make following directories

• DeepPano/data/
• DeepPano/data/metadata/
• DeepPano/data/rawdata/
• DeepPano/data/rawdata/panoImg: original panorama images
• DeepPano/data/rawdata/psdFile: annotation files
• DeepPano/data/rawdata/xmlFile: PanoSeg or box information
• DeepPano/result/
• DeepPano/result/checkpoint: for postprocess

it iterates DeepPano/data/rawdata/panoImg files to generate FirstFile for all panorama images

and generate DeepPano/data/metadata/SemiSet.csv

it iterates DeepPano/data/rawdata/psdFile files to generate FirstFile for all annotated panorama images

and generate DeepPano/data/metadata/DataSet.csv

or you can use your own .csv file that has Image.Title, Pano.File, Xml.File, Annot.File, Train.Val columns

This generates image patches in DeepPano/data/metadata/(firstfile name)/

and metadata of DeepPano/data/metadata/(firstfile name)-10.csv

To use this dataset for training, you need to make DeepPano/data/StatDataset.csv

It generates pano/box mean/std stat for the dataset

put checkpoint under DeepPano/result/checkpoint/(directory name)/checkpoint/

and config file(.json) used to train that checkpoint at DeepPano/result/checkpoint/(directory name)/

SecondFile.csv and its Dataset, and its panoImgs should also be prepared

This iterates all folders in DeepPano/result/checkpoint/ and generate result for all image patches in SecondFile.csv

This iterates all checkpoints in checkpoint directory and generate result for all image patches in SecondFile.csv