Mulai 29 April 2025, model Gemini 1.5 Pro dan Gemini 1.5 Flash tidak tersedia di project yang belum pernah menggunakan model ini, termasuk project baru. Untuk mengetahui detailnya, lihat Versi dan siklus proses model.
Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Dengan Coba Virtual, Anda dapat membuat gambar orang untuk mencoba produk pakaian secara virtual. Anda memberikan gambar seseorang dan gambar produk pakaian, lalu fitur Coba Virtual akan membuat gambar orang yang mengenakan produk tersebut.
Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
Select the tab for how you plan to use the samples on this page:
Python
Untuk menggunakan contoh Python di halaman ini dalam lingkungan
pengembangan lokal, instal dan lakukan inisialisasi gcloud CLI, lalu
siapkan Kredensial Default Aplikasi dengan kredensial pengguna Anda.
Tetapkan variabel lingkungan untuk menggunakan Gen AI SDK dengan Vertex AI:
# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values# with appropriate values for your project.exportGOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECTexportGOOGLE_CLOUD_LOCATION=globalexportGOOGLE_GENAI_USE_VERTEXAI=True
fromgoogleimportgenaifromgoogle.genai.typesimportRecontextImageSource,ProductImageclient=genai.Client()# TODO(developer): Update and un-comment below line# output_file = "output-image.png"image=client.models.recontext_image(model="virtual-try-on-preview-08-04",source=RecontextImageSource(person_image=Image.from_file(location="test_resources/man.png"),product_images=[ProductImage(product_image=Image.from_file(location="test_resources/sweater.jpg"))]))image.generated_images[0].image.save(output_file)print(f"Created output image using {len(image.generated_images[0].image.image_bytes)} bytes")# Example response:# Created output image using 1234567 bytes
REST
Sebelum menggunakan salah satu data permintaan,
lakukan penggantian berikut:
REGION: Region tempat project Anda berada. Untuk mengetahui informasi selengkapnya tentang region yang didukung, lihat Lokasi AI Generatif di Vertex AI.
[[["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 2025-08-25 UTC."],[],[],null,["# Generate Virtual Try-On Images\n\n| **Preview**\n|\n|\n| This product or feature is a Generative AI Preview offering, subject to\n| the \"Pre-GA Offerings Terms\" of the\n| [Google Cloud Service Specific Terms](/terms/service-terms),\n| as well as the\n| [Additional Terms for Generative AI Preview Products](/trustedtester/aitos). For this\n| Generative AI Preview offering, Customers may elect to use it for\n| production or commercial purposes, or disclose Generated Output to\n| third-parties, and may process personal data as outlined in the\n| [Cloud Data Processing\n| Addendum](/terms/data-processing-addendum),\n| subject to the obligations and restrictions described in the agreement\n| under which you access Google Cloud. Pre-GA products are available \"as is\"\n| and might have limited support. For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n\nVirtual Try-On lets you generate images of people to virtually try-on clothing\nproducts. You provide an image of a person and an image of a clothing product,\nand then Virtual Try-On generates an image of the person wearing that\nproduct.\n\n[Try Virtual Try-On in a Colab](https://colab.sandbox.google.com/github/GoogleCloudPlatform/generative-ai/blob/main/vision/getting-started/virtual_try_on.ipynb)\n\nBefore you begin\n----------------\n\nSign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n\nIn the Google Cloud console, on the project selector page,\nselect or create a Google Cloud project.\n| **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n[Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n\n\n[Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n\nEnable the Vertex AI API.\n\n\n[Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com) \nIn the Google Cloud console, on the project selector page,\nselect or create a Google Cloud project.\n| **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n[Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n\n\n[Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n\nEnable the Vertex AI API.\n\n\n[Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com)\n1. Set up authentication for your environment.\n\n Select the tab for how you plan to use the samples on this page: \n\n ### Python\n\n\n To use the Python samples on this page in a local\n development environment, install and initialize the gcloud CLI, and\n then set up Application Default Credentials with your user credentials.\n 1.\n [Install](/sdk/docs/install) the Google Cloud CLI.\n\n 2. If you're using an external identity provider (IdP), you must first\n [sign in to the gcloud CLI with your federated identity](/iam/docs/workforce-log-in-gcloud).\n\n 3.\n\n If you're using a local shell, then create local authentication credentials for your user\n account:\n\n ```bash\n gcloud auth application-default login\n ```\n\n You don't need to do this if you're using Cloud Shell.\n\n\n If an authentication error is returned, and you are using an external identity provider\n (IdP), confirm that you have\n [signed in to the gcloud CLI with your federated identity](/iam/docs/workforce-log-in-gcloud).