通过 Imagen v.002 使用蒙版修改图片内容
使用集合让一切井井有条
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此示例演示了如何使用 Imagen 模型进行基于蒙版的图片修改。指定目标蒙版区域,并使用文本提示指定修改。
代码示例
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[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],[],[],[],null,["# Edit image content using a mask with Imagen v.002\n\nThis sample demonstrates how to use the Imagen model for mask-based image editing. Specify a targeted mask area and specify the edits using a text prompt.\n\nCode sample\n-----------\n\n### Python\n\n\nBefore trying this sample, follow the Python setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Python API\nreference documentation](/python/docs/reference/aiplatform/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n\n import https://cloud.google.com/python/docs/reference/vertexai/latest/\n from vertexai.preview.vision_models import https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.generative_models.Image.html, https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.vision_models.ImageGenerationModel.html\n\n # TODO(developer): Update and un-comment below lines\n # PROJECT_ID = \"your-project-id\"\n # input_file = \"input-image.png\"\n # mask_file = \"mask-image.png\"\n # output_file = \"output-image.png\"\n # prompt = \"\" # The text prompt describing what you want to see.\n\n https://cloud.google.com/python/docs/reference/vertexai/latest/.init(project=PROJECT_ID, location=\"us-central1\")\n\n model = https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.vision_models.ImageGenerationModel.html.https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.vision_models.ImageGenerationModel.html#vertexai_preview_vision_models_ImageGenerationModel_from_pretrained(\"imagegeneration@002\")\n base_img = https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.generative_models.Image.html.https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.generative_models.Image.html#vertexai_preview_generative_models_Image_load_from_file(location=input_file)\n mask_img = https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.generative_models.Image.html.https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.generative_models.Image.html#vertexai_preview_generative_models_Image_load_from_file(location=mask_file)\n\n images = model.https://cloud.google.com/python/docs/reference/vertexai/latest/vertexai.preview.vision_models.ImageGenerationModel.html#vertexai_preview_vision_models_ImageGenerationModel_edit_image(\n base_image=base_img,\n mask=mask_img,\n prompt=prompt,\n # Optional parameters\n seed=1,\n # Controls the strength of the prompt.\n # -- 0-9 (low strength), 10-20 (medium strength), 21+ (high strength)\n guidance_scale=21,\n number_of_images=1,\n )\n\n images[0].save(location=output_file, include_generation_parameters=False)\n\n # Optional. View the edited image in a notebook.\n # images[0].show()\n\n print(f\"Created output image using {len(images[0]._image_bytes)} bytes\")\n # Example response:\n # Created output image using 971614 bytes\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=generativeaionvertexai)."]]