forked from shibing624/python-tutorial
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathrocket_demo.py
More file actions
39 lines (33 loc) · 1.3 KB
/
rocket_demo.py
File metadata and controls
39 lines (33 loc) · 1.3 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
# -*- coding: utf-8 -*-
"""
@author:XuMing（[email protected])
@description:
"""
import base64
import os
import time
import numpy as np
import tensorflow as tf
from keras.layers import Conv2D, UpSampling2D, InputLayer
from keras.models import Sequential
from keras.preprocessing.image import img_to_array, load_img
from skimage.color import rgb2lab, lab2rgb
from skimage.io import imsave
def build_model():
model = Sequential()
model.add(InputLayer(input_shape=(None, None, 1)))
model.add(Conv2D(8, (3, 3), activation='relu', padding='same', strides=2))
model.add(Conv2D(8, (3, 3), activation='relu', padding='same'))
model.add(Conv2D(16, (3, 3), activation='relu', padding='same'))
model.add(Conv2D(16, (3, 3), activation='relu', padding='same', strides=2))
model.add(Conv2D(32, (3, 3), activation='relu', padding='same'))
model.add(Conv2D(32, (3, 3), activation='relu', padding='same', strides=2))
model.add(UpSampling2D((2, 2)))
model.add(Conv2D(32, (3, 3), activation='relu', padding='same'))
model.add(UpSampling2D((2, 2)))
model.add(Conv2D(16, (3, 3), activation='relu', padding='same'))
model.add(UpSampling2D((2, 2)))
model.add(Conv2D(2, (3, 3), activation='tanh', padding='same'))
model.compile(optimizer='adam', loss='mse')
return model
build_model()