\n\n\n For more information, see\n [Set up ADC for a local development environment](/docs/authentication/set-up-adc-local-dev-environment)\n in the Google Cloud authentication documentation.\n\n ### REST\n\n\n To use the REST API samples on this page in a local development environment, you use the\n credentials you provide to the gcloud CLI.\n 1. [Install](/sdk/docs/install) the Google Cloud CLI.\n 2. If you're using an external identity provider (IdP), you must first [sign in to the gcloud CLI with your federated identity](/iam/docs/workforce-log-in-gcloud).\n\n\n For more information, see\n [Authenticate for using REST](/docs/authentication/rest)\n in the Google Cloud authentication documentation.\n\nGenerate images\n---------------\n\n### Python\n\n#### Install\n\n```\npip install --upgrade google-genai\n```\n\n\nTo learn more, see the\n[SDK reference documentation](https://googleapis.github.io/python-genai/).\n\n\nSet environment variables to use the Gen AI SDK with Vertex AI:\n\n```bash\n# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values\n# with appropriate values for your project.\nexport GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT\nexport GOOGLE_CLOUD_LOCATION=global\nexport GOOGLE_GENAI_USE_VERTEXAI=True\n```\n\n\u003cbr /\u003e\n\n from google import genai\n from google.genai.types import RecontextImageSource, ProductImage\n\n client = genai.Client()\n\n # TODO(developer): Update and un-comment below line\n # output_file = \"output-image.png\"\n\n image = client.models.recontext_image(\n model=\"virtual-try-on-preview-08-04\",\n source=RecontextImageSource(\n person_image=Image.from_file(location=\"test_resources/man.png\"),\n product_images=[\n ProductImage(product_image=Image.from_file(location=\"test_resources/sweater.jpg\"))\n ],\n ),\n )\n\n image.generated_images[0].image.save(output_file)\n\n print(f\"Created output image using {len(image.generated_images[0].image.image_bytes)} bytes\")\n # Example response:\n # Created output image using 1234567 bytes\n\n### REST\n\n\nBefore using any of the request data,\nmake the following replacements:\n\n- \u003cvar translate=\"no\"\u003eREGION\u003c/var\u003e: The region that your project is located in. For more information about supported regions, see [Generative AI on Vertex AI\n locations](/vertex-ai/generative-ai/docs/learn/locations).\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: Your Google Cloud [project ID](/resource-manager/docs/creating-managing-projects#identifiers).\n- \u003cvar translate=\"no\"\u003eBASE64_PERSON_IMAGE\u003c/var\u003e: The Base64-encoded image of the person image.\n- \u003cvar translate=\"no\"\u003eBASE64_PRODUCT_IMAGE\u003c/var\u003e: The Base64-encoded image of the product image.\n- \u003cvar translate=\"no\"\u003eIMAGE_COUNT\u003c/var\u003e: The number of images to generate. The accepted range of values is `1` to `4`.\n- \u003cvar translate=\"no\"\u003eGCS_OUTPUT_PATH\u003c/var\u003e: The Cloud Storage path to store the virtual try-on output to.\n\n\nHTTP method and URL:\n\n```\nPOST https://REGION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/REGION/publishers/google/models/virtual-try-on-preview-08-04:predict\n```\n\n\nRequest JSON body:\n\n```\n{\n \"instances\": [\n {\n \"personImage\": {\n \"image\": {\n \"bytesBase64Encoded\": \"BASE64_PERSON_IMAGE\"\n }\n },\n \"productImages\": [\n {\n \"image\": {\n \"bytesBase64Encoded\": \"BASE64_PRODUCT_IMAGE\"\n }\n }\n ]\n }\n ],\n \"parameters\": {\n \"sampleCount\": IMAGE_COUNT,\n \"storageUri\": \"GCS_OUTPUT_PATH\"\n }\n}\n```\n\nTo send your request, choose one of these options: \n\n#### curl\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) , or by using [Cloud Shell](/shell/docs), which automatically logs you into the `gcloud` CLI . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nSave the request body in a file named `request.json`,\nand execute the following command:\n\n```\ncurl -X POST \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n -H \"Content-Type: application/json; charset=utf-8\" \\\n -d @request.json \\\n \"https://REGION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/REGION/publishers/google/models/virtual-try-on-preview-08-04:predict\"\n```\n\n#### PowerShell\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nSave the request body in a file named `request.json`,\nand execute the following command:\n\n```\n$cred = gcloud auth print-access-token\n$headers = @{ \"Authorization\" = \"Bearer $cred\" }\n\nInvoke-WebRequest `\n -Method POST `\n -Headers $headers `\n -ContentType: \"application/json; charset=utf-8\" `\n -InFile request.json `\n -Uri \"https://REGION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/REGION/publishers/google/models/virtual-try-on-preview-08-04:predict\" | Select-Object -Expand Content\n```\nThe request returns image objects. In this example, two image objects are returned, with two prediction objects as base64-encoded images.\n\n```\n{\n \"predictions\": [\n {\n \"mimeType\": \"image/png\",\n \"bytesBase64Encoded\": \"BASE64_IMG_BYTES\"\n },\n {\n \"bytesBase64Encoded\": \"BASE64_IMG_BYTES\",\n \"mimeType\": \"image/png\"\n }\n ]\n}\n```\n\n\u003cbr /\u003e"]]