We release our test MegaDepth dataset including 1600 pairs, can be downloaded here here.
Once it is downloaded, saved it into ../../data, the file structure should be :
./RANSAC-Flow/data/MegaDepth
├── MegaDepth_Train/
├── MegaDepth_Train_Org/
├── Val/
└── Test/
The RobotCar dataset can be downloaded from the Visual Localization Challenge (at the bottom of the site), or more precisely here.
This evaluation code takes the same structure as MegaDepth, which means you need to have a csv containing all the correspondences and the image paths. The file structure should be :
./RANSAC-Flow/data/RobotCar
├── img/
└── test6511.csv
The cvs file can be downloaded from here(~5G).
Running :
python evaluation.py --outDir MOCO_MegaDepth_WO_FT MegaDepthTo get results with our fine alignment :
python getResults.py --coarsePth MOCO_MegaDepth_WO_FT_Coarse --finePth MOCO_MegaDepth_WO_FT_Fine --dataset MegaDepth --multiH MegaDepthRunning :
python evaluation.py --outDir MOCO_MegaDepth_FT --resumePth ../../model/pretrained/MegaDepth_TestFT.pth MegaDepthTo get results with our fine alignment :
python getResults.py --coarsePth MOCO_MegaDepth_FT_Coarse --finePth MOCO_MegaDepth_FT_Fine --dataset MegaDepth --multiH MegaDepthRunning :
python evaluation.py --outDir MOCO_RobotCar_WO_FT RobotCarTo get results with our fine alignment :
python getResults.py --coarsePth MOCO_RobotCar_WO_FT_Coarse --finePth MOCO_RobotCar_WO_FT_Fine --multiH --dataset RobotCar RobotCarRunning :
python evaluation.py --outDir MOCO_RobotCar_FT --resumePth ../../model/pretrained/RobotCar_TestFT.pth RobotCarTo get results with our fine alignment :
python getResults.py --coarsePth MOCO_RobotCar_FT_Coarse --finePth MOCO_RobotCar_FT_Fine --multiH --dataset RobotCar RobotCarAdding --imageNet when running evaluation.py with the above commands.