Add Facebox teach service

homeassistant/components/image_processing/facebox.py

@@ -10,20 +10,26 @@
 import requests
 import voluptuous as vol
 
-from homeassistant.const import ATTR_NAME
+from homeassistant.const import (
+    ATTR_ENTITY_ID, ATTR_NAME)
 from homeassistant.core import split_entity_id
 import homeassistant.helpers.config_validation as cv
 from homeassistant.components.image_processing import (
     PLATFORM_SCHEMA, ImageProcessingFaceEntity, ATTR_CONFIDENCE, CONF_SOURCE,
-    CONF_ENTITY_ID, CONF_NAME)
+    CONF_ENTITY_ID, CONF_NAME, DOMAIN)
 from homeassistant.const import (CONF_IP_ADDRESS, CONF_PORT)
 
 _LOGGER = logging.getLogger(__name__)
 
 ATTR_BOUNDING_BOX = 'bounding_box'
+ATTR_CLASSIFIER = 'classifier'
 ATTR_IMAGE_ID = 'image_id'
 ATTR_MATCHED = 'matched'
 CLASSIFIER = 'facebox'
+DATA_FACEBOX = 'facebox_classifiers'
+EVENT_CLASSIFIER_TEACH = 'image_processing.teach_classifier'
+FILE_PATH = 'file_path'
+SERVICE_TEACH_FACE = 'facebox_teach_face'
 TIMEOUT = 9
 
 
@@ -32,6 +38,12 @@
     vol.Required(CONF_PORT): cv.port,
 })
 
+SERVICE_TEACH_SCHEMA = vol.Schema({
+    vol.Optional(ATTR_ENTITY_ID): cv.entity_ids,
+    vol.Required(ATTR_NAME): cv.string,
+    vol.Required(FILE_PATH): cv.string,
+})
+
 
 def encode_image(image):
     """base64 encode an image stream."""
@@ -63,26 +75,74 @@ def parse_faces(api_faces):
     return known_faces
 
 
+def post_image(url, image):
+    """Post an image to the classifier."""
+    try:
+        response = requests.post(
+            url,
+            json={"base64": encode_image(image)},
+            timeout=TIMEOUT
+            )
+        return response
+    except requests.exceptions.ConnectionError:
+        _LOGGER.error("ConnectionError: Is %s running?", CLASSIFIER)
+
+
+def valid_file_path(file_path):
+    """Check that a file_path points to a valid file."""
+    try:
+        cv.isfile(file_path)
+        return True
+    except vol.Invalid:
+        _LOGGER.error(
+            "%s error: Invalid file path: %s", CLASSIFIER, file_path)
+        return False
+
+
 def setup_platform(hass, config, add_devices, discovery_info=None):
     """Set up the classifier."""
+    if DATA_FACEBOX not in hass.data:
+        hass.data[DATA_FACEBOX] = []
+
     entities = []
     for camera in config[CONF_SOURCE]:
-        entities.append(FaceClassifyEntity(
+        facebox = FaceClassifyEntity(
             config[CONF_IP_ADDRESS],
             config[CONF_PORT],
             camera[CONF_ENTITY_ID],
-            camera.get(CONF_NAME)
-        ))
+            camera.get(CONF_NAME))
+        entities.append(facebox)
+        hass.data[DATA_FACEBOX].append(facebox)
     add_devices(entities)
 
+    def service_handle(service):
+        """Handle for services."""
+        entity_ids = service.data.get('entity_id')
+
+        classifiers = hass.data[DATA_FACEBOX]
+        if entity_ids:
+            classifiers = [c for c in classifiers if c.entity_id in entity_ids]
+
+        for classifier in classifiers:
+            name = service.data.get(ATTR_NAME)
+            file_path = service.data.get(FILE_PATH)
+            classifier.teach(name, file_path)
+
+    hass.services.register(
+        DOMAIN,
+        SERVICE_TEACH_FACE,
+        service_handle,
+        schema=SERVICE_TEACH_SCHEMA)
+
 
 class FaceClassifyEntity(ImageProcessingFaceEntity):
     """Perform a face classification."""
 
     def __init__(self, ip, port, camera_entity, name=None):
         """Init with the API key and model id."""
         super().__init__()
-        self._url = "http://{}:{}/{}/check".format(ip, port, CLASSIFIER)
+        self._url_check = "http://{}:{}/{}/check".format(ip, port, CLASSIFIER)
+        self._url_teach = "http://{}:{}/{}/teach".format(ip, port, CLASSIFIER)
         self._camera = camera_entity
         if name:
             self._name = name
@@ -94,28 +154,54 @@ def __init__(self, ip, port, camera_entity, name=None):
 
     def process_image(self, image):
         """Process an image."""
-        response = {}
-        try:
-            response = requests.post(
-                self._url,
-                json={"base64": encode_image(image)},
-                timeout=TIMEOUT
-                ).json()
-        except requests.exceptions.ConnectionError:
-            _LOGGER.error("ConnectionError: Is %s running?", CLASSIFIER)
-            response['success'] = False
-
-        if response['success']:
-            total_faces = response['facesCount']
-            faces = parse_faces(response['faces'])
-            self._matched = get_matched_faces(faces)
-            self.process_faces(faces, total_faces)
+        response = post_image(self._url_check, image)
+        if response is not None:
+            response_json = response.json()
+            if response_json['success']:
+                total_faces = response_json['facesCount']
+                faces = parse_faces(response_json['faces'])
+                self._matched = get_matched_faces(faces)
+                self.process_faces(faces, total_faces)
 
         else:
             self.total_faces = None
             self.faces = []
             self._matched = {}
 
+    def teach(self, name, file_path):
+        """Teach classifier a face name."""
+        if (not self.hass.config.is_allowed_path(file_path)
+                or not valid_file_path(file_path)):
+            return
+        with open(file_path, 'rb') as open_file:
+            response = requests.post(
+                self._url_teach,
+                data={ATTR_NAME: name, 'id': file_path},
+                files={'file': open_file})
+
+        if response.status_code == 200:
+            self.hass.bus.fire(
+                EVENT_CLASSIFIER_TEACH, {
+                    ATTR_CLASSIFIER: CLASSIFIER,
+                    ATTR_NAME: name,
+                    FILE_PATH: file_path,
+                    'success': True,
+                    'message': None
+                    })
+
+        elif response.status_code == 400:
+            _LOGGER.warning(
+                "%s teaching of file %s failed with message:%s",
+                CLASSIFIER, file_path, response.text)
+            self.hass.bus.fire(
+                EVENT_CLASSIFIER_TEACH, {
+                    ATTR_CLASSIFIER: CLASSIFIER,
+                    ATTR_NAME: name,
+                    FILE_PATH: file_path,
+                    'success': False,
+                    'message': response.text
+                    })
+
     @property
     def camera_entity(self):
         """Return camera entity id from process pictures."""
@@ -131,4 +217,5 @@ def device_state_attributes(self):
         """Return the classifier attributes."""
         return {
             'matched_faces': self._matched,
+            'total_matched_faces': len(self._matched),
             }

homeassistant/components/image_processing/services.yaml

@@ -6,3 +6,16 @@ scan:
     entity_id:
       description: Name(s) of entities to scan immediately.
       example: 'image_processing.alpr_garage'
+
+facebox_teach_face:
+  description: Teach facebox a face using a file.
+  fields:
+    entity_id:
+      description: The facebox entity to teach.
+      example: 'image_processing.facebox'
+    name:
+      description: The name of the face to teach.
+      example: 'my_name'
+    file_path:
+      description: The path to the image file.
+      example: '/images/my_image.jpg'