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- Edit the file
utils/params.py
so thatparams['root']
points to the directory where you have the datasetTerrassaBuildings900
and where you would like to store all the intermediate files. - Run
utils/params.py
. Notice that this will create directories as well, so make sure you did the previous step ! - Run
build_database.py
to generate text files with image IDs for both the training and validation sets. - Run
get_features.py
to generate random features for both training and validation sets and store them independently in dictionaries. - Run
classify.py
andrank.py
to generate results - Run
eval_classification.py
andeval_ranking.py
to evaluate the results. For a better analysis of the results, take a look atnotebooks/gdsa_s4.ipynb
.
Team | mAP (retrieval) | mAP (classification) |
---|---|---|
Building Recognizer | TBD | TBD |
RdE | TBD | TBD |
What a building ! | TBD | TBD |
Discover Terrassa | TBD | TBD |
Egara View | TBD | TBD |
International Team | TBD | TBD |