Tidied code

Author: matthew-jones-uk

.gitignore

@@ -123,4 +123,7 @@ dmypy.json
 ### Python Patch ###
 .venv/
 
-# End of https://www.gitignore.io/api/python
+# End of https://www.gitignore.io/api/python
+
+# Visual Studio Code
+.vscode/

TapWork.py

@@ -5,23 +5,13 @@
 import cv2
 import copy
 
-
-
-taps = [(29,29),(10,10)]
-houses = [[4,(10,10)],[7,(29,29)],[8,(18,6)],[15,(12,16)],[6,[23,20]],[7,[6,19]]]
-
-
-
-
-
 def get_taps_demand(taps,houses):
     tap_demand = []
     houses_tap = []
     for tap in taps:
         tap_demand.append(0)
 
     for house in houses:
-        # print(house)
         lowest_distance = 99999999999999999
         house_tap = 0
         housex = house[1][0]
@@ -38,9 +28,6 @@ def get_taps_demand(taps,houses):
 
     for tap in houses_tap:
         tap_demand[tap[0]]+=tap[1]
-
-    # print(houses_tap)
-    # print(tap_demand)
     return tap_demand
 
 def work_done(distance):
@@ -61,44 +48,13 @@ def total_demand(tap_demands):
         total+=tap
     return total
 
-# taps_d = get_taps_demand(taps,houses)
-# print(total_differnces(taps_d))
-#
-
-
-# tick = 0
-# for x1 in range(15):
-#     print(tick/810000)
-#     for y1 in (range(30)):
-#         for x2 in (range(30)):
-#             for y2 in (range(30)):
-#                 # print(x1,y1,x2,y2)
-#                 tick += 1
-#                 taps = [[x1, y1], [x2, y2]]
-#                 tap_demand = get_taps_demand(taps, houses)
-#                 total_differnce = total_demand(tap_demand)
-#                 if total_differnce < min_total_differnces:
-#                     happy_taps = []
-#                     happy_taps.append(taps)
-#                     min_total_differnces = total_differnce
-#                 if total_differnce == min_total_differnces:
-#                     happy_taps.append(taps)
-
-
-# print(happy_taps)
-# print(min_total_differnces)
-
-taps = [[18,16],[29,29]]
-
-def draw_network(houses,taps,image = "null"):
+def draw_network(houses,taps,image):
     pos = {}
     names = []
     edges = []
     for i in range(len(houses)):
         pos[str(houses[i][0])]=(houses[i][1][0],houses[i][1][1])
         edges.append((str(houses[i][0]),str(houses[i][0])))
-    print(pos)
-    print(edges)
 
     G = nx.Graph()
     G.add_edges_from(edges)
@@ -109,48 +65,23 @@ def draw_network(houses,taps,image = "null"):
     edges = []
     for i in range(len(taps)):
         pos[(i+1)]=(taps[i][0],taps[i][1])
-        print(pos)
         edges.append((i+1,i+1))
-    print(pos)
-    print(edges)
 
     G = nx.Graph()
     G.add_edges_from(edges)
 
     nx.draw_networkx(G, pos=pos, node_color='b',node_size=30,fontsize=50)
-    # G.add_edges_from([(1, 1), (2, 2)])
-    # pos = {1: (taps[0][0], taps[0][1]), 2: (taps[1][0], taps[1][1])}
-    # #
-    # nx.draw_networkx(G, pos=pos, node_color='b')
-    print(image)
-    if image != "null":
-        img = cv2.imread(image)
-        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-        plt.imshow(img)
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    plt.imshow(image)
     plt.show()
 
-
-# import copy
-#
-# taps = [(10, 16), (18, 6), (19, 19)]
-# demands = get_taps_demand(taps,houses)
-# print(demands)
-#
-# print(total_demand(demands))
-#
-# taps = [(10, 16), (10,10), (19, 19)]
-# demands = get_taps_demand(taps,houses)
-# print(demands)
-#
-# print(total_demand(demands))
-
 def total(demands):
     totalval = 0
     for demand in demands:
         totalval += demand
     return totalval
 
-def greedy_brute(houses,amount_of_taps,grid_size,image="null"):
+def greedy_brute(houses,amount_of_taps,grid_size,image):
     tick = 0
     total_tick = amount_of_taps*grid_size[0]*grid_size[1]
     happy_taps = []
@@ -182,67 +113,4 @@ def greedy_brute(houses,amount_of_taps,grid_size,image="null"):
 
                 min_total_differnces = total_differnce
         stored_taps.append(happy_taps[-1])
-    draw_network(houses, stored_taps,image)
-
-
-
-
-def brute_tap_position(houses,amount_of_taps,grid_size,image="null"):
-
-
-    min_total_differnces = 999999999999999
-    happy_taps = []
-    possible_coords = []
-
-    for x in range(grid_size[0]+1):
-        for y in range(grid_size[1]+1):
-            possible_coords.append((x, y))
-
-
-
-
-
-    pairs = list(itertools.combinations_with_replacement(possible_coords,amount_of_taps))
-    print(pairs[-1])
-    total_ticks = (len(list(copy.copy(pairs))))
-    #total_ticks = (grid_size[0]**(2*amount_of_taps))
-    print(total_ticks)
-    tick = 0
-
-    for pair in pairs:
-
-        tick += 1
-        if tick % (int(total_ticks/1000)) == 0:
-            print((tick / total_ticks)*100)
-        taps = pair
-        tap_demand = get_taps_demand(taps, houses)
-        total_differnce = total_demand(tap_demand)
-
-
-        if total_differnce == min_total_differnces:
-            happy_taps.append(taps)
-
-
-        if total_differnce < min_total_differnces:
-            happy_taps = []
-            happy_taps.append(taps)
-            min_total_differnces = total_differnce
-
-    print(happy_taps)
-
-    for gtaps in happy_taps:
-        draw_network(houses, gtaps,image=image)
-
-
-
-# #brute_tap_position(houses,3,(20,20))
-#
-# houses = [(133.0, (130, 282)), (168.5, (55, 272)), (106.0, (72, 262)), (301.5, (86, 230)), (480.5, (14, 222)), (657.0, (93, 200)), (394.5, (108, 155)), (84.0, (228, 116)), (117.0, (115, 114)), (274.0, (44, 116)), (561.0,(212, 88)), (194.0, (80, 50)), (295.5, (124, 15))]
-#
-# taps = [(103, 159), (168, 65), (56, 240), (107, 29), (214, 92), (44, 116), (96, 218),(14, 222)]
-# draw_network(houses,taps,image="resized.jpg")
-
-
-
-
-
+    draw_network(houses, stored_taps,image)

