From 984b08b3a5b29baa6e5ad5f98a190986a14d02c4 Mon Sep 17 00:00:00 2001
From: ylolinker <66988143+ylolinker@users.noreply.github.com>
Date: Wed, 21 Oct 2020 01:16:30 +0800
Subject: [PATCH 01/28] Update Shell-installer-Tutorial.md
---
.../Tutorial/Shell-installer-Tutorial.md | 12 ++++++++----
1 file changed, 8 insertions(+), 4 deletions(-)
diff --git a/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md b/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
index b67af78ed..5c71c17bf 100644
--- a/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
+++ b/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
@@ -10,7 +10,8 @@ To install the Vision on Edge Solution Accelerator, the following prerequisites
if you don’t have one, you can create one here: https://azure.microsoft.com/en-us/pricing/purchase-options/pay-as-you-go/
2. That subscription must contain an IoT Hub with a registered IoT Edge device (generally this will be an Azure Stack Edge Device).
At least one IoT Edge with port 8080 and 5000 opened and is connected to your Iot Hub. please follow this [documentation](https://docs.microsoft.com/en-us/azure/iot-edge/quickstart-linux) for deployment information
-3. Azure Custom Vision account, see the below link to find your training key [here](https://www.customvision.ai/projects#/settings)
+3. Azure Custom Vision account, see the link to find your training key [here](https://www.customvision.ai/projects#/settings)
+
4. (Optional) Azure Media Service, please follow the document to create one https://docs.microsoft.com/en-us/azure/media-services/latest/create-account-howto?tabs=portal
@@ -21,13 +22,14 @@ To install the Vision on Edge Solution Accelerator, the following prerequisites
3. To download acs.zip from github by putting the following command `wget -O acs.zip https://github.com/Azure-Samples/azure-intelligent-edge-patterns/raw/master/factory-ai-vision/Installer/acs.zip`
-4. Unzip it `unzip -o acs.zip`. If you have downloaded before, the file name might be different with an extension. The file name can be found above if is different from acs.zip listed above.
+4. Unzip it `unzip -o acs.zip`.
5. Execute the installer `bash factory-ai-vision-install.sh`
6. It will check the az command and check if it requires any installing/updating the IoT extension
You would be asked:
Would you like to use an existing Custom Vision Service? (y or n): y
+
To learn more about Custom Vision Service, please refer the linke [here](https://azure.microsoft.com/en-us/services/cognitive-services/custom-vision-service/)
If you choose “yes”, you will asking to input endpoint and key.
Please enter your Custom Vision endpoint: xxxxxx
Please enter your Custom Vision Key: xxxxxx
@@ -43,7 +45,7 @@ To install the Vision on Edge Solution Accelerator, the following prerequisites
And Choose the number corresponding to your Azure Media Service. This is where you will be asked for the principle secret
-9. Or if you don’t have one, but you would like to install with LVA, it will create new azure media service principle for you.
+9. Or if you don’t have one, but you would like to install with LVA, please go ahead and create a [new account] and come back to continue the installer.
And please copy the "SERVICE-PRINCIPLE-SECRET" information in the bottom
You will need the secret information for later use
@@ -57,5 +59,7 @@ To install the Vision on Edge Solution Accelerator, the following prerequisites
