https://github.com/bhargav-joshi/img-caption-generator
Automatically creating the description or caption of an image using any natural language sentences is a very challenging task. 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. In addition to that we have discussed how this model can be implemented on web and will be accessible for end user as well.
https://github.com/bhargav-joshi/img-caption-generator
flask jupyter-notebook keras machine-learning nlp nltk numpy pandas python tensorflow
Last synced: 3 months ago
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Automatically creating the description or caption of an image using any natural language sentences is a very challenging task. 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. In addition to that we have discussed how this model can be implemented on web and will be accessible for end user as well.
- Host: GitHub
- URL: https://github.com/bhargav-joshi/img-caption-generator
- Owner: bhargav-joshi
- Created: 2022-05-01T11:17:36.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-06-03T05:30:49.000Z (about 4 years ago)
- Last Synced: 2025-02-14T22:39:45.047Z (over 1 year ago)
- Topics: flask, jupyter-notebook, keras, machine-learning, nlp, nltk, numpy, pandas, python, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 71.5 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Image Caption Generator
## Introduction
In the past few years, computer vision in image processing area has made significant
progress, like image classification and object detection. Benefiting from the advances of image
classification and object detection, it becomes possible to automatically generate one or more
sentences to understand the visual content of an image, which is the problem known as Image
Captioning. Generating complete and natural image descriptions automatically has large
potential effects, such as titles attached to news images, descriptions associated with medical
images, text-based image retrieval, information accessed for blind users, human-robot
interaction. These applications in image captioning have important theoretical and practical
research value.
Image captioning is a more complicated but meaningful task in the age of artificial
intelligence. Given a new image, an image captioning algorithm should output a description
about this image at a semantic level. In this an Image caption generator, Basis on our provided
or uploaded image file It will generate the caption from trained model which is trained using
algorithms and on large dataset. The main idea behind this is that users will get automated
captions when we use or implement it on social media or on any applications.
