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v3.0 edits #3743
v3.0 edits #3743
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very good start - definitely moving in the right direction. I've only done a superficial review and will do more once you're further along
You can use Viam's built-in data management service to capture images from a camera on your machine and sync the images to the cloud. | ||
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With your images synced to the cloud, you can view images from all your machines in the Viam app interface. | ||
From there, you can use your image data to do things like [train ML models](/how-tos/train-deploy-ml/). | ||
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I assume this file isn't done yet - since it talks about images? Will skip to the next
docs/data-ai/data/visualize.md
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{{< /alert >}} | ||
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## Prerequisites: Teleop |
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I think have a heading ## Teleop
and then H3s for the sub-headings to avoid this. Then you can also briefly intro both
docs/data-ai/data/visualize.md
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## Configure a sensor widget | ||
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Follow our docs to [configure a teleop workspace](manage/troubleshoot/teleoperate/). |
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You'll want to have the instructions here instead, copy them or create an include
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copied over bc needed some adjustments
docs/data-ai/data/query.md
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{{% /tablestep %}} | ||
{{< /table >}} | ||
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## Configure data query |
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This is weird here - the user would get confused why they are asked to do this. See the visualize.md file comments for h2 and h3s
docs/data-ai/data/export.md
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{{% alert title="In this page" color="tip" %}} | ||
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- [Export data with the Viam CLI](#export-data-with-the-viam-cli) | ||
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{{% /alert %}} |
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you can get rid of these, since the TOC is now in the left hand nav
{{% alert title="In this page" color="tip" %}} | |
- [Export data with the Viam CLI](#export-data-with-the-viam-cli) | |
{{% /alert %}} |
docs/data-ai/ai/create-dataset.md
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Collect images from your machine as it monitors its environment and add these images to a dataset. | ||
By creating a dataset from your images, you can then train a machine learning model. | ||
To ensure the model you create performs well, you need to train it on a variety of images that cover the range of things your machine should be able to recognize. |
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Intro here needs work
--- | ||
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I am wondering here if we should merge relevant bits from the ML model service page into this and then get rid of that page in the reference section. It feels somewhat possible? Wondering the same about the vision service and data mgmt service tbh but this seems a good place to start
And maybe also cover https://docs.viam.com/registry/ml-models/#model-framework-support ?
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nice, that seems to have worked. Now let's see if we can do the same for vision service and data management service
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For more detailed information, including optional attribute configuration, see the [`mlmodel` docs](/services/vision/mlmodel/). | ||
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## Use an SDK |
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Good start, I think we could possibly add a code sample here before pointing to APIs?
docs/data-ai/ai/alert.md
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Note that your machine must be connected to the internet for data sync and email notifications to work. | ||
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## Set up your monitor |
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like I said yesterday, this feels weird - let's iterate
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Ah sorry this edit slipped my mind, will make it
docs/data-ai/ai/alert.md
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{{% snippet "setup.md" %}} | ||
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## Configure the camera and computer vision |
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So there's room here for discussions but I think we can consider this as a follow on from the pages before this. So I think you may be able to shorten these steps - until you get to the filtered-camera module
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You can also access data from a resource or machine part menu. | ||
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## Next steps |
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veer towards keeping this here bc still helpful... thoughts?
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let's keep it for now
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Ok - I think merge this as is and address the feedback in a separate PR. This is coming together quite nicely. I think next week may be a good time for you to gather feedback from Jack & Tahiya / others on this. And maybe late next week would be good to run this by Bill if he has time (I'd like to be there for that one)
Once you have configured the data management service, you can specify the data you want to capture at a resource level. | ||
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To configure data capture and cloud sync, you must have one of the following components and services configured on your machine: | ||
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{{< readfile "/static/include/data/capture-supported.md" >}} |
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It doesn't really make sense to have the methods in this table at this point when you just want to say which components and services are supported. I think it's probably best to put what is supported later in this page and keep the requirement up front to more minimal. Also remember you can use the data management service to just sync arbitrary files that something is creating on a machine. Without any configured components.
How about something like:
Once you have configured the data management service, you can specify the data you want to capture at a resource level. | |
To configure data capture and cloud sync, you must have one of the following components and services configured on your machine: | |
{{< readfile "/static/include/data/capture-supported.md" >}} | |
You can capture data from [supported components and services](#link-to-table-that-is-later-in-the-page) or from arbitrary folders on your machines. |
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## Configure the data management service | ||
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To start, configure a data management service to capture and sync the resource data. |
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You can only configure one. And like I said above, it's not restricted to resources.
To start, configure a data management service to capture and sync the resource data. | |
To start, configure the data management service to capture and sync data. |
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{{< imgproc src="/tutorials/data-management/data-management-conf.png" alt="Data capture configuration card." resize="600x" >}} | ||
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For more advanced attribute configuration information, see [Data management service configuration](/data-ai/reference/data/#data-management-service-configuration). |
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Have you already tried moving more of the service pages into these guides and decided against it or are you waiting to do that later in a different PR?
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I personally envisioned having these pages be simpler versions of the reference docs (closer to the how-tos) but still keeping the reference docs up bc that info is also necessary. Does that make sense?
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that makes sense. if we need to keep them then so be it - just want to check that there's actually still info in there we don't already cover
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## Configure data capture | ||
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Scroll to the config card you wish to configure data capture and sync on. |
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Scroll to the config card you wish to configure data capture and sync on. | |
Scroll to the resource card you wish to configure data capture and sync on. |
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At this point, you should have already set up and tested [computer vision functionality](/data-ai/ai/run-inference/). | ||
On this page, you'll learn how to use triggers to send alerts in the form of email notifications when certain detections or classifications are made. |
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you'll need to capture both email & webhooks. webhooks are almost certainly the more sought after part
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Possibly we want to put the webhook info into and include and put that on all of the multiple alert pages...
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you mean the webhook info from the helmet tutorial to /data-ai/data/advanced/alert-data/? IMO that seems like a lot of info to add/could overwhelm the page but I can add it if you think necessary
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I ended up doing it like this here: https://docs-test.viam.dev/3723/manage/troubleshoot/alert/#webhooks just so that we also cover webhooks. The emails are nice but I think more people will need webhooks than emails so we need to mention them and provide the info for it. I think maybe we need to have a webhook reference page or something that we can then link to from the three pages. Or use this as an include and put it in all the places where this comes up
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made it into an include
First, you'll set up data capture and sync to record images with the anomaly and upload them to the cloud. | ||
Next, you'll configure a trigger to send email notifications when the anomaly is detected. | ||
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## Configured a filtered camera |
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## Configured a filtered camera | |
## Configure a filtered camera |
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## Configured a filtered camera | ||
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Your physical camera is working and your vision service is set up. |
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Add a prerequisites section please, that way this page follows the general pattern we use on other pages
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You can use the [vision service API](/dev/reference/apis/services/vision/) to get information about your machine's inferences and program behavior based on that. |
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I think worth you chatting with Jack and Tahiya about whether we want to introduce the vision service here as one of many possible services you could use.
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Also needs more work in intro to explain that we'll show a few examples here only
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You can use the following code to detect and follow the location of a colored object: | ||
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{{% expand "click to view code" %}} |
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capitalization
Co-authored-by: Naomi Pentrel <[email protected]>
Co-authored-by: Naomi Pentrel <[email protected]>
Co-authored-by: Naomi Pentrel <[email protected]>
IA edits for data and ai