Converting GDAL dataset into numpy array

Question

I am trying to do data augmentation on sentinel 2. Everything else is working and the only problem I have is the output I am getting is only one band when the input image has 10 bands. I also tried with rasterio but the results are still only one band.

Why am I only getting one band as output?

from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
# import io
from PIL import Image
from osgeo import gdal
import cv2
import rasterio
import numpy as np
from osgeo import gdal
datagen = ImageDataGenerator(
 rotation_range=180,
 width_shift_range=0,
 height_shift_range=0,
 shear_range=0,
 zoom_range=0.5,
 
 horizontal_flip=True,
 vertical_flip = True,
 fill_mode='nearest') #Also try nearest, constant, reflect, wrap
a = 1
while True:
 ds = gdal.Open("E:\\opencv\12円.tif")
 myarray = np.array(ds.ReadAsArray())
 ""Rasterio code"" 
 #fp = r'E:\\opencv\12円.tif'
 #img = rasterio.open(fp)
 #img = img.read()
 """"""
 x = img_to_array(myarray)
 x = x.reshape(x.shape + (1, )) 
 i = 1
 for batch in datagen.flow(x, batch_size=16, 
 save_to_dir='E:\\opencv\\', 
 save_prefix= a, 
 save_format='tif'):
 i += 1
 if i > 1:
 break 
 a += 1
 if a > 3:
 break

Answer 1

You will need to specify which band in the dataset you want to read as an array. I would also open your dataset outside of the while loop as this will prevent corruption

a = 1
ds = gdal.Open("E:\\opencv\12円.tif")
while True:
 band = ds.GetRasterBand(a)
 myarray = band.ReadAsArray()
 x = img_to_array(myarray)
 x = x.reshape(x.shape + (1, )) 
 i = 1
 for batch in datagen.flow(x, batch_size=16, 
 save_to_dir='E:\\opencv\\', 
 save_prefix= a, 
 save_format='tif'):
 i += 1
 if i > 1:
 break 
 a += 1
 if a > 12: #ensures you get all 12 bands
 break
del ds