feat: implemented native authentication with pwa using auth0 API

.gitignore

@@ -20,7 +20,9 @@ _mdwriter.cson
 **/ambianic_edge.egg-info/
 ambianic-debug2.sh
 config.yaml.local
+premium.yaml
 /.ropeproject
 tmp*.jpg
 src/Ambianic.egg-info/**
-/docs/dist
+config.yaml
+/docs/dist

ambianic-start.sh

@@ -23,4 +23,4 @@ docker run -it --rm \
   $USB_ARG \
   ambianic/ambianic-edge:dev /workspace/src/run-dev.sh
 # on Mac, --net=host doesnt work as expected
-#  --net=host \
+#  --net=host \

build/requirements.txt

@@ -1,8 +1,9 @@
+pytest-httpserver==1.0.0
 absl-py>=0.7.1
 appdirs>=1.4.3
 asn1crypto>=0.24.0
 astor>=0.8.0
-asttokens>=1.1.13  
+asttokens>=1.1.13
 beautifulsoup4>=4.7.1
 blinker>=1.4
 certifi>=2018.8.24
@@ -23,6 +24,7 @@ itsdangerous>=0.24
 Jinja2>=2.10.1
 numpy>=1.16.2
 oauthlib>=2.1.0
+httpretty==1.0.5
 Pillow>=5.4.1
 pyOpenSSL>=19.0.0
 PyYAML>=5.1.2

dev/dev-config.yaml

@@ -0,0 +1,98 @@
+######################################
+#  Ambianic main configuration file  #
+######################################
+version: '2020.12.11'
+
+# path to the data directory
+data_dir: ./data
+
+# Set logging level to one of DEBUG, INFO, WARNING, ERROR
+logging:
+  file: ./data/ambianic-log.txt
+  level: INFO
+  # set a less noisy log level for the console output
+  # console_level: WARNING
+
+# Store notifications provider configuration
+# see https://github.com/caronc/apprise#popular-notification-services for syntax examples
+# notifications:
+#   catch_all_email:
+#     include_attachments: true
+#     providers:
+#       - mailto://userid:[email protected]
+#   alert_fall:
+#     providers:
+#       - mailto://userid:[email protected]
+#       - json://hostname/a/path/to/post/to
+
+# Pipeline event timeline configuration
+timeline:
+  event_log: ./data/timeline-event-log.yaml
+
+# Cameras and other input data sources
+# Using Home Assistant conventions to ease upcoming integration
+sources:
+
+#  # direct support for raspberry picamera
+#  picamera:
+#    uri: picamera
+#    type: video
+#    live: true
+#
+#  # local video device integration example
+#  webcam:
+#    uri: /dev/video0
+#    type: video
+#    live: true
+
+  recorded_cam_feed:
+    uri: file:///workspace/tests/pipeline/avsource/test2-cam-person1.mkv
+    type: video
+#    live: true
+
+ai_models:
+  image_detection:
+    model:
+      tflite: ai_models/mobilenet_ssd_v2_coco_quant_postprocess.tflite
+      edgetpu: ai_models/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite
+    labels: ai_models/coco_labels.txt
+  face_detection:
+    model:
+      tflite: ai_models/mobilenet_ssd_v2_face_quant_postprocess.tflite
+      edgetpu: ai_models/mobilenet_ssd_v2_face_quant_postprocess_edgetpu.tflite
+    labels: ai_models/coco_labels.txt
+    top_k: 2
+  fall_detection:
+    model:
+      tflite: ai_models/posenet_mobilenet_v1_100_257x257_multi_kpt_stripped.tflite
+      edgetpu: ai_models/posenet_mobilenet_v1_075_721_1281_quant_decoder_edgetpu.tflite
+    labels: ai_models/pose_labels.txt
+
+# A named pipeline defines an ordered sequence of operations
+# such as reading from a data source, AI model inference, saving samples and others.
+pipelines:
+   # Pipeline names could be descriptive, e.g. front_door_watch or entry_room_watch.
+   area_watch:
+     - source: recorded_cam_feed
+     - detect_objects: # run ai inference on the input data
+        ai_model: image_detection
+        confidence_threshold: 0.6
+        # Watch for any of the labels listed below. The labels must be from the model trained label set.
+        # If no labels are listed, then watch for all model trained labels.
+        label_filter:
+          - person
+          - car
+     - save_detections: # save samples from the inference results
+        positive_interval: 300 # how often (in seconds) to save samples with ANY results above the confidence threshold
+        idle_interval: 6000 # how often (in seconds) to save samples with NO results above the confidence threshold
+     - detect_falls: # look for falls
+        ai_model: fall_detection
+        confidence_threshold: 0.6
+     - save_detections: # save samples from the inference results
+        positive_interval: 10
+        idle_interval: 600000
+#        notify: # notify a thirdy party service
+#          providers:
+#            - alert_fall
+
+

