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Hi All,

There is a nice python package google-images-download, that will download images given one or more search terms.

In a python code recipe I have

import dataiku, os.path

from google_images_download import google_images_download   
response = google_images_download.googleimagesdownload()   

handle = dataiku.Folder("peugeots")
path = handle.get_path()

arguments = {
    "keywords":"peugeot 206,peugeot 306",
    "output_directory": path
}   #creating list of arguments


Now this works, but the thing is: the images are separated into subfolders of the managed folder, and if I then want to apply the deeplearning plugin, for image classification, with an input folder that contains sub folders it does not work.



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This is not currently supported. After the download loop in your downloading recipe, you could add Python code that flattens everything at top-level of the directory.
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OK, thanks for the tip.

The reason to keep it separated though is because these subfolders already form the two (or more) categories for which to retrain a pretrained network.
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