Hello image data: Deploy a model to an endpoint and send a prediction
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After your AutoML image classification model is done training, use the
Google Cloud console to create an endpoint and deploy your model to
the endpoint. After your model is deployed to this new endpoint, send an image
to the model for label prediction.
Select your trained AutoML model. This takes you to the Evaluate tab
where you can view model performance metrics.
Choose the tabDeploy & test tab.
Click Deploy to endpoint.
Choose radio_button_checkedCreate new
endpoint, set the endpoint name to hello_automl_image, then click
Continue.
In Model settings, accept the Traffic split of
100%, enter 1 in Number of compute nodes, then click Done.
Click Deploy to deploy your model to your new endpoint.
It takes several minutes to create the endpoint and deploy the AutoML model
to the new endpoint.
Send a prediction to your model
After the endpoint creation process finishes you can send a single image
annotation (prediction) request in the Google Cloud console.
Navigate to the "Test your model" section of the same Deploy & test tab
you used to create an endpoint in the previous step
(Models > your_model > tab Deploy & test).
Click Upload image and choose a locally saved image for prediction, and
view its predicted label.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-28 UTC."],[],[],null,["# Hello image data: Deploy a model to an endpoint and send a prediction\n\nAfter your AutoML image classification model is done training, use the\nGoogle Cloud console to create an endpoint and deploy your model to\nthe endpoint. After your model is deployed to this new endpoint, send an image\nto the model for label prediction.\n\nThis tutorial has several pages:\n\n1. [Set up your project and environment.](/vertex-ai/docs/tutorials/image-classification-automl)\n\n2. [Create an image classification dataset, and\n import images.](/vertex-ai/docs/tutorials/image-classification-automl/dataset)\n\n3. [Train an AutoML image classification\n model.](/vertex-ai/docs/tutorials/image-classification-automl/training)\n\n4. [Evaluate and analyze model performance.](/vertex-ai/docs/tutorials/image-classification-automl/error-analysis)\n\n5. Deploy a model to an endpoint, and send a\n prediction.\n\n6. [Clean up your project.](/vertex-ai/docs/tutorials/image-classification-automl/cleanup)\n\nEach page assumes that you have already performed the instructions from the\nprevious pages of the tutorial.\n\nDeploy your model to an endpoint\n--------------------------------\n\nAccess your trained model to deploy it to a new or existing endpoint from\nthe Models page:\n\n1. In the Google Cloud console, in the Vertex AI section, go to\n the **Training** page.\n\n [Go to the Training page](https://console.cloud.google.com/vertex-ai/training)\n2. Select your trained AutoML model. This takes you to the **Evaluate** tab\n where you can view model performance metrics.\n\n3. Choose the tab **Deploy \\& test** tab.\n\n4. Click **Deploy to endpoint**.\n\n5. Choose radio_button_checked**Create new\n endpoint** , set the endpoint name to `hello_automl_image`, then click\n **Continue**.\n\n6. In **Model settings** , accept the **Traffic split** of\n **100%** , enter **1** in **Number of compute nodes** , then click **Done**.\n\n7. Click **Deploy** to deploy your model to your new endpoint.\n\nIt takes several minutes to create the endpoint and deploy the AutoML model\nto the new endpoint.\n\nSend a prediction to your model\n-------------------------------\n\nAfter the endpoint creation process finishes you can send a single image\nannotation (prediction) request in the Google Cloud console.\n\n1. Navigate to the \"Test your model\" section of the same **Deploy \\& test** tab\n you used to create an endpoint in the previous step\n (**Models \\\u003e \u003cvar translate=\"no\"\u003eyour_model\u003c/var\u003e \\\u003e tab Deploy \\& test**).\n\n2. Click **Upload image** and choose a locally saved image for prediction, and\n view its predicted label.\n\n *Image credit* : [Siming Ye, Unsplash](https://unsplash.com/photos/qE-_sYxOMa8) (*shown in UI view*).\n\nWhat's next\n-----------\n\nFollow the [last page of the tutorial](/vertex-ai/docs/tutorials/image-classification-automl/cleanup) to clean up\nresources that you have created."]]