Neural Image Retrival

Evaluation

The script test_dir.py can be used to evaluate the pre-trained models provided and to reproduce the results above:

python -m dirtorch.test_dir --dataset DATASET --checkpoint PATH_TO_MODEL \
		[--whiten DATASET] [--whitenp POWER] [--aqe ALPHA-QEXP] \
		[--trfs TRANSFORMS] [--gpu ID] [...]

• --dataset: selects the dataset (eg.: Oxford5K, Paris6K, ROxford5K, RParis6K) [required]
• --checkpoint: path to the model weights [required]
• --whiten: applies whitening to the output features [default 'Landmarks_clean']
• --whitenp: whitening power [default: 0.25]
• --aqe: alpha-query expansion parameters [default: None]
• --trfs: input image transformations (can be used to apply multi-scale) [default: None]
• --gpu: selects the GPU ID (-1 selects the CPU)

cd $DIR_ROOT
export DB_ROOT=/PATH/TO/YOUR/DATASETS

python -m dirtorch.test_dir --dataset RParis6K \
		--checkpoint dirtorch/data/Resnet101-AP-GeM.pt \
		--whiten Landmarks_clean --whitenp 0.25 --gpu 0

And you should see the following output:

>> Evaluation...
 * mAP-easy = 0.907568
 * mAP-medium = 0.803098
 * mAP-hard = 0.608556

Note: this script integrates an automatic downloader for the Oxford5K, Paris6K, ROxford5K, and RParis6K datasets (kudos to Filip Radenovic ;)). The datasets will be saved in $DB_ROOT.

Feature extraction with kapture datasets

It contains conversion tools for popular formats and several popular datasets are directly available in kapture.

It can be installed with:

pip install kapture

Datasets can be downloaded with:

kapture_download_dataset.py update
kapture_download_dataset.py list
# e.g.: install mapping and query of Extended-CMU-Seasons_slice22
kapture_download_dataset.py install "Extended-CMU-Seasons_slice22_*"

If you want to convert your own dataset into kapture, please find some examples here.

Once installed, you can extract global features for your kapture dataset with:

cd $DIR_ROOT
python -m dirtorch.extract_kapture --kapture-root pathto/yourkapturedataset --checkpoint dirtorch/data/Resnet101-AP-GeM-LM18.pt --gpu 0

Run python -m dirtorch.extract_kapture --help for more information on the extraction parameters.