Capter 6 - File not found in training, but file is in validation dir

Hello Fastai crew!

First post here…
Context - notebook 06 - multicat

Created a dataset consisting of one csv, plus train and validate folders with their respective pictures.

The csv file I created has the same format as in the exercise. However, when I train via learn.fine_tune(), the error message FileNotFoundError: [Errno 2] No such file or directory: '/content/gdrive/MyDrive/dest/dataset11/**train**/a-020_label_85.jpg
However, this file is in reality in the validation set.

Code for the data loaders:
dblock = DataBlock(blocks=(ImageBlock, MultiCategoryBlock),
item_tfms = RandomResizedCrop(128, min_scale=0.35))

dls = dblock.dataloaders(df)

And the other relevant functions:
def get_x( r ): return path/'train'/r['fname']
def get_y( r ): return r['labels'].split(' ')

`def splitter(df):`
    `train = df.index[df['is_valid'] == 0].tolist()`
    `valid = df.index[df['is_valid'] == 1].tolist()`
    `return train,valid`

Can you share some insight as to what might be causing the confusion between training and validation sets?

thanks in advance!

In the muticat notebook, for the PASCAL_2007 dataset, the folders are structured like so:


And for setting up the DataBlock, we used everything in the train/ folder and split the data set based on the accompanying train.csv file’s is_valid column. In your case though, you have two separate folders for train and valid. Therefore get_x() has to be updated somehow to return the full path, including the subdirectory path. Maybe you can prepend to fname in train.csv, the parent directory with awk or apply and try my previous answer.

Maybe something like this

p = lambda x: path/'valid/' if x else path/'train/'
df['fname_full'] = df['is_valid'].apply(p)/df['fname']

Now the column fname_full has the full path to the file.

Previous answer

I’m not sure, but with what you have provided, it looks like you want to return return r['fname'] in get_x(r) instead.

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Thanks @thatgeeman, that was it… I thought there were train/ valid/ test/ directories, rather than just train/ test/.
Therefore, I see I have two options
a) leave my df as is fine, and copy the iimage files from valid/ into train/ and use the original code, or
b) change the df as you suggest, and keep the folders as is.

Thanks for the great in-depth answer!

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