“Captioning images is difficult. But, our model does it easily with all relevancy.”
Let’s take an example of the below image where ‘A white dog is standing on green grasses’, which seems a caption for the image! A white dog in a grassy area; a white dog with brown spots; a dog on grass and some pink flowers, etc. are also relevant captions. But, which one is the best to use. This is quite problematic. Therefore, let’s use an image captioning tool to generate quick captions for any image.
“Input an image to produce a relevant caption as an output!”
In the Image Captioning Model,
One can understand the content of the image via NLP (Natural Language Processing) to get the right words in the right order according to the elements present in the image. For this, the model uses both Natural Language Processing (NLP) and Computer Vision to generate the captions. The dataset will be in the form [image to captions generation]. The dataset consists of input images and their corresponding output captions.
In the encoder, the input image is given to Convolutional Neural Network (CNN) to extract features. The decoder is a Recurrent Neural Network(RNN) that does language modeling up to the word level.
Automatically generating this textual description from an artificial system is the task of image captioning!
A Description that Tells Everything About Image
Such a tool describes in a single sentence what is shown in the image – the objects present, their properties, the actions being performed and the interaction between the objects, etc. This model was trained on the Imagenet dataset to perform image classification on 1000 different classes of images. However, our purpose here is not to classify the image but just to get a fixed-length informative vector for each image.
Do You Want to Use Image Captioning Tool?
If you want to understand how good the model is, let’s try to generate captions on images from the test dataset. The images used for testing were semantically related to those used for training the model. But, now you can get cations for any image!
Contact Us!How Image Captioning Tool Helps You?
For the likes of media and publishing companies, generating n number of content pieces each day, captioning images has been a manual effort so far. It takes significant effort when there is a high volume of images that are published online.
But, an Image Captioning tool reduces that load and makes it easy for companies to publish n number of images. With increasing awareness of accessibility and providing a better user experience, the tool can be used for both image captioning and generating alt text.
The tool generates image captions automatically judiciously using Artificial Intelligence and Neural Networks. Tags will enable users to identify the objects in the images and index them for any future use. Lastly, saves significant time and effort, reducing manual intervention.
"The tool identifies the image, pre-processes the data to give a caption."
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