python调用OpenCV进行找图并返回坐标示例_python找图返回坐标

import threading
import cv2  # opencv库
import numpy as np  # 将图片转换成数组，opencv无法直接处理mss的截图，用它进行转换
import mss  # 截屏库
from concurrent.futures import ThreadPoolExecutor
import os
 
 
def findpic(x1, y1, x2, y2, lujin, xiangsidu):
    chang = x2 - x1
    kuan = y2 - y1
    quyu = {"left": x1, "top": y1, "width": chang, "height": kuan}
    with mss.mss() as sct:
        # 获取大图片
        quyujieping = sct.grab(quyu)  # 对屏幕的左上角800*600进行截图
        quyujieping = np.array(quyujieping)  # 调用numpy库将mss库的截屏转换一下，并赋值给变量quyujieping
        datupian_huidu = cv2.cvtColor(quyujieping, cv2.COLOR_BGR2GRAY)
 
        xiaotupian = cv2.imread(lujin)
        xiaotupian_huidu = cv2.cvtColor(xiaotupian, cv2.COLOR_BGR2GRAY)
 
        # 在大图片中查找小图片
        result = cv2.matchTemplate(datupian_huidu, xiaotupian_huidu, cv2.TM_CCOEFF_NORMED)
 
        # 筛选结果
        locations = np.where(result >= xiangsidu)  # 用numpy筛选一下结果高于0.85的
        locations = list(zip(*locations[::-1]))  # 将结果再次处理一下，仅保留坐标
 
        if len(locations) > 0:
            return (locations[0][0] + x1, locations[0][1] + y1)
        return (-1, -1)
def zuijin_zuobiao(coordinates_list, given_coordinate):
    # 确保给定的坐标包含两个元素
    if len(given_coordinate) != 2:
        raise ValueError("给定的坐标必须包含两个元素 (x, y)")
 
        # 初始化最小距离和对应坐标的坐标
    min_distance = float('inf')  # 使用正无穷大作为初始值
    zuijin_zuobiao = None
 
    # 计算曼哈顿距离并找到最近坐标
    for coord in coordinates_list:
        # 确保列表中的每个坐标也包含两个元素
        if len(coord) != 2:
            raise ValueError("坐标列表中的每个坐标必须包含两个元素 (x, y)")
 
        x1, y1 = given_coordinate
        x2, y2 = coord
        distance = abs(x1 - x2) + abs(y1 - y2)
 
        # 如果是第一个坐标或者距离更近，则更新最小距离和最近距离的坐标
        if distance < min_distance:
            min_distance = distance
            zuijin_zuobiao = coord
    if zuijin_zuobiao==None:
        return -1,-1
    else:
        return zuijin_zuobiao
def chazhao_tupian(datupian_huidu, xiaotupian_path, xiangsidu):
    xiaotupian = cv2.imread(xiaotupian_path)
    if xiaotupian is None:
        return []  # 返回空列表表示未找到图片或路径错误
    xiaotupian_huidu = cv2.cvtColor(xiaotupian, cv2.COLOR_BGR2GRAY)
    result = cv2.matchTemplate(datupian_huidu, xiaotupian_huidu, cv2.TM_CCOEFF_NORMED)
    locations = np.where(result >= xiangsidu)
    locations = list(zip(*locations[::-1]))
    return [(loc[0] + int(os.path.splitext(os.path.basename(xiaotupian_path))[0].split("_")[1]),
             loc[1] + int(os.path.splitext(os.path.basename(xiaotupian_path))[0].split("_")[2]))
            for loc in locations]
def findpicE(x1, y1, x2, y2, liebiao_dir, xiangsidu):
    chang = x2 - x1
    kuan = y2 - y1
    quyu = {"left": x1, "top": y1, "width": chang, "height": kuan}
 
    with mss.mss() as sct:
        quyujieping = sct.grab(quyu)
        quyujieping = np.array(quyujieping)
        datupian_huidu = cv2.cvtColor(quyujieping, cv2.COLOR_BGR2GRAY)
 
        # 使用线程池并行处理图片匹配
        with ThreadPoolExecutor() as executor:
            futures = []
            for xiaotupian_name in os.listdir(liebiao_dir):
                xiaotupian_path = os.path.join(liebiao_dir, xiaotupian_name)
                future = executor.submit(chazhao_tupian, datupian_huidu, xiaotupian_path, xiangsidu)
                futures.append(future)
 
                # 收集所有线程的结果
        zuobiao_liebiao = []
        for future in futures:
            zuobiao_liebiao.extend(future.result())
    juese_zuobiao = (0,0)  # 假设这个函数已定义并返回角色坐标
    weiyi_zuobiao = zuijin_zuobiao(zuobiao_liebiao, juese_zuobiao)  # 假设这个函数已定义并返回最近坐标
    if weiyi_zuobiao[0]>0:
        return weiyi_zuobiao
    return -1,-1
def findpicEX(x1, y1, x2, y2, liebiao_dir, xiangsidu):
    chang = x2 - x1
    kuan = y2 - y1
    quyu = {"left": x1, "top": y1, "width": chang, "height": kuan}
    with mss.mss() as sct:
        quyujieping = sct.grab(quyu)
        quyujieping = np.array(quyujieping)
        datupian_huidu = cv2.cvtColor(quyujieping, cv2.COLOR_BGR2GRAY)
 
        for xiaotupian_mingcheng in os.listdir(liebiao_dir):
            if not xiaotupian_mingcheng.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif')):
                continue  # 跳过非图片文件
            xiaotupian_path = os.path.join(liebiao_dir, xiaotupian_mingcheng)
            xiaotupian = cv2.imread(xiaotupian_path)
            if xiaotupian is None:
                continue  # 跳过无法读取的图片
            xiaotupian_huidu = cv2.cvtColor(xiaotupian, cv2.COLOR_BGR2GRAY)
            result = cv2.matchTemplate(datupian_huidu, xiaotupian_huidu, cv2.TM_CCOEFF_NORMED)
            locations = np.where(result >= xiangsidu)
            if locations is not None and len(locations[0]) > 0:
                return (locations[0][0] + x1, locations[1][0] + y1)  # 注意这里要分别取locations[0]和locations[1]
        return (-1, -1)