Prepare one python notebook to build, train and evaluate model (TensorFlow or TensorFlow.Keras library recommended) on the da

Image Captioning ( Use Python Jupyter Notebook )


Prepare one python notebook to build, train and evaluate model (TensorFlow or TensorFlow.Keras library recommended) on the datasets given below.

Image Captioning is the process of generating textual description of an image. It uses both Natural Language Processing and Computer Vision to generate the captions. The dataset will be in the form [image → captions]. The dataset consists of input images and their corresponding output captions.

Data Processing


Read the pickle file ( and convert the data into the correct format which could be used for ML model. 

Pickle file contains the image id and the text associated with the image.

Eg: '319847657_2c40e14113.jpg#0tA girl in a purple shirt hold a pillow .

Each image can have multiple captions.

319847657_2c40e14113.jpg -> image name

#0 -> Caption ID

t  -> separator between Image name and Image Caption

A girl in a purple shirt hold a pillow . -> Image Caption

Corresponding image wrt image name can be found in the image dataset folder.

Image dataset Folder :

Plot at least two samples and their captions (use matplotlib/seaborn/any other library). 

Bring the train and test data in the required format. 

Model Building


Use Pretrained Resnet-50 model trained on ImageNet dataset (available publicly on google) for image feature extraction.

Create 5 layered LSTM layer model and other relevant layers for image caption generation.

Add L1 regularization to all the LSTM layers. 

Add one layer of dropout at the appropriate position and give reasons. 

Choose the appropriate activation function for all the layers. 

Print the model summary. 

Model Compilation


Compile the model with the appropriate loss function. 

Use an appropriate optimizer. Give reasons for the choice of learning rate and its value.

Model Training


Train the model for an appropriate number of epochs. Print the train and validation loss for each epoch. Use the appropriate batch size. 

Plot the loss and accuracy history graphs for both train and validation set. Print the total time taken for training. 

Model Evaluation


Take a random image from google and generate caption for that image.

Our website has a team of professional writers who can help you write any of your homework. They will write your papers from scratch. We also have a team of editors just to make sure all papers are of HIGH QUALITY & PLAGIARISM FREE. To make an Order you only need to click Ask A Question and we will direct you to our Order Page at WriteDemy. Then fill Our Order Form with all your assignment instructions. Select your deadline and pay for your paper. You will get it few hours before your set deadline.

Fill in all the assignment paper details that are required in the order form with the standard information being the page count, deadline, academic level and type of paper. It is advisable to have this information at hand so that you can quickly fill in the necessary information needed in the form for the essay writer to be immediately assigned to your writing project. Make payment for the custom essay order to enable us to assign a suitable writer to your order. Payments are made through Paypal on a secured billing page. Finally, sit back and relax.

Do you need an answer to this or any other questions?