12. The installation will be started after. Please wait for couple minutes to complete the installation.
-
Open your browser, connect to http://YOUR_IP:8080
+
You can check the deployment status on the [Azure portal](portal.azure.com)
+
+13. Open your browser, connect to http://YOUR_IP:8181
From cc8bd0346e26720a543f45b911f014de5615f241 Mon Sep 17 00:00:00 2001
From: ylolinker <66988143+ylolinker@users.noreply.github.com>
Date: Wed, 21 Oct 2020 11:27:03 +0800
Subject: [PATCH 02/28] Update Readme.md
---
factory-ai-vision/Readme.md | 46 +++++++++++++++++--------------------
1 file changed, 21 insertions(+), 25 deletions(-)
diff --git a/factory-ai-vision/Readme.md b/factory-ai-vision/Readme.md
index e8d1b8870..f9305639e 100644
--- a/factory-ai-vision/Readme.md
+++ b/factory-ai-vision/Readme.md
@@ -1,20 +1,27 @@
-| description | products | page_type | description | urlFragment |
-| -------------------------- | --------------------------------------------------------------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------- |
-| This is an easy-to-use UI solution showing how to realize a your own machine learning solution concept in a single day without requiring any Machine Learning expertise, run with hardware accleration on edge with retraining loop.| - azure Stack
-Custom Vision
-Onnxruntime
-azure-iot-edge | sample solution | -json
-python
-javascript | custom-vision-azure-iot |
+| description | products | page_type | description |
+| -------------------------- | --------------------------------------------------------------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| This is an easy-to-use UI solution showing how to realize a your own machine learning solution concept in a single day without requiring any Machine Learning expertise, run with hardware accleration on edge with retraining loop.| - azure Stack
-Custom Vision
-Onnxruntime
-azure-iot-edge | sample solution | -json
-python
-javascript |
-# Custom vision + Azure IoT Edge for Factory AI
-
-This is a sample showing how to deploy a Custom Vision model to Azure IoT edge device and get Machine learning solution up and running in a single day.
-You can define your location, camera and set up objects to detect example: any manufacturing parts, defected parts, etc. while keeping your video footage private, lowering your badnwidth costs and even running everything offline. We use onnxruntime to acclerate your models on edge device using Open Vino for CPU and TensorRT for Nvidia GPU.
+# Vision on Edge Solution
+This is a solution showing how to deploy a Custom Vision model to Azure IoT edge device and get Machine learning solution up and running in a single day.
+You can define your location, camera and set up objects to detect example: any manufacturing parts, defected parts, etc. while keeping your video footage private, lowering your badnwidth costs and even running everything offline. We use onnxruntime to acclerate your models on edge device using Open Vino for CPU and TensorRT for Nvidia GPU and Arm64 GPU. This solution is capable of processing multiple cameras with Microsoft LVA and openCV.
Check out [this video](https://lnkd.in/grQKBN8) to see brief introduction in action and understand how the value is delievered:
[](https://lnkd.in/grQKBN8)
+## Product
+- azure Stack Edge
: See more [here] (https://azure.microsoft.com/en-us/products/azure-stack/edge/)
+- Custom Vision
: Learn more [here] (https://azure.microsoft.com/en-us/services/cognitive-services/custom-vision-service/)
+- Onnxruntime
+- Azure-iot-edge
+- OpenVINO/cpu
+- TensorRT for Nvidia/gpu
+- Arm64/cpu
@@ -35,7 +42,7 @@ Check out [this video](https://lnkd.in/grQKBN8) to see brief introduction in act
# Prerequiste
## Hardware
You need to have one of the following:
-- **Azure Stack Edge**: A portfolio of devices that bring the compute, storage and intelligence to the edge right where data is created
+- **Azure Stack Edge**: A portfolio of devices that bring the compute, storage and intelligence to the edge right where data is created. Find out more [here](https://azure.microsoft.com/en-us/products/azure-stack/edge/)
- Please ensure that you have compute configured and you can run [GPU getting started module here](https://docs.microsoft.com/en-us/azure/databox-online/azure-stack-edge-gpu-deploy-sample-module-marketplace)
or
@@ -49,37 +56,26 @@ or
Check out the architecture below to see how Vision on Edge works on both LVA and OpenCV module. You can also get more details through this tutorial to see how a IoT Edge deployment works. You must have the following services set up to use this solution:
# Architecture
-### LVA Module
+### LVA Module (Recommended)
### OpenCV Module
-## Get Started
-
-To install the Vision on Edge Solution Accelerator, the following prerequisites are required:
-1. You must have an Azure subscription.
-
if you don’t have one, you can create one here: https://azure.microsoft.com/en-us/pricing/purchase-options/pay-as-you-go/
-2. That subscription must contain an IoT Hub with a registered IoT Edge device (generally this will be an Azure Stack Edge Device).