src/ambianic/__init__.py

@@ -3,11 +3,17 @@
 from dynaconf.utils.boxing import DynaBox
 from typing import Union
 import importlib_metadata as metadata
+from argparse import ArgumentParser
+
+parser = ArgumentParser()
+parser.add_argument("-c", "--config", help="Specify config YAML file location")
+
+args, unknown = parser.parse_known_args()
 
 DEFAULT_WORK_DIR: str = '/workspace'
 DEFAULT_DATA_DIR: str = './data'
 
-DEFAULT_CONFIG_FILE: str = 'config.yaml'
+DEFAULT_CONFIG_FILE: str = args.config or 'config.yaml'
 DEFAULT_SECRETS_FILE: str = 'secrets.yaml'
 
 __CONFIG_FILE: str = None
@@ -25,7 +31,8 @@ def get_secrets_file() -> str:
     return os.path.join(get_work_dir(), DEFAULT_SECRETS_FILE)
 
 
-def __merge_secrets(config: Union[Dynaconf, DynaBox], src_config: Dynaconf = None):
+def __merge_secrets(config: Union[Dynaconf, DynaBox],
+                    src_config: Dynaconf = None):
     if src_config is None:
         src_config = config
     for key, val in config.items():

src/ambianic/notification.py

@@ -4,13 +4,52 @@
 import apprise
 import os
 import ambianic
+import pkg_resources
+import yaml
+from requests import post
 
 log = logging.getLogger(__name__)
 
 UI_BASEURL = "https://ui.ambianic.ai"
 
+
+def sendCloudNotification(data):
+    # r+ flag causes a permission error
+    try:
+        premiumFile = pkg_resources.resource_filename(
+            "ambianic.webapp", "premium.yaml")
+
+        with open(premiumFile, "r") as file:
+            configFile = yaml.safe_load(file)
+
+            userId = configFile['credentials']["USER_AUTH0_ID"]
+            endpoint = configFile['credentials']["NOTIFICATION_ENDPOINT"]
+            if (userId):
+                return post(
+                    url='{0}/notification'.format(endpoint),
+                    json={
+                        'userId': userId,
+                        'notification': {
+                            'title': 'Ambianic.ai New {0} event'.format(
+                                data['label']),
+                            'message': 'New {0} detected with a {1} confidence level'.format(
+                                data['label'],
+                                data['confidence']),
+                        }})
+
+    except FileNotFoundError as err:
+        log.warning("Error locating file: {}".format(err))
+
+    except Exception as error:
+        log.warning("Error sending email: {}".format(str(error)))
+
+
 class Notification:
-    def __init__(self, event:str = "detection", data:dict = {}, providers:list = ["all"]):
+    def __init__(
+            self,
+            event: str = "detection",
+            data: dict = {},
+            providers: list = ["all"]):
         self.event: str = event
         self.providers: list = providers
         self.title: str = None
@@ -36,17 +75,16 @@ def __init__(self, config: dict = None):
             for provider in providers:
                 if not self.apobj.add(provider, tag=name):
                     log.warning(
-                        "Failed to add notification provider: %s=%s" 
-                            % (name, provider)
+                        "Failed to add notification provider: %s=%s"
+                        % (name, provider)
                     )
 
     def send(self, notification: Notification):
-
         templates = self.config.get("templates", {})
 
         title = notification.title
         if title is None:
-            title = templates.get("title", "[Ambianic.ai] New ${event} event" )
+            title = templates.get("title", "[Ambianic.ai] New ${event} event")
 
         message = notification.message
         if message is None:
@@ -63,9 +101,14 @@ def send(self, notification: Notification):
 
         template_args = {
             "event_type": notification.event,
-            "event": notification.data.get("label", notification.event),
-            "event_details_url": "%s/%s" % (UI_BASEURL, notification.data.get("id", ""))
-        }
+            "event": notification.data.get(
+                "label",
+                notification.event),
+            "event_details_url": "%s/%s" %
+            (UI_BASEURL,
+             notification.data.get(
+                 "id",
+                 ""))}
         template_args = {**template_args, **notification.data}
 
