OpenCV图像识别有什么算法_opencv图像处理代码?

import os

import numpy as np
import cv2
from PIL import Image
from loguru import logger

from config import ScreenshotDir

import uiautomator2


class base(object):

    def __init__(self, device: uiautomator2.Device, timeout: int):
        logger.info("base 类初始化")
        self.Device = device
        self.TIMEOUT = timeout

    def get_current_screenshot(self, filename="current.png") -> str:
        filename = os.path.join(ScreenshotDir, filename)
        logger.info(f"获取当前截图,路径:{filename}")
        self.Device.screenshot(filename)
        return filename

    def image_rect_match(self, image1, image2, rect) -> float:
        """
          对比两张图片指定矩形区域内容是否一样, 返回匹配系数
          矩形区域((y1,x1),(y2,x2))
          """
        (y1, x1), (y2, x2) = rect

        img1 = self.cv_read(image1)[y1:y2, x1:x2]
        img2 = self.cv_read(image2)[y1:y2, x1:x2]

        # 使用模板函数进行匹配,归一化操作
        res = cv2.matchTemplate(img1, img2, cv2.TM_CCOEFF_NORMED)

        # 获取匹配结果
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
        logger.info(f"匹配度:{max_val} rect:{rect} {image1} {image2}")
        return max_val

    def image_exists(self, image1, image2, compatibility=0.99) -> bool:
        """
        判断image1 是否存在 image2中，返回bool值
        :param image1:
        :param image2:
        :param compatibility:
        :return:
        """
        logger.debug(f"image1={image1}  image2={image2}")

        img1 = self.cv_read(image1)
        img2 = self.cv_read(image2)

        # 使用模板函数进行匹配,归一化操作
        res = cv2.matchTemplate(img2, img1, cv2.TM_CCOEFF_NORMED)

        # 获取匹配结果
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
        logger.info(f"相似度:【{max_val}】 【{image1}】在图片中的【{image2}】")
        return max_val > compatibility

    def image_loc(self, image1, image2) -> tuple:
        """
        获取image1，在image2中的中间位置
        :param image1:
        :param image2:
        :param compatibility:
        :return:
        """
        logger.debug(f"image1={image1}  image2={image2}")

        img1 = self.cv_read(image1)
        img2 = self.cv_read(image2)

        # 使用模板函数进行匹配,归一化操作
        res = cv2.matchTemplate(img2, img1, cv2.TM_CCOEFF_NORMED)

        # 获取匹配结果
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)

        # 获取image1的中心坐标
        w, h = Image.open(image1).size
        x, y = max_loc[0] + int(w / 2), max_loc[1] + int(h / 2)

        logger.info(f"返回坐标:【{x, y}】 【{image1}】在【{image2}】的位置")

        return x, y

    @staticmethod
    def image_draw_rect(image, rect):
        """
        画出目标图片中的，指定区域，主要用于调试
        :param image:
        :param rect:
        :return:
        """
        (y1, x1), (y2, x2) = rect
        image = cv2.imread(image, cv2.IMREAD_COLOR)
        cv2.rectangle(image, (x1, y1), (x2, y2), (0, 0, 255), 5)
        cv2.imwrite("Test.png", image)

    def cv_read(self, image):
        """
        opencv无法识别中文路径图片，使用此方法读
        :param image:
        :return:
        """
        # target = cv2.imread(image, cv2.IMREAD_GRAYSCALE)
        return cv2.imdecode(np.fromfile(image, dtype=np.uint8), -1)

    def cv_write(self, img, filename):
        """
        opencv无法读取中文路径图片，使用此方法写
        :param img:
        :param filename: 完整路径 如：C:1  保存：C:1.png
        :return:
        """
        cv2.imencode('.png', img)[1].tofile(filename)