Places2-Arranger

Python code for re-arranging Places2-large dataset.
Places2 (http://places2.csail.mit.edu/download.html) provides high-resolution images which is not arranged to be used to in Pytorch data loader. This repo provides codes for re-arranging high-resolution Places2 dataset for Pytorch data loader.

Usage

Requirements

1. Download Places2-large train dataset from http://data.csail.mit.edu/places/places365/train_large_places365standard.tar
2. Download Places2-large valiation dataset from http://data.csail.mit.edu/places/places365/val_large.tar
3. Untar two downloaded files to one directory. (~/Places2/ in this example)

tar -C /YOUR_PATH/Places2/ -xvf train_large_places365standard.tar
tar -C /YOUR_PATH/Places2/ -xvf val_large.tar

4. Download and save this repo's codes in the same directory. Then, ~/Places2/ directory has followings: data_large, val_large, arrange_train.py, arrange_val.py, val.txt.

Use terminal to execute arrange_train.py and arrange_val.py.

python arrange_train.py
python arrange_val.py

Check Number of Total Files

Before run the arranger script, the number of training files is,

/Places2/data_large$ find . -type f | wc -l
1803460

And validation files,

/val_large$ find . -type f | wc -l
36500

After runing the arranger, the number of files for both train and valiation are same as before.

Tested Environments

Ubuntu 16.04 and Ubuntu 18.04
python 3.6 and python 3.7

To Do

Elabarate codes.