小修改。

README.md

@@ -1,4 +1,4 @@
-# [广东政务数据创新大赛—智能算法赛](https://tianchi.aliyun.com/competition/information.htm?spm=5176.100067.5678.2.6eeaffc9NYqn2w&raceId=231615)
+# 广东政务数据创新大赛—智能算法赛
 
 其实广东政务有两个大赛：
 
@@ -21,9 +21,16 @@ src/python
 
 * 运行和结果
 
+项目是一个个单一文件组合而成，执行顺序：
+
+- src\python\main.py  导入数据，数据初始化等操作。
+- src\python\plot1.py
+- src\python\plot2.py
+- src\python\result.py
+- src\python\cut_roi.py
+
 * 相关文档
 
 本文博客：[广东政务比赛](http://blog.yoqi.me)
 
 项目地址：[gdzw-analysis](http://git.yoqi.me:3000/lyq/gdzw-analysis)
-

src/VS/labelData.cpp

@@ -1,10 +1,11 @@
 #include <iostream>
 #include <sstream>
 #include <vector>
+// "D:\Program-Files\opencv\build\include\opencv2\opencv.hpp"
 #include <opencv2/opencv.hpp>
 using namespace std;
 
-#define  DATA_DIR "/home/vl/ali/data/256/"
+#define  DATA_DIR "/media/sf_share/linux/workspaces/gdzw-analysis/input"
 
 #define  IM_ROWS  5106
 #define  IM_COLS  15106

src/python/cut_roi.py

@@ -3,10 +3,10 @@
 img_size = 256 # 15106/ 256 =59...2  5106/256=19..284
 
 for i in range(len(im_2015)/img_size + 1 ): # last 284
-    for j in range(len(im_2015[0])/img_size ): #last 2 too small, drop one
+    for j in range(len(im_2015[0])/img_size ): # last 2 too small, drop one
         im_name = str(i)+'_'+str(j)+'_'+str(img_size)+'_.jpg'
-        cv2.imwrite("2017/"+im_name,scale_percentile(im_2017[i*img_size:i*img_size+img_size, j*img_size:j*img_size+img_size, :3])*255)
-        cv2.imwrite("2015/"+im_name,scale_percentile(im_2015[i*img_size:i*img_size+img_size, j*img_size:j*img_size+img_size, :3])*255)
-        cv2.imwrite("cada/"+im_name,im_cada[i*img_size:i*img_size+img_size, j*img_size:j*img_size+img_size]*255)
-        cv2.imwrite("tiny/"+im_name,im_tiny[i*img_size:i*img_size+img_size, j*img_size:j*img_size+img_size]*255)
+        cv2.imwrite("./output/2017/"+im_name,scale_percentile(im_2017[i*img_size:i*img_size+img_size, j*img_size:j*img_size+img_size, :3])*255)
+        cv2.imwrite("./output/2015/"+im_name,scale_percentile(im_2015[i*img_size:i*img_size+img_size, j*img_size:j*img_size+img_size, :3])*255)
+        cv2.imwrite("./output/cada/"+im_name,im_cada[i*img_size:i*img_size+img_size, j*img_size:j*img_size+img_size]*255)
+        cv2.imwrite("./output/tiny/"+im_name,im_tiny[i*img_size:i*img_size+img_size, j*img_size:j*img_size+img_size]*255)
 

src/python/main.py

@@ -1,36 +1,40 @@
-from collections import defaultdict
 import csv
 import sys
+from collections import defaultdict
 
 import cv2
-from shapely.geometry import MultiPolygon, Polygon
-import shapely.wkt
-import shapely.affinity
-import numpy as np
-import tifffile as tiff
-
 #%matplotlib inline
 import matplotlib.pyplot as plt
+import numpy as np
+import shapely.affinity
+import shapely.wkt
+# Read and write image data from and to TIFF files.
+import tifffile as tiff
 from matplotlib import cm
+from shapely.geometry import MultiPolygon, Polygon
+
+import os
 
-getcwd()
-chdir("/media/sf_share/linux/workspaces/guangdong")
+os.getcwd()
+os.chdir("/media/sf_share/linux/workspaces/gdzw-analysis")
 
 FILE_2015 = './input/quickbird2015.tif'
 FILE_2017 = './input/quickbird2017.tif'
 FILE_cadastral2015 = './input/cadastral2015.tif'
 FILE_tinysample = './input/tinysample.tif'
 
-#read images
+#read images,return numpy array.
 im_2015 = tiff.imread(FILE_2015).transpose([1, 2, 0])
 im_2017 = tiff.imread(FILE_2017).transpose([1, 2, 0])
 im_tiny = tiff.imread(FILE_tinysample)
 im_cada = tiff.imread(FILE_cadastral2015)
 
 im_2015.shape
+# (5106, 15106, 4)
 im_tiny.shape
+# (5106, 15106, 3)
 im_cada.shape
-
+# (5106, 15106)
 
 def scale_percentile(matrix):
     w, h, d = matrix.shape

src/python/result.py

@@ -1,2 +1,5 @@
+#生成sample
 result_temp = np.random.randint(2, size=im_cada.shape, dtype=np.uint8)
-tiff.imsave('./output/result_temp.tiff', result_temp)
+tiff.imsave('./output/result_temp.tiff', result_temp)
+
+