多边形拟合+透视变换

# -*- coding: utf-8 -*-
# ----------------------------
# !  Copyright(C) 2022
#   All right reserved.
#   文件名称：xxx.py
#   摘   要：xxx
#   当前版本:1.0
#   作   者：刘恩甫
#   完成日期：2022-x-x
# -----------------------------
import os
import cv2
import numpy as np

def Perspective_transform(image, pts):
    (tl, tr, br, bl) = pts
    widthA = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2))
    widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2))
    maxWidth = max(int(widthA), int(widthB))
    heightA = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2))
    heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2))
    maxHeight = max(int(heightA), int(heightB))

    # in the top-left, top-right, bottom-right, and bottom-left order
    dst = np.array([[0, 0],
                    [maxWidth - 1, 0],
                    [maxWidth - 1, maxHeight - 1],
                    [0, maxHeight - 1]], dtype="float32")
    M = cv2.getPerspectiveTransform(pts, dst)
    warped = cv2.warpPerspective(image, M, (maxWidth, maxHeight))
    return warped

if __name__ == '__main__':
    label_path = r'.\truck_warp_affine\1\label\\'
    img_path = r'.\truck_warp_affine\1\img\\'

    for path in os.listdir(label_path):
        name, ext = os.path.splitext(path)

        img = cv2.imread(img_path + name + '.jpg')
        r_img = cv2.resize(img, dsize=None, fx=.25, fy=.25)
        label = cv2.imread(label_path + name + '.png')
        r_label = cv2.resize(label, dsize=None, fx=.25, fy=.25)
        #腐蚀操作
        r_label=cv2.erode(r_label,kernel=np.ones((5,5),np.uint8))
        #二值化
        gray = cv2.cvtColor(r_label, cv2.COLOR_BGR2GRAY)
        ret,binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
        contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
        cnt = contours[0]

        # 多边形拟合
        epi_thres=0.01 # epi_thres 越小，拟合越精细
        epsilon = epi_thres * cv2.arcLength(cnt, True)
        approx = cv2.approxPolyDP(cnt, epsilon, True)
        cv2.polylines(r_label, [approx], True, (0, 0, 255), 2)

        #找到最左，最下，最右，最上的四个点
        approx=approx.squeeze()
        row,col=sorted(approx, key=lambda x: x[0]),sorted(approx, key=lambda x: x[1])
        left,right,top,bottom=row[0],row[-1],col[0],col[-1]

        #进行透视变换
        min_area_rect = cv2.minAreaRect(np.array([left,right,top,bottom]))
        angle = min_area_rect[-1]
        if 0 < angle < 90:
            box=np.array([left,top,right,bottom]).astype(np.float32)
        else:
            box=np.array([top,right,bottom,left]).astype(np.float32)
        warpPerspective = Perspective_transform(r_img,box)
        if warpPerspective.shape[0]>warpPerspective.shape[1]:
            warpPerspective=np.rot90(warpPerspective)

        #画图操作
        for p in [left,right,top,bottom]:
            cv2.circle(r_img, p, 3, (255, 0, 0), 3)
            cv2.circle(r_label, p, 3, (255, 0, 0), 3)
        cv2.imshow('warpPerspective',warpPerspective)
        cv2.imshow('r_img', r_img)
        cv2.imshow('r_label', r_label)
        cv2.waitKey()

        # break