文本检测-4-极坐标

采用极坐标变换进行图片拉直

# -*- encoding: utf-8 -*-
"""
@date: 2021/4/14 3:57 下午
@author: xuehuiping
"""
import cv2
import numpy as np
import sys


# 实现图像的极坐标的转换 center代表及坐标变换中心‘;r是一个二元元组，代表最大与最小的距离；theta代表角度范围
# rstep代表步长； thetastap代表角度的变化步长
def polar(image, center, r, theta=(0, 360), rstep=0.5, thetastep=360.0 / (180 * 4)):
    # 得到距离的最小值、最大值
    minr, maxr = r
    # 角度的最小范围
    mintheta, maxtheta = theta
    # 输出图像的高、宽 O:指定形状类型的数组float64
    H = int((maxr - minr) / rstep) + 1
    W = int((maxtheta - mintheta) / thetastep) + 1
    O = 125 * np.ones((H, W), image.dtype)
    # 极坐标转换  利用tile函数实现W*1铺成的r个矩阵 并对生成的矩阵进行转置
    r = np.linspace(minr, maxr, H)
    r = np.tile(r, (W, 1))
    r = np.transpose(r)
    theta = np.linspace(mintheta, maxtheta, W)
    theta = np.tile(theta, (H, 1))
    x, y = cv2.polarToCart(r, theta, angleInDegrees=True)
    # 最近插值法
    for i in range(H):
        for j in range(W):
            px = int(round(x[i][j]) + cx)
            py = int(round(y[i][j]) + cy)
            if ((px >= 0 and px <= w - 1) and (py >= 0 and py <= h - 1)):
                O[i][j] = image[py][px]

    return O


if __name__ == "__main__":
    file_name = '/Users/xuehuiping/Downloads/改进点/002eb046-e908-4949-a21d-2fa1ddb323c9.png'
    # file_name = "/Users/xuehuiping/Downloads/改进点/WX20210311-185118@2x.png"
    img = cv2.imread(file_name, cv2.IMREAD_GRAYSCALE)
    # 传入的图像宽：600  高：400
    h, w = img.shape[:2]
    print("h:%s w:%s" % (h, w))
    # 极坐标的变换中心（300，200）
    cx, cy = w / 2, w / 2
    # 圆的半径为10 颜色：灰 最小位数3
    cv2.circle(img, (int(cx), int(cy)), int(w / 2), (255, 0, 0, 0), 3)
    L = polar(img, (cx, cy), (100, 350))
    # 旋转
    L = cv2.flip(L, 0)
    # 显示与输出
    cv2.imshow('img', img)
    cv2.imshow('O', L)
    cv2.waitKey(0)
    cv2.destroyAllWindows()