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# CCN-Group

## 1. Team members - 
### 1. Narasimha Naidu Kommi
### 2. Venkata Sai Shalini Ganni
### 3. Siva Naga Rutwik Reddy Chintha
### 4. Prashanth Sammanu

## 2. Introduction about the selected project - 
### Introduction:

Face parsing, which involves identifying and segmenting different facial components in an image, has been a growing area of research in computer vision and machine learning. With advancements in deep neural networks, it is now possible to develop highly accurate models that can segment facial features with high precision.

The objective of this project is to deploy a pre-existing face parsing PyTorch machine learning model for use in a mobile application. The proposed application will provide users with the ability to perform face parsing on their own images and manipulate or enhance their facial features. it includes separation between each face features such as eyebrows, lips, nose etc. This allows users to pick each indiviual component of the face to be modified.

## 3. What architecture you intend to use - 
### We plan to implement the above model into a standalone mobile application.

## 4. Project plan based on two weeks iteration - 
### Week 1-2: Work on understanding the existing pytorch model, how it is trained and how to deploy it.
### Week 3-4: We plan to convert the existing pytorch model to a model that our application can utilize.
### Week 5-6: We plan to build the main skeleton of the application using existing frameworks - we plan to focus most part of our time on how to utilize the converted model.
### Week 7-8: We plan to integrate the converted model into our application and test it.