core/homeassistant/components/sighthound/image_processing.py

"""Person detection using Sighthound cloud service."""
import io
import logging
from pathlib import Path

from PIL import Image, ImageDraw, UnidentifiedImageError
import simplehound.core as hound
import voluptuous as vol

from homeassistant.components.image_processing import (
    CONF_ENTITY_ID,
    CONF_NAME,
    CONF_SOURCE,
    PLATFORM_SCHEMA,
    ImageProcessingEntity,
)
from homeassistant.const import ATTR_ENTITY_ID, CONF_API_KEY
from homeassistant.core import split_entity_id
import homeassistant.helpers.config_validation as cv
import homeassistant.util.dt as dt_util
from homeassistant.util.pil import draw_box

_LOGGER = logging.getLogger(__name__)

EVENT_PERSON_DETECTED = "sighthound.person_detected"

ATTR_BOUNDING_BOX = "bounding_box"
ATTR_PEOPLE = "people"
CONF_ACCOUNT_TYPE = "account_type"
CONF_SAVE_FILE_FOLDER = "save_file_folder"
CONF_SAVE_TIMESTAMPTED_FILE = "save_timestamped_file"
DATETIME_FORMAT = "%Y-%m-%d_%H:%M:%S"
DEV = "dev"
PROD = "prod"

PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend(
    {
        vol.Required(CONF_API_KEY): cv.string,
        vol.Optional(CONF_ACCOUNT_TYPE, default=DEV): vol.In([DEV, PROD]),
        vol.Optional(CONF_SAVE_FILE_FOLDER): cv.isdir,
        vol.Optional(CONF_SAVE_TIMESTAMPTED_FILE, default=False): cv.boolean,
    }
)


def setup_platform(hass, config, add_entities, discovery_info=None):
    """Set up the platform."""
    # Validate credentials by processing image.
    api_key = config[CONF_API_KEY]
    account_type = config[CONF_ACCOUNT_TYPE]
    api = hound.cloud(api_key, account_type)
    try:
        api.detect(b"Test")
    except hound.SimplehoundException as exc:
        _LOGGER.error("Sighthound error %s setup aborted", exc)
        return

    save_file_folder = config.get(CONF_SAVE_FILE_FOLDER)
    if save_file_folder:
        save_file_folder = Path(save_file_folder)

    entities = []
    for camera in config[CONF_SOURCE]:
        sighthound = SighthoundEntity(
            api,
            camera[CONF_ENTITY_ID],
            camera.get(CONF_NAME),
            save_file_folder,
            config[CONF_SAVE_TIMESTAMPTED_FILE],
        )
        entities.append(sighthound)
    add_entities(entities)


class SighthoundEntity(ImageProcessingEntity):
    """Create a sighthound entity."""

    def __init__(
        self, api, camera_entity, name, save_file_folder, save_timestamped_file
    ):
        """Init."""
        self._api = api
        self._camera = camera_entity
        if name:
            self._name = name
        else:
            camera_name = split_entity_id(camera_entity)[1]
            self._name = f"sighthound_{camera_name}"
        self._state = None
        self._last_detection = None
        self._image_width = None
        self._image_height = None
        self._save_file_folder = save_file_folder
        self._save_timestamped_file = save_timestamped_file

    def process_image(self, image):
        """Process an image."""
        detections = self._api.detect(image)
        people = hound.get_people(detections)
        self._state = len(people)
        if self._state > 0:
            self._last_detection = dt_util.now().strftime(DATETIME_FORMAT)

        metadata = hound.get_metadata(detections)
        self._image_width = metadata["image_width"]
        self._image_height = metadata["image_height"]
        for person in people:
            self.fire_person_detected_event(person)
        if self._save_file_folder and self._state > 0:
            self.save_image(image, people, self._save_file_folder)

    def fire_person_detected_event(self, person):
        """Send event with detected total_persons."""
        self.hass.bus.fire(
            EVENT_PERSON_DETECTED,
            {
                ATTR_ENTITY_ID: self.entity_id,
                ATTR_BOUNDING_BOX: hound.bbox_to_tf_style(
                    person["boundingBox"], self._image_width, self._image_height
                ),
            },
        )

    def save_image(self, image, people, directory):
        """Save a timestamped image with bounding boxes around targets."""
        try:
            img = Image.open(io.BytesIO(bytearray(image))).convert("RGB")
        except UnidentifiedImageError:
            _LOGGER.warning("Sighthound unable to process image, bad data")
            return
        draw = ImageDraw.Draw(img)

        for person in people:
            box = hound.bbox_to_tf_style(
                person["boundingBox"], self._image_width, self._image_height
            )
            draw_box(draw, box, self._image_width, self._image_height)

        latest_save_path = directory / f"{self._name}_latest.jpg"
        img.save(latest_save_path)

        if self._save_timestamped_file:
            timestamp_save_path = directory / f"{self._name}_{self._last_detection}.jpg"
            img.save(timestamp_save_path)
            _LOGGER.info("Sighthound saved file %s", timestamp_save_path)

    @property
    def camera_entity(self):
        """Return camera entity id from process pictures."""
        return self._camera

    @property
    def name(self):
        """Return the name of the sensor."""
        return self._name

    @property
    def should_poll(self):
        """Return the polling state."""
        return False

    @property
    def state(self):
        """Return the state of the entity."""
        return self._state

    @property
    def unit_of_measurement(self):
        """Return the unit of measurement."""
        return ATTR_PEOPLE

    @property
    def extra_state_attributes(self):
        """Return the attributes."""
        if not self._last_detection:
            return {}
        return {"last_person": self._last_detection}