-
At least one IoT Edge with port 8181 and 5000 opened and is connected to your Iot Hub. please follow this [documentation](https://docs.microsoft.com/en-us/azure/iot-edge/quickstart-linux) for deployment information
-3. Azure Custom Vision account, see the below link to find your training key [here](https://www.customvision.ai/projects#/settings)
-
-4. Azure Media Service, please follow the document to create one https://docs.microsoft.com/en-us/azure/media-services/previous/media-services-portal-create-account#create-an-ams-account
-
-# Vision on Edge Installer
+## Get Started: Vision on Edge Installer
-## Option 1: Azure Shell Installer
-### Get Started:
+### Option 1: Azure Shell Installer
+#### Get Started:
Please refer to this tutorial to follow the [instruction](https://github.com/linkernetworks/azure-intelligent-edge-patterns/blob/develop/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md) on how to install from Azure shell
-## Option 2: Manual installation building a docker container and deploy by Visual Studio Code
+### Option 2: Manual installation building a docker container and deploy by Visual Studio Code
-### Prerequisites
+#### Prerequisites
Before installation, You must have the following services set up to use Vision on Edge:
From 142630299133c359d1baed4b0d997c3496ecd662 Mon Sep 17 00:00:00 2001
From: ylolinker <66988143+ylolinker@users.noreply.github.com>
Date: Wed, 21 Oct 2020 11:27:12 +0800
Subject: [PATCH 03/28] Update Shell-installer-Tutorial.md
---
factory-ai-vision/Tutorial/Shell-installer-Tutorial.md | 5 ++---
1 file changed, 2 insertions(+), 3 deletions(-)
diff --git a/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md b/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
index 5c71c17bf..7cf260419 100644
--- a/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
+++ b/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
@@ -8,9 +8,8 @@ To install the Vision on Edge Solution Accelerator, the following prerequisites
1. You must have an Azure subscription.
if you don’t have one, you can create one here: https://azure.microsoft.com/en-us/pricing/purchase-options/pay-as-you-go/
-2. That subscription must contain an IoT Hub with a registered IoT Edge device (generally this will be an Azure Stack Edge Device).
-
At least one IoT Edge with port 8080 and 5000 opened and is connected to your Iot Hub. please follow this [documentation](https://docs.microsoft.com/en-us/azure/iot-edge/quickstart-linux) for deployment information
-3. Azure Custom Vision account, see the link to find your training key [here](https://www.customvision.ai/projects#/settings)
+2. That subscription must contain Azure Stack Edge or IoT hub Edge device with port 8181 opened. please follow this [documentation](https://docs.microsoft.com/en-us/azure/iot-edge/quickstart-linux) for deployment information
+3. Azure Custom Vision account, see the below link to find your training key [here](https://www.customvision.ai/projects#/settings) and learn more [here](https://azure.microsoft.com/en-us/services/cognitive-services/custom-vision-service/)
4. (Optional) Azure Media Service, please follow the document to create one https://docs.microsoft.com/en-us/azure/media-services/latest/create-account-howto?tabs=portal
From 77b222ec451449995fa3a079d23712eb41fce573 Mon Sep 17 00:00:00 2001
From: ylolinker <66988143+ylolinker@users.noreply.github.com>
Date: Wed, 21 Oct 2020 11:29:57 +0800
Subject: [PATCH 04/28] Update Readme.md
---
factory-ai-vision/Readme.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/factory-ai-vision/Readme.md b/factory-ai-vision/Readme.md
index f9305639e..ff3908482 100644
--- a/factory-ai-vision/Readme.md
