Datasets: downloading images for multiple classes

[cwerner (Christian Werner)]

I found that any unsupervised downloads from icrawler, google image search or other downloaders contain a lot of wrong and even corrupted images and I feared they’d mess up my classification…

So I always check them visually and mark any unsuitable ones for deletion…

I wrote a small python package for this task (auto-download based on csv file of search queries/ terms) and quickly clean via GUI script afterwards…

I linked it elsewhere in the forums:

Small tool to build image dataset: fastclass

Hi all. If anyone is in need for a small tool to simplify downloading and cleaning multi-class image datasets from Google, Bing and Baidu I recently created a python package called fastclass. You can get it from my GitHub: I also wrote a brief blog post about it here: https://www.christianwerner.net/tech/Build-your-image-dataset-faster You simply define a csv file with search terms for your classes and it’ll download, resize and de-duplicate them for you. Afterwards you can use a second …

I still takes a lot of time to weed through many-class-datasets, but you get some clean data (11 classes, approx. 8500 images downloaded and cleft after cleaning with the script).