How to Develop a Deep Learning Photo Caption Generator from Scratch
Last Updated on September 3, 2020
Develop a Deep Learning Model to Automatically
Describe Photographs in Python with Keras, Step-by-Step.
Caption generation is a challenging artificial intelligence problem where a textual description must be generated for a given photograph.
It requires both methods from computer vision to understand the content of the image and a language model from the field of natural language processing to turn the understanding of the image into words in the right order. Recently, deep learning methods have achieved state-of-the-art results on examples of this problem.
Deep learning methods have demonstrated state-of-the-art results on caption generation problems. What is most impressive about these methods is a single end-to-end model can be defined to predict a caption, given a photo, instead of requiring sophisticated data preparation or a pipeline of specifically designed models.
In this tutorial, you will discover how to develop a photo captioning deep learning model from scratch.
After completing this tutorial, you will know:
- How to prepare photo and text data for training a deep learning model.
- How to design and train a deep learning caption generation model.
- How to evaluate a train caption generation model and use it to caption entirely new
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