Image Caption Generator Using CNN And LSTM

Image Caption has grown in importance in the digital age.Aside from that,there are built-in programs that produce and deliver the caption for a particular picture using deep neural network models.Picture captioning is the procedure of creating a description of an image.It requires a knowledge of the image’s key elements and feature extraction as well as the connections between them.It creates statements that are both grammatically and semantically accurate.In this research,we introduce a computer vision and machine translation-based deep learning model for describing pictures and creating descriptions for them.The goal of this study is to identify several things in a picture,recognize the links between those objects,and provide a caption for each of them.An ML approach called Transfer Learning will be employed with the aid of the Xception model to show the planned experiment using CNN and LSTM to identify the caption of the image.To develop models that can automatically create captions for images,vast datasets and plenty of processing capacity are useful.These are the features that will be included in our Python-based application.Image caption generators may also be utilized for video frames,which is consistent with the premise that consumers would get automatic captions when we use or deploy them on social media or other apps.They’ll be able to do the work of a human interpreter in a matter of minutes.Then there’s the fact that technology has the potential to aid visually impaired individuals tremendously.