I have two folders of hyperspectral data with five channels which are converted to numpy array. Each folder depicts the respective label.
dataset ----good_data ----good_image_01.npy ----good_image_02.npy ----bad_data ----bad_image_01.npy ----bad_image_02.npy
I have used keras image generator to feed the data to input pipeline previously with png images.
train_ds = tf.keras.preprocessing.image_dataset_from_directory( data_dir, validation_split=0.2, subset="training", seed=123, image_size=(img_height, img_width), batch_size=batch_size)
But I am not sure how to achieve the same with numpy dataset. can anyone help?