub-MSIT]

@akshitagupta15june Can you look into this issue and assign it to me for GSSOC'23 ?

[akshitagupta15june]

Go for it

[varshithar12]

I agree to follow this project's Code of Conduct I'm a GSSOC'24 contributor I want to work on this issue