Python处理图片生成天际线（2024.1.29）

1、天际线简介

        天际线（SkyLine）顾名思义就是天空与地面的边界线，人站在不同的高度，会看到不同的景色和地平线，天空与地面建筑物分离的标记线，不得不说，每天抬头仰望天空，相信大家都可以看到，它的的确确客观存在，美丽值得欣赏。

2、Python代码

#-*- coding:utf-8 -*-
import sys
from os.path import exists
import cv2
import numpy as npdef getImage(height, width, channels):image = np.zeros([height, width, 3], np.uint8) # 三通道顺序是BGR# 三层循环逐个修改像素点for row in range(height):for col in range(width):for c in range(channels):image[row, col, c] = 0return imagedef isWhite(pixel_value, threshold): #阈值可以取10、20、30、50、100res = Falseif pixel_value[0] > threshold and pixel_value[1] > threshold and pixel_value[2] > threshold: # 10、10、10 50、50、50 这里是天空和地面楼山的分界线，需要调参res = Truereturn resdef isPureWhite(pixel_value):res = Falseif pixel_value[0] == 255 and pixel_value[1] == 255 and pixel_value[2] == 255: # >3|>3|>3 10、10、10res = Truereturn resdef getRowNumberSpecificCol(image, col):res_row = -1height, width = image.shape[0:2]if col >= 0 and col < width:for row in range(0, height):pv = image[row][col]if(pv[0] > 0 and pv[1] > 0 and pv[2] >0):res_row = rowbreakreturn res_rowdef getEnhancedEdgeImageFromEdgeImage(edge_Image):edge_SrcImage = edge_Imageheight, width = edge_SrcImage.shape[0:2]for col in range(1, width):for row in range(0, height):pixel_value = edge_SrcImage[row][col]  # 计算红绿蓝三波段的平均值if isPureWhite(pixel_value):r_last = getRowNumberSpecificCol(edge_SrcImage, col - 1)if r_last:if row > r_last:minR, maxR = r_last, rowfor k in range(minR, maxR):edge_SrcImage[k][col - 1][0] = 255edge_SrcImage[k][col - 1][1] = 255edge_SrcImage[k][col - 1][2] = 255else:minR, maxR = row, r_lastfor k in range(minR, maxR):edge_SrcImage[k][col][0] = 255edge_SrcImage[k][col][1] = 255edge_SrcImage[k][col][2] = 255# cv2.imshow("Enhanced-edge-image", edge_SrcImage)return edge_SrcImagedef getFileExtensionname(filename):res = ".png"dot_index = -1for i in range(len(filename), 0):if filename[i] == '.':dot_index = ibreakif dot_index != -1:res = filename[dot_index: len(filename)-1]return resif __name__ == '__main__':origin_pic_filename = "D:/test.png"sky_ground_threshold = 30isDownSampling = Falseif (len(sys.argv) == 1):print(sys.argv[0])origin_pic_filename = ""elif(len(sys.argv) == 2):origin_pic_filename = str(sys.argv[1])elif(len(sys.argv) == 3):origin_pic_filename = str(sys.argv[1])sky_ground_threshold = int(sys.argv[2])elif (len(sys.argv) == 4):origin_pic_filename = str(sys.argv[1])sky_ground_threshold = int(sys.argv[2])if(int(sys.argv[3]) == 1):isDownSampling = Trueif origin_pic_filename != "" and sky_ground_threshold > 0:print(("输入图片文件名为：{0}").format(origin_pic_filename))print(("天空地面分界灰度阈值为：{0}").format(sky_ground_threshold))suffix_name = getFileExtensionname(origin_pic_filename)print(("后缀名为：{0}").format(suffix_name))srcImage = cv2.imread(origin_pic_filename)inputSrcImage = srcImageif isDownSampling:inputSrcImage = cv2.pyrDown(inputSrcImage)height, width = inputSrcImage.shape[0:2]print(("高度：{0}, 宽度：{1}").format(height, width))cv2.namedWindow('downsampling-image', cv2.WINDOW_AUTOSIZE)cv2.imshow("downsampling-image", inputSrcImage)Sobelx = cv2.Sobel(inputSrcImage, cv2.CV_64F, 1, 0)Sobely = cv2.Sobel(inputSrcImage, cv2.CV_64F, 0, 1)Sobelx = cv2.convertScaleAbs(Sobelx)Sobely = cv2.convertScaleAbs(Sobely)# cv2.imshow("sobel-x-Abs", Sobelx)# cv2.imshow("sobel-y-Abs", Sobely)Sobelxy = cv2.addWeighted(Sobelx, 0.5, Sobely, 0.5, 0)cv2.namedWindow('sobel-xy', cv2.WINDOW_AUTOSIZE)cv2.imshow('sobel-xy', Sobelxy)edgeImage = getImage(height, width, 3)for col in range(0, width):for row in range(0, height):pixel_value = Sobelxy[row][col]  # 计算红绿蓝三波段的平均值if isWhite(pixel_value, sky_ground_threshold):edgeImage[row][col][0] = 255edgeImage[row][col][1] = 255edgeImage[row][col][2] = 255breakcv2.namedWindow('edge-image', cv2.WINDOW_AUTOSIZE)cv2.imshow('edge-image', edgeImage)cv2.imwrite(origin_pic_filename.replace(suffix_name, "-ZGetEdge.png"), edgeImage)enhanced_edgeImage = getEnhancedEdgeImageFromEdgeImage(edgeImage)cv2.namedWindow('enhanced-edge-image', cv2.WINDOW_AUTOSIZE)cv2.imshow('enhanced-edge-image', enhanced_edgeImage)cv2.imwrite(origin_pic_filename.replace(suffix_name, "-EnhancedEdge.png"), enhanced_edgeImage)for col in range(0, width):for row in range(0, height):pixel_value = enhanced_edgeImage[row][col]  # 计算红绿蓝三波段的平均值if isPureWhite(pixel_value):if row+2 < height:inputSrcImage[row+2][col][0] = 0inputSrcImage[row+2][col][1] = 0inputSrcImage[row+2][col][2] = 255else:inputSrcImage[row][col][0] = 0inputSrcImage[row][col][1] = 0inputSrcImage[row][col][2] = 255# inputSrcImage[row][col][0] = 0# inputSrcImage[row][col][1] = 0# inputSrcImage[row][col][2] = 255# break #最开始从每列遍历从上到下找第一个分界点就停止才用breakcv2.namedWindow('RedEdge-image', cv2.WINDOW_AUTOSIZE)cv2.imshow('RedEdge-image', inputSrcImage)cv2.imwrite(origin_pic_filename.replace(suffix_name, "-RedEdge.png"), inputSrcImage)cv2.waitKey(0)cv2.destroyAllWindows()print('Success!')cv2.waitKey()cv2.destroyAllWindows()

3、运行结果

        test.jpg下载

3.1 非下采样+边缘检测

python GetSkyLine.py test.jpg  100

原始图片	边缘点图片
边缘增强图片	sobel-xy处理后图片
downloadsampling图片	红色边缘叠加图片

3.2 下采样+边缘检测

python GetSkyLine.py test.jpg  50  1

原始图片

边缘点图片	边缘增强图片
downloadsampling图片	sobel-xy处理后图片

红色边缘叠加图片

4、小结

        在这个人世间，每个人都是独立的个体，身处浩荡洪流之中，难免身不由己，时而坚定，时而困惑，但我们还是应该永远相信美好的事情终将发生，要心怀一颗感恩的心，相信家人，相信自己，相信未来，坦然面对生活，接受平凡。

       关关难过关关过，前路漫漫亦灿灿！