sample code

gistfile1.txt

# Bird
!wget -O /tmp/test.jpg https://upload.wikimedia.org/wikipedia/commons/1/17/Rotkehlchen_bird.jpg
file_name = '/tmp/test.jpg'
from IPython.display import Image
Image(file_name)

# resize and padding
from matplotlib.pyplot import imshow
from PIL import Image
import numpy as np

%matplotlib inline

desired_size = 32
im = Image.open(file_name)
old_size = im.size

ratio = float(desired_size)/max(old_size)
new_size = tuple([int(x*ratio) for x in old_size])

new_size

im = im.resize(new_size, Image.ANTIALIAS)
np_im = np.array(im)
np_im.shape

new_im = Image.new("RGB", (desired_size, desired_size))
new_im.paste(im, ((desired_size-new_size[0])//2,
                    (desired_size-new_size[1])//2))

np_new_im = np.array(new_im)
np_new_im.shape

imshow(np_new_im)


# reshape
np_new_im = np_new_im[np.newaxis, ...]
np_new_im.shape

# response 
response = predictor.predict({'inputs_input': np_new_im})
response


# use other people's predictor
import json
from sagemaker.tensorflow import TensorFlowPredictor
predictor = TensorFlowPredictor('sagemaker-tensorflow-2019-07-17-03-09-42-707')
result = predictor.predict({'inputs_input': np_new_im})