python 人像抠图

安装依赖:

1. 将依赖保存为requirements.txt 文件

python 人像抠图
appdirs==1.4.4
astor==0.8.1
Babel==2.8.0
certifi==2020.6.20
cfgv==3.1.0
chardet==3.0.4
click==7.1.2
cma==3.0.3
colorlog==4.1.0
cycler==0.10.0
decorator==4.4.2
distlib==0.3.1
docopt==0.6.2
filelock==3.0.12
flake8==3.8.3
Flask==1.1.2
Flask-Babel==1.0.0
funcsigs==1.0.2
gast==0.3.3
graphviz==0.14
gunicorn==20.0.4
hdfs==2.5.8
identify==1.4.22
idna==2.10
importlib-metadata==1.7.0
itsdangerous==1.1.0
Jinja2==2.11.2
joblib==0.16.0
kiwisolver==1.2.0
MarkupSafe==1.1.1
matplotlib==3.2.2
mccabe==0.6.1
nltk==3.5
nodeenv==1.4.0
numpy==1.19.0
objgraph==3.4.1
opencv-python==4.3.0.36
paddlehub==1.7.1
paddlepaddle==1.8.2
pandas==1.0.5
pathlib==1.0.1
Pillow==7.2.0
pre-commit==2.6.0
prettytable==0.7.2
protobuf==3.12.2
pycodestyle==2.6.0
pyflakes==2.2.0
pyparsing==2.4.7
python-dateutil==2.8.1
pytz==2020.1
PyYAML==5.3.1
rarfile==3.1
regex==2020.6.8
requests==2.24.0
scipy==1.3.1
sentencepiece==0.1.91
six==1.15.0
toml==0.10.1
tqdm==4.47.0
urllib3==1.25.9
virtualenv==20.0.26
visualdl==2.0.0b7
Werkzeug==1.0.1
yapf==0.26.0
zipp==3.1.0
requirements.txt

2. 当前目录运行

pip install -r requirements.txt

 

程序:

import os
import paddlehub as hub
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import matplotlib.figure as figure
import numpy as np
matplotlib.use('TkAgg') 

base_dir = os.path.abspath('.')
input_img_path = base_dir+"/source/"
output_img_path = base_dir+"/target/"


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

input_imgs_dirs = [input_img_path+p for p in os.listdir(input_img_path)]
output_img_dirs = [output_img_path+p.split(".")[0]+".png" for p in os.listdir(input_img_path)]
print(input_imgs_dirs)
print(output_img_dirs)

all =len(input_imgs_dirs)
i=0
for input in input_imgs_dirs:
    print("%d%%"%(i/all*100))
    results = humanseg.segmentation(data={"image":[input]})
    data = results[0]['data']
    plt.figure(figsize=[10,10])
    plt.imsave(output_img_dirs[i],data)
    # plt.imshow(data)
    # plt.axis("off")
    # plt.show()
    i+=1

 

NOTE:

1. MAC 和 Linux 上可以正常运行,windows 上需要安装docker 后运行

 
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