[WIP] Fix opencv (#7864)
* Updates to opencv image processor * Remove opencv hub * Requirements * Remove extra line * Fix linting errors * Indentation * Requirements * Linting * Check for import on platform setup * Remove opencv requirement * Linting * fix style * fix lint
This commit is contained in:
Teagan Glenn
Pascal Vizeli
parent
482db94372
commit
97f62cfb78
3 changed files with 124 additions and 220 deletions
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@ -7,22 +7,56 @@ https://home-assistant.io/components/image_processing.opencv/
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from datetime import timedelta
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import logging
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import requests
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import voluptuous as vol
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from homeassistant.core import split_entity_id
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from homeassistant.components.image_processing import (
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ImageProcessingEntity, PLATFORM_SCHEMA)
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from homeassistant.components.opencv import (
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ATTR_MATCHES, CLASSIFIER_GROUP_CONFIG, CONF_CLASSIFIER, CONF_ENTITY_ID,
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CONF_NAME, process_image)
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CONF_SOURCE, CONF_ENTITY_ID, CONF_NAME, PLATFORM_SCHEMA,
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ImageProcessingEntity)
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import homeassistant.helpers.config_validation as cv
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REQUIREMENTS = ['numpy==1.12.0']
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_LOGGER = logging.getLogger(__name__)
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DEPENDENCIES = ['opencv']
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ATTR_MATCHES = 'matches'
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ATTR_TOTAL_MATCHES = 'total_matches'
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CASCADE_URL = \
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'https://raw.githubusercontent.com/opencv/opencv/master/data/' + \
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'lbpcascades/lbpcascade_frontalface.xml'
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CONF_CLASSIFIER = 'classifer'
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CONF_FILE = 'file'
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CONF_MIN_SIZE = 'min_size'
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CONF_NEIGHBORS = 'neighbors'
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CONF_SCALE = 'scale'
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DEFAULT_CLASSIFIER_PATH = 'lbp_frontalface.xml'
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DEFAULT_MIN_SIZE = (30, 30)
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DEFAULT_NEIGHBORS = 4
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DEFAULT_SCALE = 1.1
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DEFAULT_TIMEOUT = 10
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SCAN_INTERVAL = timedelta(seconds=2)
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PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend(CLASSIFIER_GROUP_CONFIG)
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PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend({
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vol.Optional(CONF_CLASSIFIER, default=None): {
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cv.string: vol.Any(
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cv.isfile,
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vol.Schema({
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vol.Required(CONF_FILE): cv.isfile,
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vol.Optional(CONF_SCALE, DEFAULT_SCALE): float,
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vol.Optional(CONF_NEIGHBORS, DEFAULT_NEIGHBORS):
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cv.positive_int,
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vol.Optional(CONF_MIN_SIZE, DEFAULT_MIN_SIZE):
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vol.Schema((int, int))
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})
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)
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}
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})
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def _create_processor_from_config(hass, camera_entity, config):
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@ -37,41 +71,63 @@ def _create_processor_from_config(hass, camera_entity, config):
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return processor
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def _get_default_classifier(dest_path):
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"""Download the default OpenCV classifier."""
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_LOGGER.info('Downloading default classifier')
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req = requests.get(CASCADE_URL, stream=True)
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with open(dest_path, 'wb') as fil:
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for chunk in req.iter_content(chunk_size=1024):
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if chunk: # filter out keep-alive new chunks
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fil.write(chunk)
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def setup_platform(hass, config, add_devices, discovery_info=None):
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"""Set up the OpenCV image processing platform."""
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if discovery_info is None:
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try:
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# Verify opencv python package is preinstalled
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# pylint: disable=unused-import,unused-variable
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import cv2 # noqa
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except ImportError:
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_LOGGER.error("No opencv library found! " +
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"Install or compile for your system " +
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"following instructions here: " +
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"http://opencv.org/releases.html")
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return
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devices = []
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for camera_entity in discovery_info[CONF_ENTITY_ID]:
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devices.append(
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_create_processor_from_config(hass, camera_entity, discovery_info))
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entities = []
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if config[CONF_CLASSIFIER] is None:
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dest_path = hass.config.path(DEFAULT_CLASSIFIER_PATH)
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_get_default_classifier(dest_path)
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config[CONF_CLASSIFIER] = {
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'Face': dest_path
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}
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add_devices(devices)
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for camera in config[CONF_SOURCE]:
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entities.append(OpenCVImageProcessor(
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hass, camera[CONF_ENTITY_ID], camera.get(CONF_NAME),
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config[CONF_CLASSIFIER]
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))
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add_devices(entities)
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class OpenCVImageProcessor(ImageProcessingEntity):
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"""Representation of an OpenCV image processor."""
