imagetk 0.1.2

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What is it

imagetk是一个图像分析的Python包，用以进行图像处理、特征提取、边缘检测等。

imagetk is a Python package providing image process, feature extraction, and edge detection.

Where to get it

最新版本的源码和编译安装包可以在Python package index获取。

The source code and binary installers for the latest released version are available at the [Python package index].

https://pypi.org/project/imagetk

可以用pip安装imagetk。

You can install protege like this:

pip install imagetk

也可以用setup.py安装。

Or in the protege directory, execute:

python setup.py install

How to use it

特征提取

brisque

from imagetk import feature
import numpy
from PIL import Image

image=Image.open("test.png")#图片读取
image = image.convert('L')#转换为灰度图
image=numpy.array(image)#转换为numpy.array
brisque_feature=feature.brisque(image)#brique特征计算

mean_grad

image=Image.open("test.png")#图片读取
image = image.convert('L')#转换为灰度图
image=numpy.array(image)#转换为numpy.array
mean_grad=feature.mean_grad(image)#mean_grad计算

gray_quantile_expose

image=Image.open("test.png")#图片读取
image = image.convert('L')#转换为灰度图
image=numpy.array(image)#转换为numpy.array
bright,dark=feature.gray_quantile_expose(image,q=0.75,pix=(96,192))#gray_quantile_expose计算

block_value_expose

image=Image.open("test.png")#图片读取
image=numpy.array(image)#转换为numpy.array
bright,dark=feature.block_value_expose(array,stride=8,channel_first=False)

cumprob

image=Image.open("test.png")#图片读取
image = image.convert('L')#转换为灰度图
image=numpy.array(image)#转换为numpy.array
cumprob=feature.cumprob(image)

边缘检测

sobel

image=Image.open("test.png")#图片读取
image = image.convert('L')#转换为灰度图
image=numpy.array(image)#转换为numpy.array
edges=edge.sobel(image)

canny

image=Image.open("test.png")#图片读取
image = image.convert('L')#转换为灰度图
image=numpy.array(image)#转换为numpy.array
edges=edge.canny(image,kernel_size=3,sigma=1)

houghline

from imagetk import threshold

image=Image.open("test.png")#图片读取
image = image.convert('L')#转换为灰度图
image=numpy.array(image)#转换为numpy.array
# 二值化处理
thres=threshold.otsu(image)
image[image>thres]=255
image[image<=thres]=0
# 边缘检测
edge_image=edge.canny(image).astype(numpy.uint8)
# houghline 检测
lines=edge.houghlines(edge_image, rho=1, theta=numpy.pi/180, threshold=100)