nanfengpo / VQA_Demo

Visual Question Answering Demo on pretrained model

VQA Demo

Updated to work with Keras 2.0 and TF 1.2 This is much slower than original because now it requires three numpy axis switches. This code is meant for education thus focus is on simplicity and not speed.

This is a simple Demo of Visual Question answering which uses pretrained models (see models/CNN and models/VQA) to answer a given question about the given image.

Dependency

1. Keras version 2.0.5

   • Modular deep learning library based on python

2. Tensorflow 1.2.0 (Might also work with Theano. I have not tested Theano after the recent commit, use commit 0f89007 for Theano)

3. scikit-learn

   • Quintessential machine library for python

4. Spacy version 0.100.6

   • Used to load Glove vectors (word2vec)
   • You may have to upgrade your Spacy to use Glove vectors (default is Goldberg Word2Vec)
   • To upgrade & install Glove Vectors
     • pip install --upgrade spacy
     • sputnik —name spacy install en
     • sputnik --name spacy install en_glove_cc_300_1m_vectors

5. OpenCV

   • OpenCV is used only to resize the image and change the color channels,
   • You may use other libraries as long as you can pass a 224x224 BGR Image (NOTE: BGR and not RGB)

6. VGG 16 Pretrained Weights

   • Please download the weights file vgg16_weights.h5

Usage

python demo.py -image_file_name path_to_file -question "Question to be asked"

e.g

python demo.py -image_file_name test.jpg -question "Is there a man in the picture?"

if you have prefer to use Theano backend and if you have GPU you may want to run like this

THEANO_FLAGS='floatX=float32,device=gpu0,lib.cnmem=1,mode=FAST_RUN' python demo.py -image_file_name test.jpg -question "What vechile is in the picture?"

Expected Output : 095.2 % train 00.67 % subway 00.54 % mcdonald's 00.38 % bus 00.33 % train station

Runtime

• GPU (Titan X) Theano optimizer=fast_run : 51.3 seconds
• GPU (Titan X) Theano optimizer=fast_compile : 47.5 seconds
• CPU (i7-5820K CPU @ 3.30GHz : 35.9 seconds (Is this strange or not ?)

iPython Notebook

Jupyter/iPython Notebook has been provided with more examples and interactive tutorial. https://github.com/iamaaditya/VQA_Demo/blob/master/Visual_Question_Answering_Demo_in_python_notebook.ipynb

NOTE: See the comments on demo.py for more information on the model and methods

VQA Training

• See the repo https://github.com/iamaaditya/VQA_Keras to learn how to train new models