+++ b/factory-ai-vision/Readme.md
@@ -15,8 +15,8 @@ Check out [this video](https://lnkd.in/grQKBN8) to see brief introduction in act
[](https://lnkd.in/grQKBN8)
## Product
-- azure Stack Edge
: See more [here] (https://azure.microsoft.com/en-us/products/azure-stack/edge/)
-- Custom Vision
: Learn more [here] (https://azure.microsoft.com/en-us/services/cognitive-services/custom-vision-service/)
+- azure Stack Edge: Learn more [here] (https://azure.microsoft.com/en-us/products/azure-stack/edge/)
+- Custom Visio: Learn more [here] (https://azure.microsoft.com/en-us/services/cognitive-services/custom-vision-service/)
- Onnxruntime
- Azure-iot-edge
- OpenVINO/cpu
From a3813c80f0ca36639696d2300fb733acdd25c930 Mon Sep 17 00:00:00 2001
From: ylolinker <66988143+ylolinker@users.noreply.github.com>
Date: Wed, 21 Oct 2020 11:30:38 +0800
Subject: [PATCH 05/28] Update Readme.md
---
factory-ai-vision/Readme.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/factory-ai-vision/Readme.md b/factory-ai-vision/Readme.md
index ff3908482..df401aea1 100644
--- a/factory-ai-vision/Readme.md
+++ b/factory-ai-vision/Readme.md
@@ -15,8 +15,8 @@ Check out [this video](https://lnkd.in/grQKBN8) to see brief introduction in act
[](https://lnkd.in/grQKBN8)
## Product
-- azure Stack Edge: Learn more [here] (https://azure.microsoft.com/en-us/products/azure-stack/edge/)
-- Custom Visio: Learn more [here] (https://azure.microsoft.com/en-us/services/cognitive-services/custom-vision-service/)
+- azure Stack Edge: Learn more [here](https://azure.microsoft.com/en-us/products/azure-stack/edge/)
+- Custom Visio: Learn more [here](https://azure.microsoft.com/en-us/services/cognitive-services/custom-vision-service/)
- Onnxruntime
- Azure-iot-edge
- OpenVINO/cpu
From 29e5803508fbb52cffc9b2b8f47b5dc6268f2ff1 Mon Sep 17 00:00:00 2001
From: goatwu1993
Date: Wed, 21 Oct 2020 12:39:17 +0800
Subject: [PATCH 06/28] Add recommend fps field in inference module
---
.../inference_modules/api/serializers.py | 2 ++
.../vision_on_edge/inference_modules/models.py | 12 ++++++++++++
2 files changed, 14 insertions(+)
diff --git a/factory-ai-vision/EdgeSolution/modules/WebModule/backend/vision_on_edge/inference_modules/api/serializers.py b/factory-ai-vision/EdgeSolution/modules/WebModule/backend/vision_on_edge/inference_modules/api/serializers.py
index cfd1ef71e..347377530 100644
--- a/factory-ai-vision/EdgeSolution/modules/WebModule/backend/vision_on_edge/inference_modules/api/serializers.py
+++ b/factory-ai-vision/EdgeSolution/modules/WebModule/backend/vision_on_edge/inference_modules/api/serializers.py
@@ -13,6 +13,8 @@
class InferenceModuleSerializer(serializers.ModelSerializer):
"""InferenceModuleSerializer"""
+ recommended_fps = serializers.IntegerField(required=False, read_only=True)
+
class Meta:
model = InferenceModule
fields = "__all__"
diff --git a/factory-ai-vision/EdgeSolution/modules/WebModule/backend/vision_on_edge/inference_modules/models.py b/factory-ai-vision/EdgeSolution/modules/WebModule/backend/vision_on_edge/inference_modules/models.py
index 06697d936..3e0556e7d 100644
--- a/factory-ai-vision/EdgeSolution/modules/WebModule/backend/vision_on_edge/inference_modules/models.py
+++ b/factory-ai-vision/EdgeSolution/modules/WebModule/backend/vision_on_edge/inference_modules/models.py
@@ -3,6 +3,7 @@
import logging
+import requests
from django.db import models
logger = logging.getLogger(__name__)
@@ -15,5 +16,16 @@ class InferenceModule(models.Model):
url = models.CharField(max_length=1000, unique=True)
is_gpu = models.BooleanField(default=False)
+ def recommended_fps(self) -> int:
+ try:
+ response = requests.get("http://" + self.url + "/recommended_fps")
