Show And Tell Keras Implementation

Keras implementation of Neural Image Caption Generator(NIC)

Related paper : Vinyals, Oriol, et al. “Show and tell: A neural image caption generator.” computer vision and pattern recognition (2015): 3156-3164.

Trained on: Flickr8k

Inspired by :

• How to Develop a Deep Learning Photo Caption Generator from Scratch
• Where to put the Image in an Image Caption Generator

Environment and Dependency

Code works well under these settings(Maybe also works well for other settings):

• python 3.6.8

• keras 2.2.4 tensorflow backend

• numpy 1.15.4

• nltk 3.4

• PIL 5.4.1

• tensorflow 1.12.0 (Only use to define the TensorBoardCaption to monitor the captions genrated during the training by tensorboard, if you don’t need it is ok to bypass tensorflow module)

Model Architecture

Model weights

• current_best.h5: current best model weights. Put it in the ./model-params

• features_dict.pkl: all filckr8k image features extracted by Inception_v3. Put it in the ./datasets

• Here to Download, Google Drive

Performance

(Use beam search size=5)

Evaluation by evaluate.py

BLEU-1 0.608
BLEU-2 0.419
BLEU-3 0.272
BLEU-4 0.184

Evaluation by pycocoevalcap

CIDEr: 0.532
Bleu_4: 0.210
Bleu_3: 0.305
Bleu_2: 0.442
Bleu_1: 0.625
ROUGE_L: 0.460

METEOR: 0.202
SPICE: 0.144

Examples:

• Use NIC Interactive.ipynb to visualize and generate captions of specific images(Images in folder ‘./put-your-image-here’)
  

TensorBoardCaption

• A keras callback function to monitor small amount of images’ current caption during training by tensorboard