pythonpictureanalysis/Subtractive_Algorithm.py

# -*- coding: utf-8 -*-
# @Time    : 2022-7-26 0026 9:58
# @Author  : Qing
# @Email   : derighoid@gmail.com
# @File    : Subtractive_Algorithm.py
# @Software: PyCharm
import os.path

import matplotlib.pyplot as plt

from Picture_Reading import *


class ReduceColor(pictureRead):
    def __init__(self, filePath):
        self.filePath = filePath

    def readImg(self):
        face4 = Image.open(self.filePath)
        return face4

    def imageMatrix(self):
        im4 = np.array(self.readImg())
        return im4

    # 减色算法
    def decrease_color(self):
        '''
        val=|32  (0<=var<64)
            |96 (64<=var<128)
            |160 (128<=var<192)
            |224 (192<=var<256)
        :return:
        '''
        img = self.imageMatrix().copy()
        # img=img//64*64+32
        H = img.shape[0]  # 获取图片的高
        W = img.shape[1]  # 获取图片的宽

        # 创建新的图
        newImg = np.zeros((H, W, 3), np.uint8)
        newImg2 = np.zeros((H, W, 3), np.uint8)
        newImg3 = np.zeros((H, W, 3), np.uint8)

        # 量化操作
        for i in range(H):
            for j in range(W):
                for k in range(3):  # RGB三分量
                    if img[i, j][k] < 128:
                        gray = 0
                    else:
                        gray = 128
                    newImg[i, j][k] = np.uint8(gray)  # 传给新图片

        for i in range(H):
            for j in range(W):
                for k in range(3):
                    if img[i, j][k] < 64:
                        gray = 0
                    elif img[i, j][k] < 128:
                        gray = 64
                    elif img[i, j][k] < 192:
                        gray = 128
                    else:
                        gray = 192
                    newImg2[i, j][k] = np.uint8(gray)

        for i in range(H):
            for j in range(W):
                for k in range(3):
                    if newImg3[i, j][k] < 32:
                        gray = 0
                    elif newImg3[i, j][k] < 96:
                        gray = 32
                    elif newImg3[i, j][k] < 96:
                        gray = 96
                    elif newImg3[i, j][k] < 128:
                        gray = 96
                    elif newImg3[i,j][k]<160:
                        gray=128
                    elif newImg3[i,j][k]<192:
                        gray=160
                    elif newImg3[i,j][k]<244:
                        gray=192
                    else:
                        gray = 224
                    newImg3[i, j][k] = np.uint8(gray)

        #定义画布
        plt.figure(figsize=(16,8))
        plt.subplot(141)
        plt.imshow(img)
        plt.title("origin")

        plt.subplot(142)
        plt.imshow(newImg)
        plt.title("1")

        plt.subplot(143)
        plt.imshow(newImg2)
        plt.title("2")

        plt.subplot(144)
        plt.imshow(newImg3)
        plt.title("3")
        plt.show()
        return newImg,newImg2,newImg3

    # 图像二值化(以128为阈值进行二值化)
    def imgBinarization(self):
        a = self.imageGrey() - np.array([[128]])
        b = np.floor(a / np.array([[256]]))
        c = b + np.array([[1]], dtype=np.int16)
        bfilter = c.astype("uint8")
        result = bfilter * np.array([[255]], dtype=np.uint8)
        # result=np.array(self.readImg().convert("1"))
        plt.imshow(result)
        plt.show()
        return result

    # 保存图片
    def img_Save(self):
        root = "E:\\桌面\\Python_Picture_Analysis\\data\\"
        if not os.path.exists(root):
            os.mkdir(root)
        else:
            Image.fromarray(np.uint8(self.decrease_color)).save(root + 'picture8' + '.jpg')
            Image.fromarray(np.uint8(self.imgBinarization())).save(root + 'picture9' + '.jpg')
            print("Picture Save successfully")