+ result = int(response.json()["fps"])
+ except Exception:
+ logger.exception(
+ "Get recommended_fps from inference module failed. Fallback to default"
+ )
+ result = 10
+ return result
+
def __str__(self):
return self.name
From 0ebac4d0235e37a046aaa782c235808036ca2e96 Mon Sep 17 00:00:00 2001
From: Willy Kuo
Date: Wed, 21 Oct 2020 12:53:19 +0800
Subject: [PATCH 07/28] add api for total frame rate
---
.../modules/InferenceModule/model_wrapper.py | 17 +++++++----
.../modules/InferenceModule/server.py | 28 +++++++++++++++----
2 files changed, 34 insertions(+), 11 deletions(-)
diff --git a/factory-ai-vision/EdgeSolution/modules/InferenceModule/model_wrapper.py b/factory-ai-vision/EdgeSolution/modules/InferenceModule/model_wrapper.py
index 205fa4d98..d0bd0992f 100644
--- a/factory-ai-vision/EdgeSolution/modules/InferenceModule/model_wrapper.py
+++ b/factory-ai-vision/EdgeSolution/modules/InferenceModule/model_wrapper.py
@@ -57,9 +57,9 @@ def __init__(self, cam_type="video_file", model_dir="./default_model"):
self.is_gpu = onnxruntime.get_device() == "GPU"
if self.is_gpu:
- self.max_frame_rate = GPU_MAX_FRAME_RATE
+ self.max_total_frame_rate = GPU_MAX_FRAME_RATE
else:
- self.max_frame_rate = CPU_MAX_FRAME_RATE
+ self.max_total_frame_rate = CPU_MAX_FRAME_RATE
self.update_frame_rate_by_number_of_streams(1)
def set_is_scenario(self, is_scenario):
@@ -74,9 +74,13 @@ def get_detection_mode(self):
else:
return self.detection_mode
+ def set_max_total_frame_rate(self, fps):
+ self.max_total_frame_rate = fps
+ print("[INFO] set max total frame rate as", fps, flush=True)
+
def update_frame_rate_by_number_of_streams(self, number_of_streams):
if number_of_streams > 0:
- self.frame_rate = max(1, int(self.max_frame_rate / number_of_streams))
+ self.frame_rate = max(1, int(self.max_total_frame_rate / number_of_streams))
print("[INFO] set frame rate as", self.frame_rate, flush=True)
else:
print(
@@ -87,9 +91,12 @@ def update_frame_rate_by_number_of_streams(self, number_of_streams):
def get_recommended_frame_rate(self, number_of_streams):
if number_of_streams > 0:
- return max(1, int(self.max_frame_rate / number_of_streams))
+ return max(1, int(self.max_total_frame_rate / number_of_streams))
else:
- return self.max_frame_rate
+ return self.max_total_frame_rate
+
+ def get_recommended_total_frame_rate(self):
+ return self.max_total_frame_rate
def set_frame_rate(self, frame_rate):
self.frame_rate = frame_rate
diff --git a/factory-ai-vision/EdgeSolution/modules/InferenceModule/server.py b/factory-ai-vision/EdgeSolution/modules/InferenceModule/server.py
index cae186985..e72c49506 100644
--- a/factory-ai-vision/EdgeSolution/modules/InferenceModule/server.py
+++ b/factory-ai-vision/EdgeSolution/modules/InferenceModule/server.py
@@ -227,13 +227,12 @@ def update_cams(request_body: CamerasModel):
Cameras not in List should not inferecence.
"""
logger.info(request_body)
- fps = request_body.fps
+ frame_rate = request_body.fps
stream_manager.update_streams([cam.id for cam in request_body.cameras])
n = stream_manager.get_streams_num_danger()
# frame_rate = onnx.update_frame_rate_by_number_of_streams(n)
# recommended_fps = onnx.get_recommended_frame_rate(n)
- frame_rate = fps
- onnx.set_frame_rate(fps)
+ onnx.set_frame_rate(frame_rate)
logger.warning('update frame rate to {0}'.format(frame_rate))
# lva_mode
@@ -383,7 +382,16 @@ def get_recommended_fps(number_of_cameras: int):
Args:
number_of_cameras (int): number_of_cameras
"""
- return onnx.get_recommended_frame_rate(number_of_cameras)
+ return {'fps': int(onnx.get_recommended_frame_rate(number_of_cameras))}
+
+@app.get("/get_recommended_total_fps")
+def get_recommended_total_fps():
+ """get_recommended_fps.
