Creating a Dataset from Google Image Search Results

If you wish to create an image classifier and want to use the data from Google Image Search results, and want to exclude some of the images, you can use this bookmarklet gi2ds (drag it to your bookmarks bar and click on it after your search). Then you can click on the images you want to exclude. A list is generated for you with all the relevant image-urls for you to process further.

gi2ds is intened to help you when creating an image dataset based on a google images query. It allows you to exclude images that are not relevant by toggling them on and off by clicking on them. Default is that all images are included. The urls are found in a popup down to the right. To get all available images you need to scroll all the way down for more images to load, also pressing the show more results button and continuing scrolling in order to get all the pictures available.

For more info, the code, see GitHub

Inspiration comes from this years fast.ai course (v3) where i am attending as an International Fellow. The course will be available to the public in January 2019

 

The new Fast.ai 2 Videos available

The Fast and the Furious 2 of machine learning is now available for your pleasure.

http://course.fast.ai/part2.html

Fast.ai is the very best way to learn practical Deep Learning. Period.

The first iteration of course 1 and 2, used Keras  and the new versions use their own library built on top of PyTorch. Their new library is awesome and has a lot of useful best practice functions.