问图像数据生成器.flow_from_directory(目录)统一/合并类

EN

# define the generator
datagen = ImageDataGenerator(...)

# assign class_mode to 'sparse' to make our work easier
gen = datagen.flow_from_directory(..., class_mode= 'sparse')

# define a mapping from old classes to new classes (i.e. 0,1 -> 0 and 2,3 -> 1)
old_to_new = np.array([0, 0, 1, 1])

# the wrapping generator
def new_gen(gen):
    for data, labels in gen:
        labels = old_to_new[labels]
        # now you can call np_utils.to_categorical method 
        # if you would like one-hot encoded labels
        yield data, labels

# ... define your model

# fit the model
model.fit(new_gen(gen), ...)