Data gambar Hello: Men-deploy model ke endpoint dan mengirim prediksi
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Simpan dan kategorikan konten berdasarkan preferensi Anda.
Setelah model klasifikasi gambar AutoML Anda selesai dilatih, gunakan konsolGoogle Cloud untuk membuat endpoint dan men-deploy model Anda ke endpoint tersebut. Setelah model di-deploy ke endpoint baru ini, kirim gambar ke model untuk prediksi label.
Pilih model AutoML yang telah Anda latih. Tindakan ini akan mengarahkan Anda ke tab Evaluate tempat Anda dapat melihat metrik performa model.
Pilih tab tabDeploy & test.
Klik Deploy to endpoint.
Pilih radio_button_checkedCreate new endpoint, tetapkan nama endpoint ke hello_automl_image, lalu klik Continue.
Di Model settings, tetapkan Traffic split ke 100%, masukkan 1 di Number of compute node, lalu klik Done.
Klik Deploy untuk men-deploy model ke endpoint baru.
Perlu waktu beberapa menit untuk membuat endpoint dan men-deploy model AutoML ke endpoint baru.
Mengirim prediksi ke model
Setelah proses pembuatan endpoint selesai, Anda dapat mengirim satu permintaan anotasi gambar (prediksi) di konsol Google Cloud .
Buka bagian "Test your model" dari tab Deploy & test yang sama dengan yang digunakan untuk membuat endpoint pada langkah sebelumnya (Model > your_model > tab Deploy & test).
Klik Upload image, lalu pilih gambar yang disimpan secara lokal untuk prediksi, dan lihat label terprediksinya.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-08-19 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."]]
