@[toc]
官网地址
新建AipBodyAnalysis
from aip import AipBodyAnalysis
""" 你的 APPID AK SK """
APP_ID = '你的 App ID'
API_KEY = '你的 Api Key'
SECRET_KEY = '你的 Secret Key'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
读取图片
""" 读取图片 """
def get_file_content(filePath):
with open(filePath, 'rb') as fp:
return fp.read()
image = get_file_content('example.jpg')
""" 调用人像分割 """
client.bodySeg(image);
""" 如果有可选参数 """
options = {}
options["type"] = "labelmap"
""" 带参数调用人像分割 """
client.bodySeg(image, options)
完整代码
python调用百度AI的方法不用多说，实现人像分割的代码如下：
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 1 21:25:21 2021
@author: lenovo
"""
from aip import AipBodyAnalysis
import cv2
import numpy as np
import base64
APP_ID = '23619478'
API_KEY = 'x2M6XTQ4oNIlhS2f2GQBElHa'
SECRET_KEY = 'xxxxxxxxxxx'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
""" 读取图片 """
def get_file_content(filePath):
with open(filePath, 'rb') as fp:
return fp.read()
image = get_file_content('banben.jpg')
""" 调用人像分割 """
res = client.bodySeg(image)
foreground = base64.b64decode(res['foreground'])
labelmap = base64.b64decode(res['labelmap'])
scoremap = base64.b64decode(res['scoremap'])
nparr_foreground = np.fromstring(foreground,np.uint8)
foregroundimg = cv2.imdecode(nparr_foreground,1)
foregroundimg = cv2.resize(foregroundimg,(512,512),interpolation=cv2.INTER_NEAREST)
im_new_foreground = np.where(foregroundimg==1, 10, foregroundimg)
cv2.imwrite('foreground.png', im_new_foreground)
nparr_labelmap = np.fromstring(labelmap,np.uint8)
labelmapimg = cv2.imdecode(nparr_labelmap,1)
labelmapimg = cv2.resize(labelmapimg,(512,512),interpolation=cv2.INTER_NEAREST)
im_new_labelmapimg = np.where(labelmapimg==1, 255, labelmapimg)
cv2.imwrite('labelmap.png', im_new_labelmapimg)
nparr_scoremap = np.fromstring(scoremap,np.uint8)
scoremapimg = cv2.imdecode(nparr_scoremap,1)
scoremapimg = cv2.resize(scoremapimg,(512,512),interpolation=cv2.INTER_NEAREST)
im_new_scoremapimg = np.where(scoremapimg==1, 255, scoremapimg)
cv2.imwrite('scoremap.png', im_new_scoremapimg)
最终效果
原图：
labelmap - 二值图像，需二次处理方能查看分割效果
scoremap - 人像前景灰度图
foreground - 人像前景抠图，透明背景
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