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baba-image-telling-for-blind's Projects

apple-vision-pro-ui-kit icon apple-vision-pro-ui-kit

Free UI asset kit you can use to prototype and test interactive interfaces in Apple Vision Pro’s design system. Compatible with any XR headset with pass-through mode, including Meta Quest and Meta Quest Pro.

apple-vision-pro-ui-kit-demo icon apple-vision-pro-ui-kit-demo

Preconfigured project to show the demo scene of the Apple Vision UI Kit package in XR. Project is set up to build for Oculus Quest 2 / Quest Pro headsets.

arkitscenes icon arkitscenes

This repo accompanies the research paper, ARKitScenes - A Diverse Real-World Dataset for 3D Indoor Scene Understanding Using Mobile RGB-D Data and contains the data, scripts to visualize and process assets, and training code described in our paper.

automatic-image-captioning-using-cnn-lstm-deep-neural-networks-and-flask icon automatic-image-captioning-using-cnn-lstm-deep-neural-networks-and-flask

Image caption generation has emerged as a challenging and important research area following ad-vances in statistical language modelling and image recognition. The generation of captions from images has various practical benefits, ranging from aiding the visually impaired, to enabling the automatic and cost-saving labelling of the millions of images uploaded to the Internet every day. The field also brings together state-of-the-art models in Natural Language Processing and Computer Vision, two of the major fields in Artificial Intelligence. In this model, we has used CNN and LSTM to generate captions for the images and deployed our model using Flask.

caption-it icon caption-it

Image Captioning Web Application with PyTorch and Flask - Implementation of "Show and Tell: A Neural Image Caption Generator"

catr icon catr

Image Captioning Using Transformer

dream-with-vision-pro icon dream-with-vision-pro

Text to 3D generation in Apple Vision Pro built with the VisionOS SDK. 3D Scribblenauts in AR for the Scale Generative AI Hackathon. Won Scale AI Prize

image-caption icon image-caption

Using LSTM and Transformer to solve Image Captioning in Pytorch

image-captioning-4 icon image-captioning-4

Implementation of 'X-Linear Attention Networks for Image Captioning' [CVPR 2020]

image-captioning-5 icon image-captioning-5

Computer Vision: Generate captions that describe the contents of images using PyTorch

image-captioning-7 icon image-captioning-7

Application that either reads frames fed by webcam and captions it, or reads images in a directory and recreates these images with added captions. Trained and used the model provided by: https://github.com/neural-nuts/image-caption-generator

image-captioning-9 icon image-captioning-9

Implementation of a Multimodal Neural Network for Image Captioning in Tensorflow.

image-captioning-scene-descriptor-star icon image-captioning-scene-descriptor-star

A CNN-LSTM model to generate a sentence which describes the contents/scene of an image and establishes a Spatial Relationship (position, activity etc.) among the entities

image-captioning-with-visual-attention icon image-captioning-with-visual-attention

To build networks capable of perceiving contextual subtleties in images, to relate observations to both the scene and the real world, and to output succinct and accurate image descriptions; all tasks that we as people can do almost effortlessly.

image_captioning icon image_captioning

Image Captioning on Flickr Dataset - Describe a scene (output text) from an input image

image_captioning-1 icon image_captioning-1

generate captions for images using a CNN-RNN model that is trained on the Microsoft Common Objects in COntext (MS COCO) dataset

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