address of the file location

@@ -1,16 +1,9 @@
 # import the necessary packages
-import argparse
 import imutils
 import cv2
 
 # construct the argument parse and parse the arguments
-def get_contour_nodes():
-    args = {}
-    args["image"] = "black_and_white.png"
-
-    # load the image, convert it to grayscale, blur it slightly,
-    # and threshold it
-    image = cv2.imread(args["image"])
+def get_contour_nodes(image):
     height, width, channels = image.shape
     gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     blurred = cv2.GaussianBlur(gray, (5, 5), 0)
@@ -27,23 +20,11 @@ def get_contour_nodes():
     for c in cnts:
         # compute the center of the contour
         try:
-            print(cv2.contourArea(c))
             if cv2.contourArea(c) > 40:
                 M = cv2.moments(c)
                 cX = int(M["m10"] / M["m00"])
                 cY = int(M["m01"] / M["m00"])
                 nodes.append([cv2.contourArea(c), [cX, cY]])
-
-                # draw the contour and center of the shape on the image
-                #cv2.drawContours(image, [c], -1, (0, 0, 255), 2)
-                #cv2.circle(image, (cX, cY), 7, (255, 0, 0), -1)
-                #cv2.putText(image, "center", (cX - 20, cY - 20),
-                 #   cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2)
-
-                # show the image
-                #cv2.imshow("Image", image)
-
-
         except:
             pass
-    return nodes
+    return nodes

bigo_nodes.txt

@@ -1,13 +1,17 @@
 import resize
-import messingcolour
+import recolour
 import contours
 import TapWork
 import map_downloader
+import cv2
+import numpy as np
 
-map_downloader.download_patch((13.323964, -15.9257),'AgqByPum4K6T5wlV3oIAhSDvFHVRuoPs6cwipRdvprWtmvqld0poyLI54AP0e6HI')
+response = map_downloader.download_patch((13.623299, -15.192386),)
+image_array = np.asarray(bytearray(response.content), dtype=np.uint8)
+map_image = cv2.imdecode(image_array, -1)
 max_size = 200
-height, width = resize.resize('downloaded.png',max_size)
-print(height,width)
-messingcolour.find_silver()
-houses = contours.get_contour_nodes()
-TapWork.greedy_brute(houses,5,(height,width),image='resized.jpg')
+resized_image = resize.resize(map_image,max_size)
+height, width, _ = resized_image.shape
+recoloured_image = recolour.find_silver(resized_image)
+houses = contours.get_contour_nodes(recoloured_image)
+TapWork.greedy_brute(houses,5,(height,width),resized_image)

contours.py

@@ -6,9 +6,4 @@ def download_patch(lat_long,api_key,zoom=19,dimensions=(1000,1000),file_format='
     URL = ('https://dev.virtualearth.net/REST/v1/Imagery/Map/Aerial/{},{}/'
             '{}?mapSize={},{}&format={}&key={}').format(latitude,longitude,zoom,x,y,file_format,api_key)
     response = requests.get(URL)
-    f = open('downloaded.png', 'wb')
-    f.write(response.content)
-    return response
-
-#file = download_patch((13.338863, -15.922574),'AgqByPum4K6T5wlV3oIAhSDvFHVRuoPs6cwipRdvprWtmvqld0poyLI54AP0e6HI').content
-
+    return response

downloaded.png

@@ -0,0 +1,20 @@
+import cv2
+import numpy
+
+def find_silver(image):
+    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+    h,s,v = cv2.split(hsv)
+
+    rgb = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
+
+    mask = cv2.inRange(rgb, (150,160,160), (255, 255, 255))
+    image = cv2.bitwise_and(image, image, mask=mask)
+
+    for w in range(image.shape[0]):
+        for h in range(image.shape[1]):
+            # checks if not pure black
+            if(all(rgb != 0 for rgb in image[w][h])):
+                # makes pixel completely white
+                for colour in range(image.shape[2]):
+                    image[w][h][colour] = 255
+    return image

google.jpg

@@ -1,13 +1,7 @@
 import cv2
 
 def resize(image,max_size):
-    img = cv2.imread(image)
-    height, width, channels = img.shape
-    print(height,width)
+    height, width, channels = image.shape
     scale = max_size/(max(height,width))
-    small = cv2.resize(img, (0,0), fx=scale, fy=scale)
-    height,width,channels = small.shape
-
-    cv2.imwrite('resized.jpg',small)
-
-    return height,width
+    resized_image = cv2.resize(image, (0,0), fx=scale, fy=scale)
+    return resized_image