Image Captioning Software: Understanding and commercializing technology
Exploring Image Captioning Software, Technologies, and Commercial Opportunities
Images can tell thousands of stories so they are all blurred to an unthoughtful mind. What one needs in the present world is the message to be loud and clear. That is achieved with image captions. Why would one need the alt-texts, and tags otherwise?
Whether organizing images or explaining them, texts that explain those images better are invaluable to fulfill the purpose. When you have a lot of existing images on your website or post frequently, image captioning software is what saves you time and helps you get organized.
Underlying technologies behind image captioning software
The core principle still remains that of AI where multiple types of networks, data sets, training, and testing along with that of software development for development and deployment is used.
The most popular languages for building image captioning softwares still are Python for prototyping and early stages of releases, Java, C++ and GoLang and the most used networks are LSTM (long short term memory) and CNN (Convolution Neural Network).
Some of the popular Python libraries used for its easiness and for quick results are Keras, TensorFlow, scikit-image, OpenCV, Pillow etc. As image captioning softwares requires high computational power the server requirements for these are quite high, needless to say, they demand for stronger GPUs.
What can be built over the image captioning software?
Image captioning softwares can perform almost all types of text related operations with a minor tweak for customizations. But, even without the tweaks and simply with the output text generated, quite a few handy commercial products can be developed. Just a few examples can be:
Image text extractor
In order to create the image text extractor software, you will need to connect your image upload and output to the original engine of the image caption generator software. As the model of image captioning tools are already trained with a lot of image data set, they are well capable of recognizing the texts and are able to give you text extraction functionality. Handwriting recognition will need a collaboration with the original development team for more training of the model.
Social media image tagging
This idea is best to be implemented by a social media marketing agency and the likes of those. A software that allows to schedule social media posts can connect their platform with image captioning software. Providing auto-suggestions for image tags and image descriptions will improve the user experience.
Photos to video
Photos to videos software can be developed over the auto image caption generation software. A basic image to video generator software can even be developed in python. Check this out if you want to get your hands dirty: educative.io. But with connection with caption generation software and AI voice generators like Amazon Polly, your image to video generation tool can be a great commercial product.
Apart from the given examples, we are confident that you have other ideas for how to benefit from the auto-image caption generation softwares. And for most of those ideas, if you need API connection with the image/photo caption generator, which we have provided.
Now will you be kind enough to share it with us as well.
Oct 07, 2023
