From 707bd1a5c99e3b9998a1aca292a902deaf32d470 Mon Sep 17 00:00:00 2001 From: Robin Cole Date: Tue, 12 Nov 2019 05:11:14 +0000 Subject: [PATCH] Use entity name in saved images --- README.md | 15 +-- .../deepstack_object/image_processing.py | 90 ++++++------------ docs/object_detail.png | Bin 60510 -> 61831 bytes docs/object_usage.png | Bin 1234331 -> 1033312 bytes 4 files changed, 37 insertions(+), 68 deletions(-) diff --git a/README.md b/README.md index ebf7976..259030d 100644 --- a/README.md +++ b/README.md @@ -28,7 +28,9 @@ docker run -e VISION-DETECTION=True -e API-KEY="Mysecretkey" -v localstorage:/da ``` ## Usage of this component -The `deepstack_object` component adds an `image_processing` entity where the state of the entity is the total number of `target` objects that are above a `confidence` threshold which has a default value of 80%. The time of the last detection of the `target` object is in the `last detection` attribute. The type and number of objects (of any confidence) is listed in the `summary` attributes. Optionally the processed image can be saved to disk. If `save_file_folder` is configured two images are created, one with the filename of format `deepstack_latest_{target}.jpg` which is over-written on each new detection of the `target`, and another with a unique filename including the timestamp. An event `image_processing.object_detected` is fired for each object detected. If you are a power user with advanced needs such as zoning detections or you want to track multiple object types, you will need to use the `image_processing.object_detected` events. +The `deepstack_object` component adds an `image_processing` entity where the state of the entity is the total number of `target` objects that are above a `confidence` threshold which has a default value of 80%. The time of the last detection of the `target` object is in the `last detection` attribute. The type and number of objects (of any confidence) is listed in the `summary` attributes. Optionally the processed image can be saved to disk. If `save_file_folder` is configured two images are created, one with the filename of format `deepstack_object_{source name}_latest_{target}.jpg` which is over-written on each new detection of the `target`, and another with a unique filename including the timestamp. An event `image_processing.object_detected` is fired for each object detected. If you are a power user with advanced needs such as zoning detections or you want to track multiple object types, you will need to use the `image_processing.object_detected` events. + +**Note** that by default the component will **not** automatically scan images, but requires you to call the `image_processing.scan` service e.g. using an automation triggered by motion. Alternativley, periodic scanning can be enabled by configuring a `scan_interval`. ## Home Assistant setup Place the `custom_components` folder in your configuration directory (or add its contents to an existing `custom_components` folder). Then configure object detection. **Important:** It is necessary to configure only a single camera per `deepstack_object` entity. If you want to process multiple cameras, you will therefore need multiple `deepstack_object` `image_processing` entities. **Note** that at we can use `scan_interval` to (optionally) limit computation, [as described here](https://www.home-assistant.io/components/image_processing/#scan_interval-and-optimising-resources). @@ -41,10 +43,11 @@ image_processing: ip_address: localhost port: 5000 api_key: Mysecretkey - save_file_folder: /config/www/deepstack_person_images + # scan_interval: 30 # Optional, in seconds + save_file_folder: /config/www/ source: - entity_id: camera.local_file - name: person_detector + name: deepstack_person_detector ``` Configuration variables: @@ -121,12 +124,12 @@ The `box` coordinates and the box center (`centroid`) can be used to determine w * The centroid is in `(x,y)` coordinates where `(0,0)` is the top left hand corner of the image and `(1,1)` is the bottom right corner of the image. -## Displaying the `deepstack_latest_{target}.jpg` file -It easy to display the `deepstack_latest_{target}.jpg` image with a [local_file](https://www.home-assistant.io/components/local_file/) camera. An example configuration is: +## Displaying the deepstack latest jpg file +It easy to display the `deepstack_object_{source name}_latest_{target}.jpg` image with a [local_file](https://www.home-assistant.io/components/local_file/) camera. An example configuration is: ```yaml camera: - platform: local_file - file_path: /config/www/deepstack/deepstack_latest_person.jpg + file_path: /config/www/deepstack_object_local_file_latest_person.jpg name: deepstack_latest_person ``` diff --git a/custom_components/deepstack_object/image_processing.py b/custom_components/deepstack_object/image_processing.py index df28ff1..0065048 100644 --- a/custom_components/deepstack_object/image_processing.py +++ b/custom_components/deepstack_object/image_processing.py @@ -7,38 +7,39 @@ import base64 import datetime import io -from typing import Tuple import json import logging import os - -from PIL import Image, ImageDraw +from datetime import timedelta +from typing import Tuple import requests -import voluptuous as vol +from PIL import Image, ImageDraw import deepstack.core as ds - -import homeassistant.util.dt as dt_util -from homeassistant.const import ATTR_ENTITY_ID, ATTR_NAME -from homeassistant.core import split_entity_id import homeassistant.helpers.config_validation as cv +import homeassistant.util.dt as dt_util +import voluptuous as vol from homeassistant.components.image_processing import ( - PLATFORM_SCHEMA, - ImageProcessingEntity, ATTR_CONFIDENCE, - CONF_SOURCE, CONF_ENTITY_ID, CONF_NAME, + CONF_SOURCE, DOMAIN, + PLATFORM_SCHEMA, + ImageProcessingEntity, + draw_box, ) from homeassistant.const import ( + ATTR_ENTITY_ID, + ATTR_NAME, CONF_IP_ADDRESS, CONF_PORT, HTTP_BAD_REQUEST, HTTP_OK, HTTP_UNAUTHORIZED, ) +from homeassistant.core import split_entity_id _LOGGER = logging.getLogger(__name__) @@ -46,6 +47,7 @@ CONF_TARGET = "target" CONF_TIMEOUT = "timeout" CONF_SAVE_FILE_FOLDER = "save_file_folder" +DATETIME_FORMAT = "%Y-%m-%d %H:%M:%S" DEFAULT_API_KEY = "" DEFAULT_TARGET = "person" DEFAULT_TIMEOUT = 10 @@ -55,6 +57,8 @@ CENTROID = "centroid" FILE = "file" OBJECT = "object" +RED = (255, 0, 0) +SCAN_INTERVAL = timedelta(days=365) # NEVER SCAN. PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend( @@ -102,41 +106,6 @@ def get_box_centroid(box: Tuple) -> Tuple: return centroid -def draw_box( - draw: ImageDraw, - box: Tuple[float, float, float, float], - img_width: int, - img_height: int, - text: str = "", - color: Tuple[int, int, int] = (255, 255, 0), -) -> None: - """ - Draw a bounding box on and image. - The bounding box is defined by the tuple (y_min, x_min, y_max, x_max) - where the coordinates are floats in the range [0.0, 1.0] and - relative to the width and height of the image. - For example, if an image is 100 x 200 pixels (height x width) and the bounding - box is `(0.1, 0.2, 0.5, 0.9)`, the upper-left and bottom-right coordinates of - the bounding box will be `(40, 10)` to `(180, 50)` (in (x,y) coordinates). - """ - - line_width = 5 - y_min, x_min, y_max, x_max = box - (left, right, top, bottom) = ( - x_min * img_width, - x_max * img_width, - y_min * img_height, - y_max * img_height, - ) - draw.line( - [(left, top), (left, bottom), (right, bottom), (right, top), (left, top)], - width=line_width, - fill=color, - ) - if text: - draw.text((left + line_width, abs(top - line_width)), text, fill=color) - - def setup_platform(hass, config, add_devices, discovery_info=None): """Set up the classifier.""" ip_address = config.get(CONF_IP_ADDRESS) @@ -192,7 +161,7 @@ def __init__( self._name = name else: camera_name = split_entity_id(camera_entity)[1] - self._name = "{} {}".format(CLASSIFIER, camera_name) + self._name = "deepstack_object_{}".format(camera_name) self._state = None self._targets_confidences = [] self._predictions = {} @@ -231,7 +200,7 @@ def process_image(self, image): ) ) if self._state > 0: - self._last_detection = dt_util.now() + self._last_detection = dt_util.now().strftime(DATETIME_FORMAT) self._summary = ds.get_objects_summary(self._predictions) self.fire_prediction_events(self._predictions, self._confidence) if hasattr(self, "_save_file_folder") and self._state > 0: @@ -257,20 +226,19 @@ def save_image(self, image, predictions, target, directory): box, self._image_width, self._image_height, - str(prediction_confidence), + text=str(prediction_confidence), + color=RED, ) - latest_save_path = directory + "deepstack_latest_{}.jpg".format(target) - timestamp_save_path = directory + "deepstack_{}_{}.jpg".format( - target, self._last_detection.strftime("%Y-%m-%d-%H-%M-%S") + latest_save_path = directory + "{}_latest_{}.jpg".format(self._name, target) + timestamp_save_path = directory + "{}_{}_{}.jpg".format( + self._name, target, self._last_detection ) - try: - img.save(latest_save_path) - img.save(timestamp_save_path) - self.fire_saved_file_event(timestamp_save_path) - _LOGGER.info("Saved bounding box image to %s", timestamp_save_path) - except Exception as exc: - _LOGGER.error("Error saving bounding box image : %s", exc) + + img.save(latest_save_path) + img.save(timestamp_save_path) + self.fire_saved_file_event(timestamp_save_path) + _LOGGER.info("Saved bounding box image to %s", timestamp_save_path) def fire_prediction_events(self, predictions, confidence): """Fire events based on predictions if above confidence threshold.""" @@ -323,8 +291,6 @@ def device_state_attributes(self): """Return device specific state attributes.""" attr = {} if self._last_detection: - attr[ - "last_{}_detection".format(self._target) - ] = self._last_detection.strftime("%Y-%m-%d %H:%M:%S") + attr["last_{}_detection".format(self._target)] = self._last_detection attr["summary"] = self._summary return attr diff --git a/docs/object_detail.png b/docs/object_detail.png index 68c3c4482b2a8af486b4dc5282df12fa76f00573..ab068dd30e5f478f03c7df6ff23c347ca4243aab 100644 GIT binary patch literal 61831 zcmeFYWmH_t_UMa-CLu@&?h+t4B&2bd-~@uZdqd;yPH=Y!1cE~#xVr>8K!Uplx8M!D zMfN`D?E8QBeR<=K`{}^w(W`6KtW`B@R@JOozZI^eAocVy@nZx8gs0MP#g!2dkfsq3 zkRO8{0V(auuaXcDFyt)7#FV7P#3+>^bVX27s$eI@qCAuQfG*M_|5CLIf`dw+h4-!&Q+P+byoLd?%OLZv_=gc50ppUX zaQSWDp{Gx~=V8uP_KgsY>&4;|KRp(Gx?!m^M21-WAzW%P&4lrB%>ve3WrzuE 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