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def __init__(self, hass, camera_entity, name, classifier_configs):
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def __init__(self, hass, camera_entity, name, classifiers):
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"""Initialize the OpenCV entity."""
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self.hass = hass
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self._camera_entity = camera_entity
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self._name = name
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self._classifier_configs = classifier_configs
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if name:
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self._name = name
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else:
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self._name = "OpenCV {0}".format(
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split_entity_id(camera_entity)[1])
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self._classifiers = classifiers
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self._matches = {}
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self._total_matches = 0
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self._last_image = None
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@property
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def last_image(self):
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"""Return the last image."""
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return self._last_image
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@property
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def matches(self):
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"""Return the matches it found."""
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return self._matches
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@property
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def camera_entity(self):
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"""Return camera entity id from process pictures."""
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@ -85,20 +141,54 @@ class OpenCVImageProcessor(ImageProcessingEntity):
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@property
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def state(self):
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"""Return the state of the entity."""
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total_matches = 0
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for group in self._matches.values():
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total_matches += len(group)
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return total_matches
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return self._total_matches
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@property
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def state_attributes(self):
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"""Return device specific state attributes."""
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return {
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ATTR_MATCHES: self._matches
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ATTR_MATCHES: self._matches,
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ATTR_TOTAL_MATCHES: self._total_matches
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}
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def process_image(self, image):
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"""Process the image."""
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self._last_image = image
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self._matches = process_image(
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image, self._classifier_configs, False)
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import cv2 # pylint: disable=import-error
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import numpy
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# pylint: disable=no-member
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cv_image = cv2.imdecode(numpy.asarray(bytearray(image)),
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cv2.IMREAD_UNCHANGED)
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for name, classifier in self._classifiers.items():
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scale = DEFAULT_SCALE
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neighbors = DEFAULT_NEIGHBORS
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min_size = DEFAULT_MIN_SIZE
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if isinstance(classifier, dict):
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path = classifier[CONF_FILE]
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scale = classifier.get(CONF_SCALE, scale)
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neighbors = classifier.get(CONF_NEIGHBORS, neighbors)
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min_size = classifier.get(CONF_MIN_SIZE, min_size)
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else:
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path = classifier
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# pylint: disable=no-member
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cascade = cv2.CascadeClassifier(path)
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detections = cascade.detectMultiScale(
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cv_image,
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scaleFactor=scale,
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minNeighbors=neighbors,
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minSize=min_size)
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matches = {}
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total_matches = 0
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regions = []
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# pylint: disable=invalid-name
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for (x, y, w, h) in detections:
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regions.append((int(x), int(y), int(w), int(h)))
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total_matches += 1
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matches[name] = regions
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self._matches = matches
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self._total_matches = total_matches
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@ -1,183 +0,0 @@
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"""
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Support for OpenCV image/video processing.
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For more details about this component, please refer to the documentation at
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https://home-assistant.io/components/opencv/
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"""
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import logging
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import os
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import voluptuous as vol
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import requests
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from homeassistant.const import (
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CONF_NAME,
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CONF_ENTITY_ID,
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CONF_FILE_PATH
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)
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from homeassistant.helpers import (
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discovery,
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config_validation as cv,
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)
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REQUIREMENTS = ['opencv-python==3.2.0.6', 'numpy==1.12.0']
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_LOGGER = logging.getLogger(__name__)
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ATTR_MATCHES = 'matches'
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BASE_PATH = os.path.realpath(__file__)
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CASCADE_URL = \
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'https://raw.githubusercontent.com/opencv/opencv/master/data/' +\
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'lbpcascades/lbpcascade_frontalface.xml'
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CONF_CLASSIFIER = 'classifier'
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CONF_COLOR = 'color'
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CONF_GROUPS = 'classifier_group'
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CONF_MIN_SIZE = 'min_size'
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CONF_NEIGHBORS = 'neighbors'
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CONF_SCALE = 'scale'
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DATA_CLASSIFIER_GROUPS = 'classifier_groups'
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DEFAULT_COLOR = (255, 255, 0)
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DEFAULT_CLASSIFIER_PATH = 'lbp_frontalface.xml'
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DEFAULT_NAME = 'OpenCV'
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DEFAULT_MIN_SIZE = (30, 30)
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DEFAULT_NEIGHBORS = 4
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DEFAULT_SCALE = 1.1
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DOMAIN = 'opencv'
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CLASSIFIER_GROUP_CONFIG = {
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vol.Required(CONF_CLASSIFIER): vol.All(
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cv.ensure_list,
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[vol.Schema({
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vol.Optional(CONF_COLOR, default=DEFAULT_COLOR):
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vol.Schema((int, int, int)),
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vol.Optional(CONF_FILE_PATH, default=None): cv.isfile,
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vol.Optional(CONF_NAME, default=DEFAULT_NAME):
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cv.string,
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vol.Optional(CONF_MIN_SIZE, default=DEFAULT_MIN_SIZE):
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vol.Schema((int, int)),
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vol.Optional(CONF_NEIGHBORS, default=DEFAULT_NEIGHBORS):
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cv.positive_int,
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vol.Optional(CONF_SCALE, default=DEFAULT_SCALE):
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float
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})]),
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vol.Required(CONF_ENTITY_ID): cv.entity_ids,
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vol.Optional(CONF_NAME, default=DEFAULT_NAME): cv.string,
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}
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CLASSIFIER_GROUP_SCHEMA = vol.Schema(CLASSIFIER_GROUP_CONFIG)
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CONFIG_SCHEMA = vol.Schema({
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DOMAIN: vol.Schema({
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vol.Required(CONF_GROUPS): vol.All(
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cv.ensure_list,
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[CLASSIFIER_GROUP_SCHEMA]
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),
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})
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}, extra=vol.ALLOW_EXTRA)
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# NOTE:
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# pylint cannot find any of the members of cv2, using disable=no-member
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# to pass linting
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def cv_image_to_bytes(cv_image):
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"""Convert OpenCV image to bytes."""
