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DOCS-2783: Update detect-people.md #3223

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Aug 9, 2024
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DOCS-2783: Update detect-people.md #3223

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97fa963
Update detect-people.md
npentrel Aug 9, 2024
647173f
Update detect-people.md
npentrel Aug 9, 2024
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16 changes: 7 additions & 9 deletions docs/get-started/detect-people.md
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Expand Up @@ -97,9 +97,7 @@ Create the service.

In the resulting ML model service configuration pane, ensure that **Deploy model on machine** is selected for the **Deployment** field.

Click on **Select models** and select the `ml-models-scuttle:people` model from the registry (the **people** model by **ml-models-scuttle**) to deploy an object detection TFLite model that has been trained to be able to detect a person.

Click the **Save** button in the top right corner of the page to save your configuration and deploy an object detection TFLite model that has been trained to be able to detect a person.
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I do think we should still tell people to save it though. here I meant to repeat to drill it in ("tell show tell")

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why though? they will be saving immediately again right after

Click on **Select model** and select the `ml-models-scuttle:people` model from the registry (the **people** model by **ml-models-scuttle**) to deploy an object detection TFLite model that has been trained to be able to detect a person.

For more detailed information, including optional attribute configuration, see the [`tflite_cpu` docs](/services/ml/deploy/tflite_cpu/).

Expand All @@ -117,9 +115,9 @@ Click the **Save** button in the top right corner of the page to save your visio
{{% /expand%}}
{{%expand "Step 6: Test person detection" %}}

Now, test your person detection on in the **Test** section of the computer vision service's configuration panel or on the **CONTROL** tab.
Now, test your person detection in the **Test** section of the computer vision service's configuration panel or on the **CONTROL** tab.

You will see your camera stream and see detections as labeled boxes on the images along with position, dimension, class and confidence data.
You will see your camera stream and see detections as labeled boxes on the images along with labels and confidence data.
Detections in class `Person` with a high confidence score show positive person detections, but the ML model can also detect other objects:

{{<imgproc src="/get-started/quickstarts/vision-card-more-detections.png" resize="x1100" declaredimensions=true alt="Positive person detection on the vision card with a lower default minimum confidence threshold." class="imgzoom">}}
Expand All @@ -145,14 +143,14 @@ The full configuration for the attributes of the vision service should resemble:
}
```

This optional attribute reduces your detections output (which you'll view in step 7) by filtering out detections below the threshold of 82% confidence.
This optional attribute reduces your detections output by filtering out detections below the threshold of 82% confidence.
You can adjust this attribute as necessary.

Click the **Save** button in the top right corner of the page to save your configuration.
For more detailed information, including optional attribute configuration, see the [`mlmodel` docs](/services/vision/mlmodel/).

Click the **Save** button in the top right corner of the page to save your configuration and close and reopen the **Test** panel of the vision service configuration panel.
Now if you view detections, you will only see detections with a confidence value higher than the `"default_minimum_confidence"` attribute.

For more detailed information, including optional attribute configuration, see the [`mlmodel` docs](/services/vision/mlmodel/).

{{<imgproc src="/get-started/quickstarts/vision-card.png" resize="x1100" declaredimensions=true alt="Positive person detection on the vision card." >}}

{{% /expand%}}
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