Update README.md

README.md

@@ -11,6 +11,20 @@ widget:
   example_title: Cat in a Crate
 - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-3.jpg
   example_title: Two Cats Chilling
-license: apache-2.0
+license: cc0.0
 ---
-Keras image captioning model with encoder-decoder network. 🌃🌅🎑
+## Tensorflow Keras Implementation of an Image Captioning Model with encoder-decoder network. 🌃🌅🎑
+
+This repo contains the models and the notebook [on Image captioning with visual attention](https://www.tensorflow.org/tutorials/text/image_captioning?hl=en).
+
+Full credits to TensorFlow Team
+
+## Background Information
+This notebook implements TensorFlow Keras implementation on Image captioning with visual attention.
+Given an image like the example below, your goal is to generate a caption such as "a surfer riding on a wave".
+![image](https://www.tensorflow.org/images/surf.jpg)
+To accomplish this, you'll use an attention-based model, which enables us to see what parts of the image the model focuses on as it generates a caption.
+![attention](https://www.tensorflow.org/images/imcap_prediction.png)
+The model architecture is similar to [Show, Attend and Tell: Neural Image Caption Generation with Visual Attention](https://arxiv.org/abs/1502.03044).
+
+This notebook is an end-to-end example. When you run the notebook, it downloads the [MS-COCO](https://cocodataset.org/#home) dataset, preprocesses and caches a subset of images using Inception V3, trains an encoder-decoder model, and generates captions on new images using the trained model.