+
+ Args:
+ number_of_cameras (int): number_of_cameras
+ """
+ return {'fps': int(onnx.get_recommended_total_frame_rate())}
# @app.route("/get_current_fps")
@@ -498,7 +506,7 @@ def benchmark():
SCENARIO1_MODEL = "scenario_models/1"
n_threads = 3
- n_images = 100
+ n_images = 30
logger.info("============= BenchMarking (Begin) ==================")
logger.info("--- Settings ----")
logger.info("%s threads", n_threads)
@@ -533,10 +541,16 @@ def _f():
threads[i].join()
t1 = time.time()
# print(t1-t0)
+
+ discount = 0.75
+ max_total_frame_rate = discount * (n_images * n_threads) / (t1-t0)
+
logger.info("---- Overall ----")
logger.info("Processing %s images in %s seconds", n_images * n_threads, t1 - t0)
logger.info(" Avg: %s ms per image", (t1 - t0) / (n_images * n_threads) * 1000)
+ logger.info(" Recommended Total FPS: %s", max_total_frame_rate)
logger.info("============= BenchMarking (End) ==================")
+ onnx.set_max_total_frame_rate(max_total_frame_rate)
def cvcapture_url():
@@ -638,10 +652,12 @@ def main():
else:
logging.config.dictConfig(logging_config.LOGGING_CONFIG_DEV)
+ benchmark()
+
logger.info("is_edge: %s", is_edge())
+
if is_edge():
main()
else:
logger.info("Assume running at local development.")
local_main()
- # benchmark()
From 2be89b829616725d826e66ad1218042d8afd96c9 Mon Sep 17 00:00:00 2001
From: Andrew Kao
Date: Wed, 21 Oct 2020 13:24:39 +0800
Subject: [PATCH 08/28] Get recommended fps from server
---
.../modules/WebModule/ui/src/store/project/projectActions.ts | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/store/project/projectActions.ts b/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/store/project/projectActions.ts
index 7172fa0a9..36c2f0013 100644
--- a/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/store/project/projectActions.ts
+++ b/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/store/project/projectActions.ts
@@ -183,7 +183,7 @@ export const thunkGetProject = (): ProjectThunk => (dispatch): Promise
.then((results) => {
const partDetection = results[0].data;
const infModuleIdx = results[1].data.findIndex((e) => e.id === partDetection[0].inference_module);
- const totalRecomendedFps = results[1].data[infModuleIdx]?.is_gpu ? 30 : 10;
+ const totalRecomendedFps = results[1].data[infModuleIdx]?.recommended_fps;
const recomendedFps = Math.floor(totalRecomendedFps / (partDetection[0].cameras?.length || 1));
const project: ProjectData = {
From f9e1322d6d532cab295ed240d4bd28e7f6bf74cf Mon Sep 17 00:00:00 2001
From: Andrew Kao
Date: Wed, 21 Oct 2020 16:02:28 +0800
Subject: [PATCH 09/28] Update project test case
---
.../modules/WebModule/ui/src/store/__test__/project.spec.ts | 2 ++
1 file changed, 2 insertions(+)
diff --git a/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/store/__test__/project.spec.ts b/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/store/__test__/project.spec.ts
index 2d4a8b356..32ad0e686 100644
--- a/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/store/__test__/project.spec.ts
+++ b/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/store/__test__/project.spec.ts
@@ -40,6 +40,8 @@ describe('Post project', () => {
send_video_to_cloud: initialProjectData.sendVideoToCloud,
inference_mode: initialProjectData.inferenceMode,
fps: 10,
+ inference_protocol: 'grpc',
+ send_video_to_cloud: [],
},
});
});
From 9dca6d12609ac3d6d2a3c1285b1509d6679c185d Mon Sep 17 00:00:00 2001
From: ylolinker <66988143+ylolinker@users.noreply.github.com>
Date: Wed, 21 Oct 2020 16:29:05 +0800
Subject: [PATCH 10/28] Update Shell-installer-Tutorial.md
---
factory-ai-vision/Tutorial/Shell-installer-Tutorial.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md b/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
index 7cf260419..0eb02da90 100644
--- a/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
+++ b/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
@@ -19,7 +19,7 @@ To install the Vision on Edge Solution Accelerator, the following prerequisites
