from nets.unet import mobilenet_unet model = mobilenet_unet(32, input_height=256, input_width=192) model.summary() # from nets.uunet import get_unet # model = get_unet(4,256,256) # model.summary() # # # from nets.unet1 import mobilenet_unet # model = mobilenet_unet(2,48,48) # model.summary()
import numpy as np
import random
import copy
import os
import cv2
random.seed(0)
class_colors = [[0, 0, 0], [255, 0, 0], [255, 255, 0], [0, 255, 0],
[0, 255, 255], [255, 255, 255], [255, 0, 255], [0, 0, 255],
[0, 100, 200], [200, 100, 0]]
NCLASSES = 10
HEIGHT = 256
WIDTH = 256
model = mobilenet_unet(n_classes=NCLASSES,
input_height=HEIGHT,
input_width=WIDTH)
model.load_weights("logs/last1.h5")
imgs = os.listdir("./img")
for jpg in imgs:
image = cv2.imread('./img/' + jpg)
cv2.imwrite('./img/' + jpg[:-4] + '.png', image)
img = Image.open("./img/" + jpg[:-4] + '.png')
old_img = copy.deepcopy(img)
orininal_h = np.array(img).shape[0]
orininal_w = np.array(img).shape[1]
img = img.resize((WIDTH, HEIGHT))
#---------------------------------------------#
# 该部分用于查看网络结构
#---------------------------------------------#
from nets.unet import mobilenet_unet
if __name__ == "__main__":
model = mobilenet_unet(2, 416, 416)
model.summary()
