Maj vio for panda demo

deployment/edge/ansible/README.md

@@ -4,13 +4,27 @@ export LOCAL_VIO_DIR=
 ```
 
 
-### Install sshpass
-https://stackoverflow.com/questions/42835626/ansible-to-use-the-ssh-connection-type-with-passwords-you-must-install-the-s
+### Install sshpass and the requirements
 
+On MacOS, you can install sshpass using brew:
+```bash
+brew install sshpass
 ```
+
+Then install requirements:
+```bash
 pip install -r requirements.txt
 ```
 
+### Find the IP of the edge
+
+Under Ubuntu, you can use the following command to find the IP of the edge
+```bash
+ip a | grep -A 2 'wlx' | grep 'inet ' | awk '{print $2}' | cut -d/ -f1
+```
+
+Then change the IP addresses on the inventory file
+
 ## docker-compose devices
 
 We are adding those devices to be able to trigger capture from 2 cameras connected on the usb port of your edge.

deployment/edge/ansible/files/docker-compose.template.yml

@@ -1,5 +1,3 @@
-version: '3'
-
 services:
   edge_model_serving:
     container_name: edge_model_serving
@@ -32,7 +30,7 @@ services:
       SERVING_MODEL_URL: http://edge_model_serving:8501
       GOOGLE_APPLICATION_CREDENTIALS: /edge_orchestrator/config/secrets/credentials.json
       GCP_BUCKET_NAME: tf-vio-bucket
-      ACTIVE_CONFIG_NAME: marker_classification_with_1_fake_camera
+      ACTIVE_CONFIG_NAME: duck_detector_with_2_usbcamera
 
   edge_interface:
     container_name: edge_interface

deployment/edge/gcp/README.md

@@ -1,3 +1,21 @@
+## Launch edge locally and upload data on GCP
+
+### Service account for edge_orchestrator
+- Create a service account with the roles/storage.admin directly through the GCP UI.
+- Export key json file
+- Store the key file at this location: `edge_orchestrator/config/secrets/credentials.json`
+
+### Set env variables on docker-compose.yml
+
+    API_CONFIG: upload-gcp
+    GOOGLE_APPLICATION_CREDENTIALS: /edge_orchestrator/config/secrets/credentials.json
+    GCP_BUCKET_NAME: <bucket-name>
+
+### Launch VIO
+```shell
+$ make edge_orchestrator
+```
+
 ## Deploy edge on GCP via Kube
 
 Ensure that Terraform has ran before to create the infrastructure.

docker-compose.raspberrypi.yml

@@ -1,5 +1,3 @@
-version: '3'
-
 services:
   edge_db:
     image: webhippie/mongodb:latest-arm32v7

docker-compose.yml

@@ -1,5 +1,3 @@
-version: '3'
-
 services:
   edge_db:
     image: mongo:5.0.2
@@ -34,10 +32,11 @@ services:
       - 8000:8000
     environment:
       EDGE_NAME: vio-edge-1
-      API_CONFIG: docker
+      API_CONFIG: upload-gcp
       SERVING_MODEL_URL: http://edge_model_serving:8501
-      MONGO_DB_URI: mongodb://edge_db:27017/
-      POSTGRES_DB_URI: postgresql://vio:vio@hub_monitoring_db:5432/vio
+      GOOGLE_APPLICATION_CREDENTIALS: /edge_orchestrator/config/secrets/credentials.json
+      GCP_BUCKET_NAME: tf-vio-bucket
+      ACTIVE_CONFIG_NAME: marker_classification_with_1_fake_camera
     profiles: [edge]
 
   hub_labelizer:

edge_model_serving/tflite_serving/Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.8.10-slim
+FROM python:3.8-slim
 
 WORKDIR /tflite_serving
 

edge_model_serving/tflite_serving/Dockerfile.raspberrypi

@@ -1,4 +1,4 @@
-FROM --platform=linux/arm64 arm64v8/python:3.8.10
+FROM --platform=linux/arm64 arm64v8/python:3.8
 
 WORKDIR /tflite_serving
 

edge_orchestrator/.env.template

@@ -1,2 +1,8 @@
-REGISTRY_USERNAME = <your-github-username>
-REGISTRY_PASSWORD = <your-personal-access-token-generated-in-github>
+EDGE_NAME=
+API_CONFIG=
+SERVING_MODEL_URL=
+GOOGLE_APPLICATION_CREDENTIALS=
+GCP_BUCKET_NAME=
+ACTIVE_CONFIG_NAME=
+REGISTRY_USERNAME=<your-github-username>
+REGISTRY_PASSWORD=<your-personal-access-token-generated-in-github>

edge_orchestrator/.python-version

@@ -1 +1 @@
-3.8.10
+3.9

edge_orchestrator/Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.8.16-slim
+FROM python:3.8-slim
 
 WORKDIR /edge_orchestrator
 

edge_orchestrator/Dockerfile.raspberrypi

@@ -1,4 +1,4 @@
-FROM --platform=linux/arm64 arm64v8/python:3.8.16
+FROM --platform=linux/arm64 arm64v8/python:3.8
 #FROM --platform=linux/arm/v7 arm32v7/python:3.9.16-bullseye
 
 WORKDIR /edge_orchestrator

edge_orchestrator/README.md

@@ -7,3 +7,21 @@ The edge_orchestrator orchestrates the following steps as soon as it is triggere
 3. metadata backup
 4. model inference on images
 5. saving results
+
+
+## Common errors
+
+# Error: pg_config executable not found.
