Now it's time to load the train and validation datasets. Pick the right folders, as well as the right target$\_$size of the images $($it needs to match the height and width input of the model you've created$).$ If you'd like a reference, you can check out notebook $05$b$.$

# load and iterate training dataset

train$\_$it $=$ datagen.flow$\_$from$\_$directory$(\text{'}$data$/$fruits$\text{'},$

target$\_$size$=(224,224),$

color$\_$mode$=\text{'}$rgb$\text{'},$

class$\_$mode$=$"categorical"$)$

# load and iterate validation dataset

valid$\_$it $=$ datagen.flow$\_$from$\_$directory$(\text{'}$data$/$fruits$\text{'},$

target$\_$size$=(224,224),$

color$\_$mode$=\text{'}$rgb$\text{'},$

class$\_$mode$=$"categorical"$)$

Found $1511$ images belonging to $2$ classes.

Found $1511$ images belonging to $2$ classes.