ça marche pas mais c'est cool

Challenge3/code/getElevation.py

+from PIL import Image
 import urllib.request
 import json
 import math
@@ -5,25 +6,36 @@ import matplotlib.pyplot as plt
 import csv
 import numpy as np
 csvfile = "D:/documents/IMT/datascience/challenge3/code/svg.csv"
+import png
+
+def draw_image_from_colour_grid(iteration,partie,colour_grid):
+    im = Image.new(mode='RGB', size=(len(colour_grid), len(colour_grid[0])))
+    im.putdata([x for row in colour_grid for x in row])
+    im.show()
+    im.save('D:/documents/IMT/datascience/challenge3/code/out'+str(iteration)+'partie'+str(partie)+'.jpg', 'JPEG')
+
+
+def pixelfromaltitude(altitude):
+    '''convert altitude to RGB as altitude = R*255+V'''
+    return((altitude//255,altitude%255,0))
+
+def altitudefrompixel(pixel):
+    '''pixelfromaltitude^-1'''
+    return(pixel[0]*255+pixel[1]+0)
 
 def convert(listPixels):
-    intercept=np.matrix([60.59049467, -12.61278589])
-    coef=np.matrix([[2.34940394e-05, -9.22137497e-03],[1.12794639e-02, 4.39805467e-04]])
+    intercept=np.matrix([60.96807828, -9.89553667])
+    coef=np.matrix([[1.66888816e-06, -9.33208479e-03], [1.20700439e-02, -1.55870403e-03]])
     res=[]
     for pixel in listPixels:
-        print("intercept = ", intercept)
-        print("coef = ", coef)
-        print("np.matrix(([pixel[0],pixel[1]])) = ", np.matrix(([pixel[0],pixel[1]])))
         res.append(np.transpose(intercept)+coef*np.transpose(np.matrix(([pixel[0],pixel[1]]))))
     return(res)
 
-print("coucou ! : ",convert([(4036,2790),(1988,2579),(660,1319)]))
 
 def getElevation(listPixels):
     listLongLat=convert(listPixels)
-    lat_list=[elt[0] for elt in listLongLat]
-    long_list=[elt[1] for elt in listLongLat]
-
+    lat_list=[elt[0].item(0) for elt in listLongLat] #.item(0) c'est pour prendre l'unique elt de la np.matrix
+    lon_list=[elt[1].item(0) for elt in listLongLat]
 
     #on contruit le json
     d_ar=[{}]*len(lat_list)
@@ -51,17 +63,22 @@ def getElevation(listPixels):
         elev_list.append(js_str['results'][j]['elevation'])
     return(elev_list)
 
-listPixels=[]
-for line in range(3510):
-    for col in range(4830):
-        listPixels.append((col,line))
-liste=getElevation(listPixels)
+nbLine=3510
+nbCol=483
+partie=0
+for iteration in range(3510):
+    listPixels=[]
+    for line in range(iteration,(iteration+1)):
+        for col in range(partie*nbCol,(partie+1)*nbCol):
+            listPixels.append((col,line))
+    liste=getElevation(listPixels)
 
-res=[[[] for _ in range(4830)] for _ in range(3510)]
-for pixel in listPixels:
-    line=pixel[1]
-    col=pixel[0]
-    res[line][col]=listPixels[4830*line+col]
-with open(csvfile, "w") as output:
-    writer = csv.writer(output, lineterminator='\n')
-    writer.writerows(res)
+    res=[[[] for _ in range(nbCol)] for _ in range(nbLine)]
+    for pixel in listPixels:
+        line=pixel[1]
+        col=pixel[0]
+        res[line][col]=liste[nbCol*line+nbCol]
+    
+    image_svg=[[pixelfromaltitude(a) for a in liste]]
+    draw_image_from_colour_grid(iteration,partie,image_svg)
+    print("ok")

Challenge3/code/regressionImage.py

@@ -5,12 +5,12 @@ from sklearn import linear_model
 from PIL import Image
 import matplotlib.pyplot as plt
 
-pixel_x=[4036,1988,553,660,706]
-pixel_y=[2790,2579,2686,1319,684]
-latitude=[34.966380,36.834287,35.898757,48.275379,54.415694]
-longitude=[34.068130,11.116444,-5.284306,-4.582430,-4.365422]
-listePixels=[[pixel_x[i],pixel_y[i]] for i in range(5)]
-listeLatLong=[[latitude[i],longitude[i]] for i in range(5)]
+pixel_x=[4036,1988,553,660,706,720,1672,2920,3976,2344,2728]
+pixel_y=[2790,2579,2686,1319,684,1320,568,2504,2256,3072,240]
+latitude=[34.966380,36.834287,35.898757,48.275379,54.415694,48.480773,56.300218,37.550021,39.389509,32.928013,58.837378]
+longitude=[34.068130,11.116444,-5.284306,-4.582430,-4.365422,-4.614974,9.251141,22.098190,32.671718,13.178906,25.607752]
+listePixels=[[pixel_x[i],pixel_y[i]] for i in range(11)]
+listeLatLong=[[latitude[i],longitude[i]] for i in range(11)]
 
 reg = linear_model.LinearRegression()
 reg.fit(listePixels, listeLatLong)