I am using a custom dataset with the following structure.
I got an error(Wrong Databunch composition) while creating the ImageDataBunch object with data blocks API.
As you might see in the image the test folder is also loaded in the training data set and is considered as a class.
This is an imagenet data structure, so ideally the images in test set should not go into the training dataset. Is this because of a library bug or am I missing something?
I tried inferencing using predict but since my test data set is very large, it takes a lot of time to run.
For anyone still facing this issue.
I found a work around to it.
data = (ImageItemList.from_folder(path/"train") # Where to find the data? -> in path and its subfolders
.random_split_by_pct() # How to split in train/valid? -> use the folders
.label_from_folder() #How to label? -> # depending on the folder of the filenames
.transform(get_transforms(),size=224) # Data augmentation? -> use tfms with a size of 64
This worked !! Thanks. @rishabh
@rishabh This is is not working for me. I am getting error . Please suggest how to fix the issue
TypeError: unsupported operand type(s) for /: ‘str’ and ‘str’
@ritika26 I guess your path variable is of string type rather than PosixPath object.
Also check if you have the same folder structure as shown in original post.