updating for individual projecet

Main.py

@@ -6,7 +6,8 @@ import collections
 import alg
 from models.dumpster import trash
 from models.Garbagetruck import GarbageTruck
-
+import numbering
+from sklearn.datasets import load_digits
 
 #heuristics for finding the closest dumpster
 def closest(GT, D):
@@ -96,6 +97,16 @@ a = createDumpstersAndDump(20,size+1)
 TheDump = np.reshape(a[-1], (1, 2))
 a = np.reshape(a[:-1], (size, 2))
 
+
+#Patryk Krawiec subproject part
+digitsy=np.load("Ytest.npy")
+digitsx=np.load("Xtest.npy")
+images_and_labels=list(zip(digitsx,digitsy))
+num,xnum,ynum=numbering.num(20,images_and_labels)
+
+paying_customers=num[3:]
+paying_customers = list(map(int, paying_customers))
+
 #initiating the coordinates for the garbage truck
 GT = GarbageTruck()
 coor = GT.start()
@@ -109,6 +120,8 @@ for i in range(0,size):
     s.throwAway()
     s.colour()
     s.xy = a[i]
+    s.numberx=xnum[i]
+    s.numbery=ynum[i]
     dumpsters.append(s)
 
 #colouring trashcans
@@ -158,14 +171,19 @@ while not done:
             #recognize which dumpster are we visiting
             Xz=np.where(all==x)[0]
             x =[item for item, count in collections.Counter(Xz).items() if count > 1]
-
-            if GT.collectingTrash(dumpsters, x[0]):
+            predicted=numbering.pred(dumpsters[x[0]].numberx,dumpsters[x[0]].numbery)
+            if(predicted not in paying_customers):
+                print("House number is: ",predicted," but it is not our customer")
+            elif GT.collectingTrash(dumpsters, x[0]):
                 dumpsters[x[0]].empty()
+                print("House number is: ",predicted)
             elif GT.amIFull():
                 print("DUMPSTER TRUCK FULL")
             else:
                 print("No more space for this kind of trash")
 
+
+
     # remove visited dumpster
     a = a[~((a[:,0] ==ZZ[0]) & (a[:,1] ==ZZ[1]))]
     print("Dumpsters left: ",len(a))