Drone-view building identification by cross-view Triplet deep neural network and relative spatial estimation
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poi
README.md
data.py
extract_fasterbb.py
extract_triplet.py
extract_triplet_cross.py
location.txt
model.py
renderhtml.py
retrieval.py
similarity.py
train.py
train_cross.py

README.md

drone_view_building_identification

Drone-view building identification by cross-view Triplet deep neural network and relative spatial estimation

Demo video: https://www.youtube.com/watch?v=sdq31ep2zYk

  1. Environment: tensorflow 0.10.0 numpy 1.11.0 python 2.7

  2. Run code:

train triplet: python train_cross.py --model_dir model/ig_21.61 (fine-tuned from --model_dir model_dir09el/ig_21.61)

extract deep features: python extract_triplet_cross.py --model_dir model/weatherB_best (extract fc features by model/weatherB_best )

retrieval: python retrieval.py --f frame/all
(retrieval in frame/all)

similarity.py: compute similiarty

  1. Dataset (will release after paper acceptance)

(1) Drone-BR 80 drone-view images: frame/all/ Sensor information per image: location.txt Building information frome Google Place API per image: poi/[name].txt

Building information from Web: a. ground-level image: search/ b. street-view image: streetview_clean/ c. aerial image: aerial_clean/

(2) Drone-BD bounding box per image: Drone-BD/[name].txt

(3) IG-City8 same buildings are in same directory

Download model: https://www.dropbox.com/sh/t8q70qnz9njtytq/AAAE2Hbw159p7Dj86QL2Z9hia