To illustrate DELF usage, please download the Oxford buildings dataset. To
follow these instructions closely, please download the dataset to the
tensorflow/models/research/delf/delf/python/examples
directory, as in the
following commands:
# From tensorflow/models/research/delf/delf/python/examples/
mkdir data && cd data
wget http://www.robots.ox.ac.uk/~vgg/data/oxbuildings/oxbuild_images.tgz
mkdir oxford5k_images oxford5k_features
tar -xvzf oxbuild_images.tgz -C oxford5k_images/
cd ../
echo data/oxford5k_images/hertford_000056.jpg >> list_images.txt
echo data/oxford5k_images/oxford_000317.jpg >> list_images.txt
Also, you will need to download the trained DELF model:
# From tensorflow/models/research/delf/delf/python/examples/
mkdir parameters && cd parameters
wget http://download.tensorflow.org/models/delf_v1_20171026.tar.gz
tar -xvzf delf_v1_20171026.tar.gz
Now that you have everything in place, running this command should extract DELF
features for the images hertford_000056.jpg
and oxford_000317.jpg
:
# From tensorflow/models/research/delf/delf/python/examples/
python extract_features.py \
--config_path delf_config_example.pbtxt \
--list_images_path list_images.txt \
--output_dir data/oxford5k_features
After feature extraction, run this command to perform feature matching between
the images hertford_000056.jpg
and oxford_000317.jpg
:
python match_images.py \
--image_1_path data/oxford5k_images/hertford_000056.jpg \
--image_2_path data/oxford5k_images/oxford_000317.jpg \
--features_1_path data/oxford5k_features/hertford_000056.delf \
--features_2_path data/oxford5k_features/oxford_000317.delf \
--output_image matched_images.png
The image matched_images.png
is generated and should look similar to this one:
matplotlib
may complain with a message such as no display name and no $DISPLAY environment variable
. To fix this, one option is add the line
backend : Agg
to the file config/matplotlib/matplotlibrc
. On this problem,
see the discussion
here.