Image-Captioning

Image captioning using a CNN and RNN

Instructions

1. Clone this repo: https://github.com/cocodataset/cocoapi

   git clone https://github.com/cocodataset/cocoapi.git
   

2. Setup the coco API (also described in the readme here)

      cd cocoapi/PythonAPI  
      make 
      cd ..
   

3. Download some specific data from here: http://cocodataset.org/#download (described below)

   Under Annotations, download:

   2014 Train/Val annotations [241MB] (extract captions_train2014.json and captions_val2014.json, and place at locations
   cocoapi/annotations/captions_train2014.json and cocoapi/annotations/captions_val2014.json, respectively)

   2014 Testing Image info [1MB] (extract image_info_test2014.json and place at location cocoapi/annotations/image_info_test2014.json) Under Images, download:

   2014 Train images [83K/13GB] (extract the train2014 folder and place at location cocoapi/images/train2014/)

   2014 Val images [41K/6GB] (extract the val2014 folder and place at location cocoapi/images/val2014/)

   2014 Test images [41K/6GB] (extract the test2014 folder and place at location cocoapi/images/test2014/)

The project is structured as a series of Jupyter notebooks that are designed to be completed in sequential order (0_Dataset.ipynb, 1_Preliminaries.ipynb, 2_Training.ipynb, 3_Inference.ipynb).