Hi,
I am currently in the process of integrating my rooted Roborock S5 into Home Assistant. Because I really dislike the solutions using a server within Docker Container to display a live map in Home Assistant, I wrote a python script, which takes the map data provided by the Valetudos /api/map/latest endpoint and generates the map out of it. It lacks some polish but now does what it should.
Since Home Assistant is also Python based I was thinking if it might be worth integrating the script into the vacuum/xiaomi Home Assistant component as a sensor/camera, so that external solutions would become unnecessary? Is this viable? I had a look into the git repo of Home Assistant and I was somewhat overwhelmed, so I would need help to do that. In the meantime I leave the script here, so tell me what you think.
import io
import json
import requests
from PIL import Image, ImageDraw
import cairosvg
HOST = "192.168.1.43" # IP of the vacuum
SCALE_FACTOR = 4 # Map scaling
CROP = False # Crop map size to content
DRAW_PATH = True
DRAW_NO_GO_AREAS = True
COLOR_FLOOR = (0, 118, 255)
COLOR_OBSTACLE_WEAK = (0, 0, 0)
COLOR_OBSTACLE_STRONG = (82, 174, 255)
COLOR_PATH = (255, 255, 255)
COLOR_NOGO_BORDER = (255, 0, 0)
COLOR_NOGO_AREA = (255, 0, 0, 128)
COLOR_BACKGROUND = (255, 0, 0, 0)
def transfrom_coords(coord, offset_from):
coord /= 50
coord -= offset_from
coord *= SCALE_FACTOR
return round(coord)
def main():
r = requests.get("http://%s/api/map/latest" % HOST)
json_file = json.loads(r.text)
# map data
dimensions = json_file["image"]["dimensions"]
floor = json_file["image"]["pixels"]["floor"]
obstacle_weak = json_file["image"]["pixels"]["obstacle_weak"]
obstacle_strong = json_file["image"]["pixels"]["obstacle_strong"]
no_go_areas = json_file["no_go_areas"]
# robot data
robot = json_file["robot"]
charger = json_file["charger"]
path = json_file["path"]["points"]
position = json_file["image"]["position"]
current_angle = json_file["path"]["current_angle"]
# load image assets
vacuum_byte_obj = io.BytesIO()
charger_byte_obj = io.BytesIO()
cairosvg.svg2png(url="robot-vacuum.svg", write_to=vacuum_byte_obj, scale=10)
vacuum = Image.open(vacuum_byte_obj)
vacuum = vacuum.rotate(360-current_angle) # correct for inverse rotation
cairosvg.svg2png(url="flash.svg", write_to=charger_byte_obj, scale=(0.4 * SCALE_FACTOR))
d_station = Image.open(charger_byte_obj)
# draw map
map = Image.new("RGBA", (dimensions["width"], dimensions["height"]), color=COLOR_BACKGROUND)
draw = ImageDraw.Draw(map)
max_x = 0
max_y = 0
min_x = dimensions["width"]
min_y = dimensions["height"]
for coordinate in floor:
# store min/max coordinates for cropping
if CROP:
max_x = coordinate[0] if max_x < coordinate[0] else max_x
max_y = coordinate[1] if max_y < coordinate[1] else max_y
min_x = coordinate[0] if min_x > coordinate[0] else min_x
min_y = coordinate[1] if min_y > coordinate[1] else min_y
draw.point((coordinate[0],coordinate[1]), fill=COLOR_FLOOR)
for coordinate in obstacle_weak:
draw.point((coordinate[0],coordinate[1]), fill=COLOR_OBSTACLE_WEAK)
for coordinate in obstacle_strong:
draw.point((coordinate[0],coordinate[1]), fill=COLOR_OBSTACLE_STRONG)
map = map.resize((dimensions["width"]*SCALE_FACTOR, dimensions["height"]*SCALE_FACTOR), Image.NEAREST)
draw = ImageDraw.Draw(map)
# no go zones
if DRAW_NO_GO_AREAS:
for no_go_area in no_go_areas:
def draw_line (i1, i2, i3, i4):
draw.line((transfrom_coords(no_go_area[i1], position["left"]),
transfrom_coords(no_go_area[i2], position["top"]),
transfrom_coords(no_go_area[i3], position["left"]),
transfrom_coords(no_go_area[i4], position["top"])),
fill=COLOR_NOGO_BORDER,
width=round(0.5 * SCALE_FACTOR))
# draw box borders
draw_line(0,1,2,3)
draw_line(2,3,4,5)
draw_line(4,5,6,7)
draw_line(6,7,0,1)
# create rectange on an overlay to preserve map data below; then merge it
overlay = Image.new('RGBA', map.size, COLOR_BACKGROUND)
draw = ImageDraw.Draw(overlay)
draw.rectangle(((transfrom_coords(no_go_area[0], position["left"]),
transfrom_coords(no_go_area[1], position["top"])),
(transfrom_coords(no_go_area[4], position["left"]),
transfrom_coords(no_go_area[5], position["top"]))),
fill=COLOR_NOGO_AREA)
map = Image.alpha_composite(map, overlay)
draw = ImageDraw.Draw(map)
# Vacuum cleaning path
if DRAW_PATH and len(path) > 1:
old_x = transfrom_coords(path[0][0], position["left"])
old_y = transfrom_coords(path[0][1], position["top"])
for x in range(len(path)):
if (x == len(path)-1):
break
new_x = transfrom_coords(path[x + 1][0], position["left"])
new_y = transfrom_coords(path[x + 1][1], position["top"])
draw.line((old_x, old_y, new_x, new_y), fill=COLOR_PATH, width=round(0.25*SCALE_FACTOR))
old_x = new_x
old_y = new_y
# paste docking station and vacuum; occluding items after non-occluding ones
map.paste(d_station,
(transfrom_coords(charger[0], position["left"]) - round(d_station.width / 2),
transfrom_coords(charger[1], position["top"]) - round(d_station.height / 2)),
d_station)
vacuum.thumbnail((8*SCALE_FACTOR, 8*SCALE_FACTOR), Image.ANTIALIAS) # downscale for image quality
map.paste(vacuum,
(transfrom_coords(robot[0], position["left"]) - round(vacuum.width / 2),
transfrom_coords(robot[1], position["top"]) - round(vacuum.height / 2)),
vacuum)
if CROP:
map = map.crop((min_x*SCALE_FACTOR,
min_y*SCALE_FACTOR,
max_x*SCALE_FACTOR,
max_y*SCALE_FACTOR))
map.save("map.png")
if __name__ == "__main__":
main()
