Roborock Live Map Generator


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 = ""  # IP of the vacuum
SCALE_FACTOR = 4 # Map scaling
CROP = False # Crop map size to content

COLOR_FLOOR = (0, 118, 255)
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 =
    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 =

    # draw map
    map ="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
        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"])),
                          width=round(0.5 * SCALE_FACTOR))

            # draw box borders

            # create rectange on an overlay to preserve map data below; then merge it
            overlay ='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"]))),
            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):
            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
              (transfrom_coords(charger[0], position["left"]) - round(d_station.width / 2),
               transfrom_coords(charger[1], position["top"]) - round(d_station.height / 2)),
    vacuum.thumbnail((8*SCALE_FACTOR, 8*SCALE_FACTOR), Image.ANTIALIAS) # downscale for image quality
              (transfrom_coords(robot[0], position["left"]) - round(vacuum.width / 2),
               transfrom_coords(robot[1], position["top"]) - round(vacuum.height / 2)),

    if CROP:
        map = map.crop((min_x*SCALE_FACTOR,

if __name__ == "__main__":
1 Like

I dislike the docker solution either :) Is that a live-map data in valetudos /api/map/lastest ?
What is your plan to run this scripts in real-time?

I am in process of creating of creating a camera + support for it in my card (Xiaomi Vacuum Interactive Map Card). Camera part is almost done, now I work on the lovelace card

You can check out camera here:

No, that is just a reference to the vacuum robot svg, which is used to mark the position of the robot on the map. Also the generation of the map is not realtime. Every time you call the script it retrieves the data from the endpoint and generates a png of the map. If you then want an updated map you need to call the script again (which certainly can be changed).

I saw you project and I really like your card, especially the integrated zoning part :slight_smile:

But for me my current interest lies mostly on just having a camera component for Valetudo enabled Xiaomi robots (e.g. like with the consumable sensors which are already present) integrated in Home Assistant in order to have map support in Home Assistant right out of the box without the need of adding external dependencies. Not sure if your project aims for that and if it ever will ship with Home Assistant itself.

Camera I have linked above does (almost) exactly what you need, but without Valetudo.
Paths are also extracted, but they will be drawn in my lovelace card.

Hi @FriedrichNietzsche , Is Valetudos /api/map/latest stable in your environment? I’ve got “No MAP Data” too often. I’ve no idea why.


I’m trying to implement this with a Gen 1 rooted vacuum.
I don’t get any errors during startup, so I’m assuming the component can connect to the vacuum OK.

However, my camera entity is not working even after the vacuum finished cleaning.

I get the following error when trying to access the camera:

Traceback (most recent call last):
  File "/usr/local/lib/python3.7/site-packages/aiohttp/", line 418, in start
    resp = await task
  File "/usr/local/lib/python3.7/site-packages/aiohttp/", line 458, in _handle
    resp = await handler(request)
  File "/usr/local/lib/python3.7/site-packages/aiohttp/", line 119, in impl
    return await handler(request)
  File "/usr/src/homeassistant/homeassistant/components/http/", line 39, in real_ip_middleware
    return await handler(request)
  File "/usr/src/homeassistant/homeassistant/components/http/", line 73, in ban_middleware
    return await handler(request)
  File "/usr/src/homeassistant/homeassistant/components/http/", line 127, in auth_middleware
    return await handler(request)
  File "/usr/src/homeassistant/homeassistant/components/http/", line 125, in handle
    result = await result
  File "/usr/src/homeassistant/homeassistant/components/camera/", line 491, in get
    return await self.handle(request, camera)
  File "/usr/src/homeassistant/homeassistant/components/camera/", line 526, in handle
    return await camera.handle_async_mjpeg_stream(request)
  File "/usr/src/homeassistant/homeassistant/components/camera/", line 391, in handle_async_mjpeg_stream
    return await self.handle_async_still_stream(request, self.frame_interval)
  File "/usr/src/homeassistant/homeassistant/components/camera/", line 382, in handle_async_still_stream
    request, self.async_camera_image, self.content_type, interval
  File "/usr/src/homeassistant/homeassistant/components/camera/", line 197, in async_get_still_stream
    img_bytes = await image_cb()
  File "/usr/src/homeassistant/homeassistant/components/camera/", line 377, in async_camera_image
    return await self.hass.async_add_executor_job(self.camera_image)
  File "/usr/local/lib/python3.7/concurrent/futures/", line 57, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/config/custom_components/xiaomi_vacuum_map/", line 58, in camera_image
  File "/usr/src/homeassistant/homeassistant/util/", line 239, in wrapper
    result = method(*args, **kwargs)
  File "/config/custom_components/xiaomi_vacuum_map/", line 64, in _camera_image
  File "/config/custom_components/xiaomi_vacuum_map/", line 227, in update
  File "/config/custom_components/xiaomi_vacuum_map/", line 120, in extract
    with + "/map_data.tar.gz", "r:gz") as tar:
  File "/usr/local/lib/python3.7/", line 1591, in open
    return func(name, filemode, fileobj, **kwargs)
  File "/usr/local/lib/python3.7/", line 1637, in gzopen
    fileobj = GzipFile(name, mode + "b", compresslevel, fileobj)
  File "/usr/local/lib/python3.7/", line 168, in __init__
    fileobj = self.myfileobj =, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: '/tmp/hass_xiaomi_map_data/map_data.tar.gz'

Anything I can check? Cheers.

I assume you are using Home Assistant (former Currently this camera is not compatible with it

Thanks for clarifying. I’m using the Homeassistant Supervised installation method on Ubuntu Server.
Any plans on making it available for this type of installation?

Some time ago I have created an issue for that, you can follow it here.

Thanks. I ended up implementing the solution here for the time being: