TensorFlow Implementation of "Show, Attend and Tell"

Overview

Show, Attend and Tell

Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attention which introduces an attention based image caption generator. The model changes its attention to the relevant part of the image while it generates each word.


alt text


References

Author's theano code: https://github.com/kelvinxu/arctic-captions

Another tensorflow implementation: https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow


Getting Started

Prerequisites

First, clone this repo and pycocoevalcap in same directory.

$ git clone https://github.com/yunjey/show-attend-and-tell-tensorflow.git
$ git clone https://github.com/tylin/coco-caption.git

This code is written in Python2.7 and requires TensorFlow 1.2. In addition, you need to install a few more packages to process MSCOCO data set. I have provided a script to download the MSCOCO image dataset and VGGNet19 model. Downloading the data may take several hours depending on the network speed. Run commands below then the images will be downloaded in image/ directory and VGGNet19 model will be downloaded in data/ directory.

$ cd show-attend-and-tell-tensorflow
$ pip install -r requirements.txt
$ chmod +x ./download.sh
$ ./download.sh

For feeding the image to the VGGNet, you should resize the MSCOCO image dataset to the fixed size of 224x224. Run command below then resized images will be stored in image/train2014_resized/ and image/val2014_resized/ directory.

$ python resize.py

Before training the model, you have to preprocess the MSCOCO caption dataset. To generate caption dataset and image feature vectors, run command below.

$ python prepro.py

Train the model

To train the image captioning model, run command below.

$ python train.py

(optional) Tensorboard visualization

I have provided a tensorboard visualization for real-time debugging. Open the new terminal, run command below and open http://localhost:6005/ into your web browser.

$ tensorboard --logdir='./log' --port=6005 

Evaluate the model

To generate captions, visualize attention weights and evaluate the model, please see evaluate_model.ipynb.


Results


Training data

(1) Generated caption: A plane flying in the sky with a landing gear down.

alt text

(2) Generated caption: A giraffe and two zebra standing in the field.

alt text

Validation data

(1) Generated caption: A large elephant standing in a dry grass field.

alt text

(2) Generated caption: A baby elephant standing on top of a dirt field.

alt text

Test data

(1) Generated caption: A plane flying over a body of water.

alt text

(2) Generated caption: A zebra standing in the grass near a tree.

alt text

Owner
Yunjey Choi
Yunjey Choi
Implementation for Simple Spectral Graph Convolution in ICLR 2021

Simple Spectral Graph Convolutional Overview This repo contains an example implementation of the Simple Spectral Graph Convolutional (S^2GC) model. Th

allenhaozhu 64 Dec 31, 2022
Generative Modelling of BRDF Textures from Flash Images [SIGGRAPH Asia, 2021]

Neural Material Official code repository for the paper: Generative Modelling of BRDF Textures from Flash Images [SIGGRAPH Asia, 2021] Henzler, Deschai

Philipp Henzler 80 Dec 20, 2022
High performance distributed framework for training deep learning recommendation models based on PyTorch.

High performance distributed framework for training deep learning recommendation models based on PyTorch.

340 Dec 30, 2022
Dataset and codebase for NeurIPS 2021 paper: Exploring Forensic Dental Identification with Deep Learning

Repository under construction. Example dataset, checkpoints, and training/testing scripts will be avaible soon! 💡 Collated best practices from most p

4 Jun 26, 2022
Zero-Cost Proxies for Lightweight NAS

Zero-Cost-NAS Companion code for the ICLR2021 paper: Zero-Cost Proxies for Lightweight NAS tl;dr A single minibatch of data is used to score neural ne

SamsungLabs 108 Dec 20, 2022
Official implementation of "Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform", ICCV 2021

Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform This repository is the implementation of "Variable-Rate Deep Image C

Myungseo Song 47 Dec 13, 2022
Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer.

DocEnTR Description Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer. This model is implemented on to

Mohamed Ali Souibgui 74 Jan 07, 2023
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning

Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning This is the official repository of "Camera Distortion-

Hanbyel Cho 12 Oct 06, 2022
Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”

VectorNet Re-implementation This is the unofficial pytorch implementation of CVPR2020 paper "VectorNet: Encoding HD Maps and Agent Dynamics from Vecto

120 Jan 06, 2023
A platform to display the carbon neutralization information for researchers, decision-makers, and other participants in the community.

Welcome to Carbon Insight Carbon Insight is a platform aiming to display the carbon neutralization roadmap for researchers, decision-makers, and other

Microsoft 14 Oct 24, 2022
Data manipulation and transformation for audio signal processing, powered by PyTorch

torchaudio: an audio library for PyTorch The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the

1.9k Dec 28, 2022
Code and real data for the paper "Counterfactual Temporal Point Processes", available at arXiv.

counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code

Networks Learning 11 Dec 09, 2022
EdiBERT, a generative model for image editing

EdiBERT, a generative model for image editing EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation. The

16 Dec 07, 2022
Sign Language is detected in realtime using video sequences. Our approach involves MediaPipe Holistic for keypoints extraction and LSTM Model for prediction.

RealTime Sign Language Detection using Action Recognition Approach Real-Time Sign Language is commonly predicted using models whose architecture consi

Rishikesh S 15 Aug 20, 2022
A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform

FedML-AI 175 Dec 01, 2022
Python with OpenCV - MediaPip Framework Hand Detection

Python HandDetection Python with OpenCV - MediaPip Framework Hand Detection Explore the docs » Contact Me About The Project It is a Computer vision pa

2 Jan 07, 2022
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)

Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations The code of: Weakly Supervised Learning of Instance Segmentation with I

Jiwoon Ahn 472 Dec 29, 2022
This project aims to be a handler for input creation and running of multiple RICEWQ simulations.

What is autoRICEWQ? This project aims to be a handler for input creation and running of multiple RICEWQ simulations. What is RICEWQ? From the descript

Yass Fuentes 1 Feb 01, 2022
3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans.

3DMV 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 p

Владислав Молодцов 0 Feb 06, 2022
The official implementation of the Hybrid Self-Attention NEAT algorithm

PUREPLES - Pure Python Library for ES-HyperNEAT About This is a library of evolutionary algorithms with a focus on neuroevolution, implemented in pure

Adrian Westh 91 Dec 12, 2022