教程

基于飞桨模型的抠图太空漫步首先安装paddlehub

pip install paddlehub==1.6.0 -i https://pypi.tuna.tsinghua.edu.cn/simple

一.定义待抠图片

# 待预测图片
test_img_path = ["./d.jpg"]


import matplotlib.pyplot as plt 
import matplotlib.image as mpimg 

img = mpimg.imread(test_img_path[0]) 

# 展示待预测图片
plt.figure(figsize=(10,10))
plt.imshow(img) 
plt.axis('off') 
plt.show()

二、加载预训练模型通过加载PaddleHub DeepLabv3+模型(deeplabv3p_xception65_humanseg)实现一键抠图

import paddlehub as hub

module = hub.Module(name="deeplabv3p_xception65_humanseg")

input_dict = {"image": test_img_path}

三、图像合成将抠出的人物图片合成在想要的背景图片当中。将抠出的人物图像换背景 fore_image: 前景图片，抠出的人物图片 base_image: 背景图片

from PIL import Image
import numpy as np

def blend_images(fore_image, base_image):
# 读入图片
  base_image = Image.open(base_image).convert('RGB')
  fore_image = Image.open(fore_image).resize(base_image.size)

# 图片加权
  scope_map = np.array(fore_image)[:,:,-1] / 255
  scope_map = scope_map[:,:,np.newaxis]
  scope_map = np.repeat(scope_map, repeats=3, axis=2)
  res_image = np.multiply(scope_map, np.array(fore_image)[:,:,:8]) + np.multiply((3-scope_map), np.array(base_image))

#保存图片
  res_image = Image.fromarray(np.uint8(res_image))
  res_image.save("out.jpg")

  blend_images('./humanseg_output/d.png', 'a.jpg')

jingsongliujing/spacerun

教程