+
+Check if pg_config is installed on your system.
+
+```bash
+pg_config --version
+```
+
+If not, install it using the following command:
+
+MacOS:
+```bash
+brew install postgresql
+```

edge_orchestrator/config/inventory.json

@@ -74,6 +74,19 @@
         320
       ],
       "objectness_threshold": 0.3
+    },
+    "duck_detector": {
+      "category": "classification",
+      "version": 1,
+      "class_names": [
+        "OK",
+        "NOK",
+        "NOK2"
+      ],
+      "image_resolution": [
+        224,
+        224
+      ]
     }
   },
   "camera_rules": [
@@ -86,4 +99,4 @@
     "min_threshold_ok_ratio_rule",
     "min_threshold_ko_rule"
   ]
-}
+}

edge_orchestrator/config/station_configs/duck_detector_with_2_usbcamera.json

@@ -0,0 +1,47 @@
+{
+  "name": "duck_detector_2_cams",
+  "cameras": {
+    "camera_id0": {
+      "type": "usb_camera",
+      "source": "/dev/video0",
+      "position": "front",
+      "exposition": 100,
+      "models_graph": {
+        "model_id4": {
+          "name": "duck_detector",
+          "depends_on": []
+        }
+      },
+      "camera_rule": {
+        "name": "expected_label_rule",
+        "parameters": {
+          "expected_label": ["OK"]
+        }
+      }
+    },
+    "camera_id2": {
+      "type": "usb_camera",
+      "source": "/dev/video2",
+      "position": "front",
+      "exposition": 100,
+      "models_graph": {
+        "model_id4": {
+          "name": "duck_detector",
+          "depends_on": []
+        }
+      },
+      "camera_rule": {
+        "name": "expected_label_rule",
+        "parameters": {
+          "expected_label": ["OK"]
+        }
+      }
+    }
+  },
+  "item_rule": {
+    "name": "min_threshold_ko_rule",
+    "parameters": {
+      "threshold": 1
+    }
+  }
+}

edge_orchestrator/edge_orchestrator/api_config.py

@@ -1,9 +1,12 @@
 import os
 
+from dotenv import load_dotenv
+
 from edge_orchestrator import logger
 
 
 def load_config():
+    load_dotenv()
     configuration = os.environ.get("API_CONFIG", "default")
     logger.info(f"App running with configuration: {configuration}")
 

edge_orchestrator/edge_orchestrator/application/trigger_routes.py

@@ -45,8 +45,17 @@ async def upload_job(
     station_config: StationConfig = Depends(get_station_config),
     background_tasks: BackgroundTasks = None,
 ):
-    item = Item.from_nothing()
-    contents = image.file.read()
-    item.binaries = {"0": contents}
-    background_tasks.add_task(uploader.upload, item, station_config.active_config["name"])
-    return {"item_id": item.id}
+    if station_config.active_config is None:
+        return JSONResponse(
+            status_code=403,
+            content={
+                "message": "No active configuration selected! "
+                "Set the active station configuration before triggering the inspection."
