xuanhan863 / vqa_demo Goto Github PK

#VQA Demo

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.

1. Keras

   • Modular deep learning library based on python

2. Theano/Tensorflow

   • As backend for Keras, you may choose either one.
   • For the development of this project, I used Theano 0.8.0

3. scikit-learn

   • Quintessential machine library for python

4. Spacy

   • 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 :

78.32 % train 01.11 % truck 00.98 % passenger 00.95 % fire truck 00.68 % bus

##Runtime

• GPU (Titan X) Theano optimizer=fast_run : 117 seconds
• GPU (Titan X) Theano optimizer=fast_compile : 122 seconds
• CPU (i7-5820K CPU @ 3.30GHz : 160 seconds

##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