Face-mask-Segmentation

To build a Face Mask Segmentation model which includes building a face detector to locate the position of a face in an image.

Objective:

In this problem, we use "Transfer Learning" of an Image Segmentation model to detect any object according to the problem in hand. Here, we are particularly interested in segmenting faces in a given image Steps and Tasks: Load the dataset given in form .npy format.

We have already extracted the images from wider face-dataset and

added it in the file images.npy. You can directly use this file for this project.

“images.npy” contains details about the image and it’s masks, there

is no separate CSV file for that

There is no separate train and test data given

Create Features(images) and labels(mask) using that data.

Load the pre-trained model and weights.

Create a model using the above model.

Define the Dice Coefficient and Loss function.

Compile and fit the model.

Evaluate the model.