def download_image(location_coordinates, tileSystem_level, null_image):
min_latitude, max_latitude, min_longitude, max_longitude = location_coordinates
x1, y1 = TileSystem.LatLong_To_PixelXY(min_latitude, min_longitude,
tileSystem_level)
x2, y2 = TileSystem.LatLong_To_PixelXY(max_latitude, max_longitude,
tileSystem_level)
X1, Y1 = TileSystem.PixelXY_To_TileXY(min(x1, x2), min(y1, y2))
X2, Y2 = TileSystem.PixelXY_To_TileXY(max(x1, x2), max(y1, y2))
success_status = True
mapurl = "http://h0.ortho.tiles.virtualearth.net/tiles/h{0}.jpeg?g=131"
final_image = np.zeros(
((Y2 - Y1 + 1) * TILESIZE, (X2 - X1 + 1) * TILESIZE, 3),
dtype=np.uint8)
start_y = 0
end_y = TILESIZE
start_x = 0
end_x = TILESIZE
for Y in range(Y1, Y2 + 1):
for X in range(X1, X2 + 1):
quadkey = TileSystem.TileXY_To_QuadKey(X, Y, tileSystem_level)
resp = requests.get(mapurl.format(quadkey), stream=True).raw
image = np.asarray(bytearray(resp.read()), dtype="uint8")
image = cv2.imdecode(image, cv2.IMREAD_COLOR)
if (np.equal(image, null_image).all()):
success_status = False
break
final_image[start_y:end_y, start_x:end_x, :] = image
start_x += TILESIZE
end_x += TILESIZE
#cv2.imwrite('image_iter'+str(Y)+str(X)+'.png', image)
start_x = 0
end_x = TILESIZE
start_y += TILESIZE
end_y += TILESIZE
#temp_view = cv2.resize(final_image, (2000, 2000))
#cv2.imwrite('image'+str(Y)+str(X)+'.png', temp_view)
if (not success_status):
break
if (not success_status):
final_image, tileSystem_level = download_image(location_coordinates,
tileSystem_level - 1,
null_image)
return final_image, tileSystem_level
def overlay_ways(coorindates, aerial_image_path):
min_latitude, max_latitude, min_longitude, max_longitude = coorindates
api = overpy.Overpass()
#roadcolor = (255, 0, 0) # blue color
roadthickness = 50
aerial_image = cv2.imread(aerial_image_path)
colors = [(255, 0, 0), (0, 255, 0), (0, 0, 255), (203, 192, 255),
(0, 255, 255), (42, 42, 165), (0, 165, 255), (216, 235, 52)]
# fetch all ways and nodes
result = api.query("""
way(%f, %f, %f, %f) ["highway"];
(._;>;);
out body;
""" % (min_latitude, min_longitude, max_latitude, max_longitude))
tile_level = int(aerial_image_path[-6:-4])
x1, y1 = TileSystem.LatLong_To_PixelXY(min_latitude, min_longitude,
tile_level)
x2, y2 = TileSystem.LatLong_To_PixelXY(max_latitude, max_longitude,
tile_level)
image = np.zeros((abs(y2 - y1), abs(x2 - x1), 3))
start_x = min(x1, x2)
start_y = min(y1, y2)
for way in result.ways:
# print("Name: %s" % way.tags.get("name", "n/a"))
# print(" Highway: %s" % way.tags.get("highway", "n/a"))
# print(" Nodes:")
if 'highway' in way.tags.keys():
prev_nodeX = way.nodes[0].lat
prev_nodeY = way.nodes[0].lon
prev_nodeX, prev_nodeY = TileSystem.LatLong_To_PixelXY(
float(way.nodes[0].lat), float(way.nodes[0].lon), tile_level)
prev_nodeX = prev_nodeX - start_x
prev_nodeY = prev_nodeY - start_y
color = random.choice(colors)
for node in way.nodes[1:]:
current_nodeX, current_nodeY = TileSystem.LatLong_To_PixelXY(
float(node.lat), float(node.lon), tile_level)
current_nodeX = current_nodeX - start_x
current_nodeY = current_nodeY - start_y
image = cv2.line(image, (prev_nodeX, prev_nodeY),
(current_nodeX, current_nodeY), color,
roadthickness)
aerial_image = cv2.line(aerial_image, (prev_nodeX, prev_nodeY),
(current_nodeX, current_nodeY), color,
roadthickness)
prev_nodeX = current_nodeX
prev_nodeY = current_nodeY
cv2.imwrite('network_only.png', image)
resized_image = cv2.resize(image, None, fx=0.2, fy=0.2)
cv2.imwrite('network_only_resized.png', resized_image)
cv2.imwrite('final_result.png', aerial_image)
aerial_resized = cv2.resize(aerial_image, None, fx=0.2, fy=0.2)
cv2.imwrite("final_result_resized.png", aerial_resized)