I’m trying to use fast.ai for multi-label prediction from images using CNNs. The prediction task is essentially the same as in Lesson 3: Planet, but the dataset is my own and quite different.
I have a dataframe with filename and label information, and my folder with images.
I can load the images and do the train-validation split perfectly fine.
np.random.seed(42) data = ImageList.from_df(df, path=PNG_path, suffix=".png").split_by_rand_pct(0.25)
Then I try to add labels, which separated by a space in case there is more than one.
data = data.label_from_df(label_delim=' ')
However, this command does not work and gives the following error message: TypeError: init() got an unexpected keyword argument 'label_delim’
I have the same issue as here: https://forums.fast.ai/t/lesson-3-planet-label-delim-issue/36851. But I’m running version 1.0.59 on Google Colab, so updating should not be an issue.
Thanks for help. Here’s a screenshot of the whole thing: