updated README

README.md

@@ -7,5 +7,13 @@ dataset:
 - oxfort-iit pets
 license: apache-2.0
 ---
-## Image segmentation model on segmenting pets! 🐶 🐕 🐩 
-U-Net model on MobileNet weights, trained on Oxford-IIT Pets dataset.
+## Keras semantic segmentation models on the 🤗Hub! 🐶 🐕 🐩 
+
+Image classification task tells us about a class assigned to an image, and object detection task creates a boundary box on an object in an image. But what if we want to know about the shape of the image? Segmentation models helps us segment images and reveal their shapes. It has many variants. You can host your Keras segmentation models on the Hub.
+Semantic segmentation models classify pixels, meaning, they assign a class (can be cat or dog) to each pixel. The output of a model looks like following.
+![Raw Output](./raw_output.jpg)
+We need to get the best prediction for every pixel.
+![Mask](./mask.jpg)
+This is still not readable. We have to convert this into different binary masks for each class and convert to a readable format by converting each mask into base64. You can find the full implementation in pipeline.py.
+![Binary Mask](./binary_mask.jpg)
+