         for key, value in template_args.items():
@@ -76,22 +119,23 @@ def send(self, notification: Notification):
 
         for provider in notification.providers:
             cfg = self.config.get(provider, None)
-            if cfg is None:
-                log.warning("Skip unknown provider %s" % provider)
-                continue
-
-            include_attachments = cfg.get("include_attachments", False)
-            ok = self.apobj.notify(
-                message, 
-                title=title,
-                tag=provider, 
-                attach=attachments if include_attachments else [],
-            )
-            if ok:
-                log.debug(
-                    "Sent notification for %s to %s" % 
-                    (notification.event, provider)
+
+            if cfg:
+                include_attachments = cfg.get("include_attachments", False)
+                ok = self.apobj.notify(
+                    message,
+                    title=title,
+                    tag=provider,
+                    attach=attachments if include_attachments else [],
                 )
+                if ok:
+                    log.debug(
+                        "Sent notification for %s to %s" %
+                        (notification.event, provider)
+                    )
+                else:
+                    log.warning("Error sending notification for %s to %s" %
+                                (notification.event, provider))
             else:
-                log.warning("Error sending notification for %s to %s" %
-                          (notification.event, provider))
+                log.warning("Skip unknown provider %s" % provider)
+                continue

src/ambianic/pipeline/store.py

@@ -1,14 +1,14 @@
 """Pipeline sample storage elements."""
 import logging
-import datetime
 import pathlib
 import json
 import uuid
+import datetime
 from typing import Iterable
 import numpy as np
 from ambianic import DEFAULT_DATA_DIR
 from ambianic.pipeline import PipeElement
-from ambianic.notification import Notification, NotificationHandler
+from ambianic.notification import Notification, NotificationHandler, sendCloudNotification
 
 log = logging.getLogger(__name__)
 
@@ -66,11 +66,13 @@ def __init__(self,
         ii = idle_interval
         self._idle_interval = datetime.timedelta(seconds=ii)
         self._time_latest_saved_idle = self._time_latest_saved_detection
-        
+
         # setup notification handler
         self.notification = None
         self.notification_config = notify
-        if self.notification_config is not None and self.notification_config.get("providers"):
+
+        if self.notification_config is not None and self.notification_config.get(
+                "providers"):
             self.notification = NotificationHandler()
 
     def _save_sample(self,
@@ -79,7 +81,6 @@ def _save_sample(self,
                      thumbnail=None,
                      inference_result=None,
                      inference_meta=None):
-
         time_prefix = inf_time.strftime("%Y%m%d-%H%M%S.%f%z-{suffix}.{fext}")
         image_file = time_prefix.format(suffix='image', fext='jpg')
         image_path = self._output_directory / image_file
@@ -101,6 +102,7 @@ def _save_sample(self,
             'inference_result': inference_result,
             'inference_meta': inference_meta
         }
+
         image.save(image_path)
         thumbnail.save(thumbnail_path)
         # save samples to local disk
@@ -139,7 +141,7 @@ def process_sample(self, **sample) -> Iterable[dict]:
                     # let's save it if its been longer than
                     # the user specified positive_interval
                     if now - self._time_latest_saved_detection >= \
-                      self._positive_interval:
+                            self._positive_interval:
                         self._save_sample(inf_time=now,
                                           image=image,
                                           thumbnail=thumbnail,
@@ -151,7 +153,7 @@ def process_sample(self, **sample) -> Iterable[dict]:
                     # let's save a sample if its been longer than
                     #  the user specified idle_interval
                     if now - self._time_latest_saved_idle >= \
-                      self._idle_interval:
+                            self._idle_interval:
                         self._save_sample(inf_time=now,
                                           image=image,
                                           thumbnail=thumbnail,
@@ -171,18 +173,25 @@ def process_sample(self, **sample) -> Iterable[dict]:
                 yield processed_sample
 
     def notify(self, save_json: dict):
-        if self.notification is None:
-            return
-        log.debug("Sending notification(s)..")
         # TODO extract inference data
+        if save_json['inference_result'] is None:
+            return
+
         for inference_result in save_json['inference_result']:
             data = {
                 'id': save_json['id'],
                 'label': inference_result['label'],
                 'confidence': inference_result['confidence'],
                 'datetime': save_json['datetime'],
             }
-            notification = Notification(data=data, providers=self.notification_config["providers"])
+
+            sendCloudNotification(data=data)
+
+            if self.notification is None:
+                return
+
+            notification = Notification(
+                data=data, providers=self.notification_config["providers"])
             self.notification.send(notification)