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import cv2 # pylint: disable=import-error
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# pylint: disable=no-member
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encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 90]
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# pylint: disable=no-member
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success, data = cv2.imencode('.jpg', cv_image, encode_param)
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if success:
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return data.tobytes()
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return None
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def cv_image_from_bytes(image):
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"""Convert image bytes to OpenCV image."""
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import cv2 # pylint: disable=import-error
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import numpy
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# pylint: disable=no-member
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return cv2.imdecode(numpy.asarray(bytearray(image)), cv2.IMREAD_UNCHANGED)
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def process_image(image, classifier_group, is_camera):
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"""Process the image given a classifier group."""
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import cv2 # pylint: disable=import-error
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import numpy
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# pylint: disable=no-member
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cv_image = cv2.imdecode(numpy.asarray(bytearray(image)),
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cv2.IMREAD_UNCHANGED)
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group_matches = {}
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for classifier_config in classifier_group:
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classifier_path = classifier_config[CONF_FILE_PATH]
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classifier_name = classifier_config[CONF_NAME]
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color = classifier_config[CONF_COLOR]
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scale = classifier_config[CONF_SCALE]
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neighbors = classifier_config[CONF_NEIGHBORS]
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min_size = classifier_config[CONF_MIN_SIZE]
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# pylint: disable=no-member
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classifier = cv2.CascadeClassifier(classifier_path)
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detections = classifier.detectMultiScale(cv_image,
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scaleFactor=scale,
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minNeighbors=neighbors,
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minSize=min_size)
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regions = []
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# pylint: disable=invalid-name
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for (x, y, w, h) in detections:
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if is_camera:
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# pylint: disable=no-member
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cv2.rectangle(cv_image,
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(x, y),
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(x + w, y + h),
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color,
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2)
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else:
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regions.append((int(x), int(y), int(w), int(h)))
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group_matches[classifier_name] = regions
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if is_camera:
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return cv_image_to_bytes(cv_image)
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else:
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return group_matches
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def setup(hass, config):
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"""Set up the OpenCV platform entities."""
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default_classifier = hass.config.path(DEFAULT_CLASSIFIER_PATH)
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if not os.path.isfile(default_classifier):
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_LOGGER.info('Downloading default classifier')
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req = requests.get(CASCADE_URL, stream=True)
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with open(default_classifier, 'wb') as fil:
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for chunk in req.iter_content(chunk_size=1024):
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if chunk: # filter out keep-alive new chunks
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fil.write(chunk)
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for group in config[DOMAIN][CONF_GROUPS]:
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grp = {}
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for classifier, config in group.items():
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config = dict(config)
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if config[CONF_FILE_PATH] is None:
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config[CONF_FILE_PATH] = default_classifier
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grp[classifier] = config
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discovery.load_platform(hass, 'image_processing', DOMAIN, grp)
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return True
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@ -387,7 +387,7 @@ netdisco==1.0.1
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# homeassistant.components.sensor.neurio_energy
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neurio==0.3.1
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# homeassistant.components.opencv
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# homeassistant.components.image_processing.opencv
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numpy==1.12.0
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# homeassistant.components.google
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@ -399,9 +399,6 @@ oemthermostat==1.1
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# homeassistant.components.media_player.onkyo
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onkyo-eiscp==1.1
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# homeassistant.components.opencv
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# opencv-python==3.2.0.6
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# homeassistant.components.sensor.openevse
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openevsewifi==0.4
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