forked from 626_privacy/tensorflow_privacy
38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
# Copyright 2020 Google LLC
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
# ==============================================================================
|
|
|
|
|
|
"""
|
|
Given the private images, draw them in a 100x100 grid for visualization.
|
|
"""
|
|
|
|
import numpy as np
|
|
from PIL import Image
|
|
import matplotlib.pyplot as plt
|
|
|
|
p = np.load("data/private.npy")
|
|
|
|
def toimg(x):
|
|
print(x.shape)
|
|
img = (x+1)*127.5
|
|
img = np.clip(img, 0, 255)
|
|
img = np.reshape(img, (10, 10, 32, 32, 3))
|
|
img = np.concatenate(img, axis=2)
|
|
img = np.concatenate(img, axis=0)
|
|
img = Image.fromarray(np.array(img,dtype=np.uint8))
|
|
return img
|
|
|
|
toimg(p).save("data/reconstructed.png")
|
|
|