# -*- coding: utf-8 -*-
'''
作者 : 丁毅
開(kāi)發(fā)時(shí)間 : 2021/4/21 15:30
'''
import cv2
import numpy as np
from PIL import Image, ImageDraw, ImageFont
import matplotlib.pyplot as plt


#用于給圖片添加中文字符的函數(shù)
def cv2ImgAddText(img, text, left, top, textColor=(0, 255, 0), textSize=20):
    # 判斷是否OpenCV圖片類型
    if (isinstance(img, np.ndarray)):
        img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
    # 創(chuàng)建一個(gè)可以在給定圖像上繪圖的對(duì)象
    draw = ImageDraw.Draw(img)
    # 字體的格式
    fontStyle=ImageFont.truetype("font/simsun.ttc",textSize, encoding="utf-8")
    # 繪制文本
    draw.text((left, top), text, textColor, font=fontStyle)
    # 轉(zhuǎn)換回OpenCV格式
    return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)

# plt繪圖顯示中文
plt.rcParams['font.family'] = 'SimHei'
img0 = cv2.imread(r"C:\Users\pc\Desktop\0.bmp")
cv2.imshow('img', img0)
# 彩色圖轉(zhuǎn)灰度圖
img1 = cv2.cvtColor(img0, cv2.COLOR_BGR2GRAY)

# 缺陷檢測(cè)
for i in range(1, 6):
    defect_img0 = cv2.imread(r"C:\Users\pc\Desktop\%d.bmp"%i)
    # 獲取灰度圖像
    defect_img1 = cv2.cvtColor(defect_img0, cv2.COLOR_BGR2GRAY)
    # 獲取原圖像的灰度直方圖
    hist0 = cv2.calcHist([img1], [0], None, [256], [0.0, 255.0])
    # 獲取待檢測(cè)圖像的灰度直方圖
    hist1 = cv2.calcHist([defect_img1], [0], None, [256], [0.0, 255.0])
    # 為圖像添加標(biāo)題
    plt.title("原圖與待檢測(cè)img%d對(duì)比"%i)
    # 添加圖例
    plt.plot(hist0, label='原圖')
    plt.plot(hist1, label='待檢測(cè)img%d'%i)
    # 相似度比較
    rst = cv2.compareHist(hist0, hist1, method=cv2.HISTCMP_CORREL)
    # res >= 0.95即認(rèn)為合格
    cv2.imshow(str(i) + ".img", cv2ImgAddText(defect_img0, "合格" if rst >= 0.95 else "不合格", 20, 20, (255, 0, 0), 25))
    # 設(shè)置x軸的數(shù)值范圍
    plt.xlim([0, 256])
    plt.legend(loc='upper left')
    plt.show()
cv2.waitKey(0)