+            },
+        )
+    else:
+        item = Item.from_nothing()
+        contents = image.file.read()
+        item.binaries = {"0": contents}
+        background_tasks.add_task(uploader.upload, item, station_config.active_config["name"])
+        return {"item_id": item.id}

edge_orchestrator/edge_orchestrator/domain/use_cases/supervisor.py

@@ -5,7 +5,6 @@
 from pathlib import Path
 from typing import Any, Dict, List, Union
 
-from codecarbon import track_emissions
 from PIL import Image
 
 from edge_orchestrator.api_config import (
@@ -59,9 +58,6 @@ def __init__(
         self.edge_station = edge_station
         self.telemetry_sink = telemetry_sink
 
-    @track_emissions(
-        project_name="save_item_metadata", measure_power_secs=1, log_level="info", output_dir=str(emissions_path)
-    )
     def save_item_metadata(self, fct):
         @functools.wraps(fct)
         async def wrapper(item: Item, *args):
@@ -80,7 +76,6 @@ async def inspect(self, item: Item):
         tasks = OrderedDict()
 
         @self.save_item_metadata
-        @track_emissions(project_name="capture", measure_power_secs=1, log_level="info", output_dir=str(emissions_path))
         async def capture(item: Item):
             if item.binaries is None or len(item.binaries) == 0:
                 cameras_metadata, binaries = self.edge_station.capture()
@@ -89,23 +84,14 @@ async def capture(item: Item):
             check_capture_according_to_config(item, self.station_config.get_cameras())
 
         @self.save_item_metadata
-        @track_emissions(
-            project_name="save_item_binaries", measure_power_secs=1, log_level="info", output_dir=str(emissions_path)
-        )
         async def save_item_binaries(item: Item):
             self.binary_storage.save_item_binaries(item, self.station_config.active_config["name"])
 
         @self.save_item_metadata
-        @track_emissions(
-            project_name="set_inferences", measure_power_secs=1, log_level="info", output_dir=str(emissions_path)
-        )
         async def set_inferences(item: Item):
             item.inferences = await self.get_predictions(item)
 
         @self.save_item_metadata
-        @track_emissions(
-            project_name="set_decision", measure_power_secs=1, log_level="info", output_dir=str(emissions_path)
-        )
         async def set_decision(item: Item):
             decision = self.apply_business_rules(item)
             item.decision = decision.value

edge_orchestrator/edge_orchestrator/domain/use_cases/uploader.py

@@ -29,7 +29,8 @@ def save_item_metadata(self, fct):
         async def wrapper(item: Item, *args):
             item.state = args[0].value
             await fct(item)
-            self.metadata_storage.save_item_metadata(item)
+            active_config_name = args[1]
+            self.metadata_storage.save_item_metadata(item, active_config_name)
 
         return wrapper
 
@@ -50,12 +51,12 @@ async def set_error_state(item: Item, error_message: str):
             logger.info(f"Starting {uploader_state.value}")
             try:
                 logger.info(f"Entering try {uploader_state.value}")
-                await task_fct(item, uploader_state)
+                await task_fct(item, uploader_state, active_config_name)
             except Exception as e:
                 logger.error(f"Error during {uploader_state.value}: {e}")
                 await set_error_state(item, str(e))
 
             logger.info(f"End of {uploader_state.value}")
 
         item.state = UploaderState.DONE.value
-        self.metadata_storage.save_item_metadata(item)
+        self.metadata_storage.save_item_metadata(item, active_config_name)

edge_orchestrator/edge_orchestrator/infrastructure/binary_storage/gcp_binary_storage.py

@@ -10,7 +10,11 @@
 class GCPBinaryStorage(BinaryStorage):
     def __init__(self):
         self.storage_client = storage.Client()
-        self.prefix = os.environ.get("EDGE_NAME", "")
+
+        prefix = os.getenv("EDGE_NAME")
+        if prefix is None:
+            raise Exception("EDGE_NAME environment variable should be set")
+        self.prefix = prefix
         self.bucket = self.storage_client.get_bucket(os.getenv("GCP_BUCKET_NAME"))
 
     def save_item_binaries(self, item: Item, active_config_name: str) -> None:

edge_orchestrator/edge_orchestrator/infrastructure/metadata_storage/gcp_metadata_storage.py

@@ -11,7 +11,11 @@
 class GCPMetadataStorage(MetadataStorage):
     def __init__(self):
         self.storage_client = storage.Client()
-        self.prefix = os.environ.get("EDGE_NAME", "")
+
+        prefix = os.getenv("EDGE_NAME")
+        if prefix is None:
+            raise Exception("EDGE_NAME environment variable should be set")
+        self.prefix = prefix
         self.bucket = self.storage_client.get_bucket(os.getenv("GCP_BUCKET_NAME"))
 
     def save_item_metadata(self, item: Item, active_config_name: str):

edge_orchestrator/edge_orchestrator/infrastructure/model_forward/tf_serving_classification_wrapper.py

@@ -45,9 +45,17 @@ def perform_pre_processing(self, model: ModelInfos, binary: bytes):
 
     def perform_post_processing(self, model: ModelInfos, json_outputs: list, binary_name: str) -> dict:
         logger.debug(f"model classnames: {model.class_names}")
+        predictions = json_outputs[0]
+        number_predictions_classes = len(predictions)
+        number_model_classes = len(model.class_names)
+        if number_predictions_classes != number_model_classes:
+            raise Exception(
+                f"Number of classes in the model ({number_model_classes}) is different from"
+                "the number of predictions ({number_predictions_classes})"
+            )
         return {
             binary_name: {
-                "label": model.class_names[np.argmax(json_outputs[0])],
-                "probability": float(np.max(json_outputs[0])),
+                "label": model.class_names[np.argmax(predictions)],
+                "probability": float(np.max(predictions)),
             }
         }

edge_orchestrator/edge_orchestrator/infrastructure/station_config/json_station_config.py

@@ -28,7 +28,7 @@ def __init__(self, station_configs_folder: Path, inventory: Inventory, data_fold
         self.load()
 
         self.active_config = None
-        config_name = os.environ.get("ACTIVE_CONFIG_NAME", None)
+        config_name = os.getenv("ACTIVE_CONFIG_NAME")
         if config_name is not None:
             self.set_station_config(config_name)