This software was written to convert the FlickrLogos-47 dataset to make it usable in CNNs.
The files provided are:
- create_dataset.py
- create_lmdb.py
- divide_by_classes.py
- utilities.py
- create_dataset.ini
Settings file: is generated automatically if missing. caffe_root and flickrlogos_path have to be adjusted to suit your setup.
| flag | default | explanation |
|---|---|---|
| caffe_root | ../../caffe/ | path to root folder of compiled caffe framework |
| flickrlogos_path | ../../flickrlogos/ | path to root of flickrlogos-47 dataset |
| result_path | result_set | output folder; will be created |
| ignore_difficult | True | snippets marked as 'difficult' are ignored if True |
| ignore_truncated | False | snippets marked as 'truncated' are ignored if True |
| size_threshold | 20 | snippets with height + width <= 20 will be ignored |
Creates 2 test and train datasets, with image sizes 256x256 and 64x64, suited for CNN classification.
This script reads the images from the flickrlogos-47 dataset, crops out snippets according to the bounding boxes provided in the dataset's *.gt_data.txt files. Snippets marked as 'difficult' or 'truncated' will be ignored depending on the create_dataset.ini. Snippets with height + width <= size_threshold will be ignored as well.
These snippets will then be scaled with the longer side matching 256 / 64 pixels and filled with black to reach 256x256 / 64x64
Calls the caffe tool caffe/build/tools/convert_imageset to turn the datasets created with create_dataset.py into lmdb databases.
#divide_by_classes.py
Copies the images from result_set/256/test/ (created by create_dataset.py) into folders corresponding to their classification class.
Functions and classes needed for the other scripts.