1. Open your browser and paste the link https://shell.azure.com/ to open the shell installer.
2. You will need a Azure subscription to continue. Choose your Azure account.
-3. To download acs.zip from github by putting the following command `wget -O acs.zip https://github.com/Azure-Samples/azure-intelligent-edge-patterns/raw/master/factory-ai-vision/Installer/acs.zip`
+3. To download installer (acs.zip) from github by putting the following command `wget -O acs.zip https://github.com/Azure-Samples/azure-intelligent-edge-patterns/raw/master/factory-ai-vision/Installer/acs.zip`
4. Unzip it `unzip -o acs.zip`.
From 10b55a40468e599d9e2cf16bbbb045e8a5196a85 Mon Sep 17 00:00:00 2001
From: ylolinker <66988143+ylolinker@users.noreply.github.com>
Date: Wed, 21 Oct 2020 17:00:44 +0800
Subject: [PATCH 11/28] Update Shell-installer-Tutorial.md
---
factory-ai-vision/Tutorial/Shell-installer-Tutorial.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md b/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
index 0eb02da90..dbd2152a5 100644
--- a/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
+++ b/factory-ai-vision/Tutorial/Shell-installer-Tutorial.md
@@ -58,7 +58,7 @@ To install the Vision on Edge Solution Accelerator, the following prerequisites
12. The installation will be started after. Please wait for couple minutes to complete the installation.
-
You can check the deployment status on the [Azure portal](portal.azure.com)
+
You can check the deployment status on the [Azure portal](https://portal.azure.com/#home)
13. Open your browser, connect to http://YOUR_IP:8181
From fa012fd81fc548b7910656699d77e9c339f097fa Mon Sep 17 00:00:00 2001
From: Andrew Kao
Date: Wed, 21 Oct 2020 18:35:05 +0800
Subject: [PATCH 12/28] Add test case for AddCameraPanel
* Fix the validator to accept when value is 0
* Replace useSelector with connect HOC so we can use dependency injection
when testing
---
.../ui/src/components/AddCameraPanel.tsx | 17 ++++-
.../__tests__/AddCameraPanel.spec.tsx | 71 +++++++++++++++++++
.../WebModule/ui/src/pages/CameraDetails.tsx | 2 +-
.../WebModule/ui/src/pages/Cameras.tsx | 2 +-
4 files changed, 87 insertions(+), 5 deletions(-)
create mode 100644 factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/components/__tests__/AddCameraPanel.spec.tsx
diff --git a/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/components/AddCameraPanel.tsx b/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/components/AddCameraPanel.tsx
index 7fc58f014..751e4df05 100644
--- a/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/components/AddCameraPanel.tsx
+++ b/factory-ai-vision/EdgeSolution/modules/WebModule/ui/src/components/AddCameraPanel.tsx
@@ -11,8 +11,9 @@ import {
Link,
} from '@fluentui/react';
import * as R from 'ramda';
-import { useDispatch, useSelector } from 'react-redux';
+import { connect, useDispatch } from 'react-redux';
import { createSelector } from '@reduxjs/toolkit';
+import { State } from 'RootStateType';
import { postCamera, putCamera } from '../store/cameraSlice';
import { selectAllLocations, getLocations, postLocation } from '../store/locationSlice';
@@ -27,6 +28,7 @@ type AddEditCameraPanelProps = {
isOpen: boolean;
onDissmiss: () => void;
mode: PanelMode;
+ locationOptions: IDropdownOption[];
initialValue?: Form;
cameraId?: number;
};
@@ -59,20 +61,20 @@ export const AddEditCameraPanel: React.FC = ({
isOpen,
onDissmiss,
mode,
+ locationOptions,
initialValue = initialForm,
cameraId,
}) => {
const [loading, setLoading] = useState(false);
const [formData, setFormData] = useState