2024年TI杯E题-三子棋游戏装置方案分享-jdk123团队-第三弹视觉模块的封装

机械臂的设计

比赛第一天，我们打算做点提前量

视觉部分任务概述

赛题中，我们应该完成棋盘外棋子的识别，以及棋盘上棋子的识别。对此我们团队的方案为，先利用opencv,对九宫格棋盘进行识别

然后依据识别出九宫格的四个角点，来建立一个屏蔽罩，当识别内部棋子的时候，向外屏蔽，当识别外部棋子的时候，向内屏蔽。

内部棋子的识别

import time
import cv2
import numpy as np
import copy














def main7(image_path):
    class BHSBFL:
        def __init__(self, image_path):
            # 读取图像并转换为灰度图
            self.image = cv2.imread(image_path)
            self.gray = cv2.cvtColor(self.image, cv2.COLOR_BGR2GRAY)

        def find_grid_coordinates(self):
            # 应用边缘检测
            edges = cv2.Canny(self.gray, 50, 150, apertureSize=3)

            # 使用霍夫变换检测直线
            lines = cv2.HoughLinesP(edges, 1, np.pi / 180, 100, minLineLength=100, maxLineGap=10)

            # 复制原始图像以绘制检测结果（此处不再需要显示）
            image_copy = self.image.copy()

            # 寻找轮廓
            contours_info = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
            contours = contours_info[0] if len(contours_info) == 2 else contours_info[1]

            if contours:
                # 选择最大的轮廓，这通常是九宫格的外框
                contour = max(contours, key=cv2.contourArea)

                # 获取最小的外接矩形
                rect = cv2.minAreaRect(contour)
                box = cv2.boxPoints(rect)
                box = np.int0(box)

                # 计算每个格子的中心并编号
                width, height = rect[1]
                cell_width = width / 3
                cell_height = height / 3

                # 确保顶点顺序为左上、右上、右下、左下
                box = sorted(box, key=lambda x: (x[1], x[0]))

                coordinates = []
                for i in range(3):
                    for j in range(3):
                        # 计算格子中心
                        center_x = int(box[0][0] + j * cell_width + cell_width / 2)
                        center_y = int(box[0][1] + i * cell_height + cell_height / 2)

                        # 返回编号和中心坐标
                        coordinates.append((i * 3 + j + 1, (center_x, center_y)))

                return coordinates
            else:
                print("未找到轮廓")
                return []

    class ChessPieceDetector(BHSBFL):
        def __init__(self, image_path):
            super().__init__(image_path)
            self.image_path = image_path  # 存储图像路径
            self.coordinates = self.find_grid_coordinates()
            self.corner_coordinates = self.find_corners()
            self.image = cv2.imread(image_path)  # 读取图像

        def find_corners(self):
            gray = cv2.cvtColor(self.image, cv2.COLOR_BGR2GRAY)
            edged = cv2.Canny(gray, 30, 150)

            contours_info = cv2.findContours(edged, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
            contours = contours_info[0] if len(contours_info) == 2 else contours_info[1]

            if contours:
                largest_contour = max(contours, key=cv2.contourArea)
                rect = cv2.minAreaRect(largest_contour)
                box = cv2.boxPoints(rect)
                box = np.int0