从图片生成文本
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 Gemini 模型从图片生成文本。
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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,["# Generate text from an image\n\nThis sample demonstrates how to use the Gemini model to generate text from an image.\n\nExplore further\n---------------\n\n\nFor detailed documentation that includes this code sample, see the following:\n\n- [Generate content with the Gemini API in Vertex AI](/vertex-ai/generative-ai/docs/model-reference/inference)\n- [Image understanding](/vertex-ai/generative-ai/docs/multimodal/image-understanding)\n- [Migrate from the Gemini Developer API to the Gemini API in Vertex AI](/vertex-ai/generative-ai/docs/migrate/migrate-google-ai)\n- [Quickstart: Generate text using the Vertex AI Gemini API](/vertex-ai/generative-ai/docs/start/quickstarts/quickstart-multimodal)\n\nCode sample\n-----------\n\n### Go\n\n\nBefore trying this sample, follow the Go 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 Go API\nreference documentation](/go/docs/reference/cloud.google.com/go/aiplatform/latest/apiv1).\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 import (\n \t\"context\"\n \t\"fmt\"\n \t\"io\"\n\n \tgenai \"google.golang.org/genai\"\n )\n\n // generateWithTextImage shows how to generate text using both text and image input\n func generateWithTextImage(w io.Writer) error {\n \tctx := context.Background()\n\n \tclient, err := genai.NewClient(ctx, &genai.ClientConfig{\n \t\tHTTPOptions: genai.HTTPOptions{APIVersion: \"v1\"},\n \t})\n \tif err != nil {\n \t\treturn fmt.Errorf(\"failed to create genai client: %w\", err)\n \t}\n\n \tmodelName := \"gemini-2.5-flash\"\n \tcontents := []*genai.Content{\n \t\t{Parts: []*genai.Part{\n \t\t\t{Text: \"What is shown in this image?\"},\n \t\t\t{FileData: &genai.FileData{\n \t\t\t\t// Image source: https://storage.googleapis.com/cloud-samples-data/generative-ai/image/scones.jpg\n \t\t\t\tFileURI: \"gs://cloud-samples-data/generative-ai/image/scones.jpg\",\n \t\t\t\tMIMEType: \"image/jpeg\",\n \t\t\t}},\n \t\t},\n \t\t\tRole: \"user\"},\n \t}\n\n \tresp, err := client.Models.GenerateContent(ctx, modelName, contents, nil)\n \tif err != nil {\n \t\treturn fmt.Errorf(\"failed to generate content: %w\", err)\n \t}\n\n \trespText := resp.Text()\n\n \tfmt.Fprintln(w, respText)\n\n \t// Example response:\n \t// The image shows an overhead shot of a rustic, artistic arrangement on a surface that ...\n\n \treturn nil\n }\n\n### Node.js\n\n\nBefore trying this sample, follow the Node.js 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 Node.js API\nreference documentation](/nodejs/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 const {GoogleGenAI} = require('@google/genai');\n\n const GOOGLE_CLOUD_PROJECT = process.env.GOOGLE_CLOUD_PROJECT;\n const GOOGLE_CLOUD_LOCATION = process.env.GOOGLE_CLOUD_LOCATION || 'global';\n\n async function generateContent(\n projectId = GOOGLE_CLOUD_PROJECT,\n location = GOOGLE_CLOUD_LOCATION\n ) {\n const ai = new GoogleGenAI({\n vertexai: true,\n project: projectId,\n location: location,\n });\n\n const image = {\n fileData: {\n fileUri: 'gs://cloud-samples-data/generative-ai/image/scones.jpg',\n mimeType: 'image/jpeg',\n },\n };\n\n const response = await ai.models.generateContent({\n model: 'gemini-2.5-flash',\n contents: [image, 'What is shown in this image?'],\n });\n\n console.log(response.text);\n\n return response.text;\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 from google import genai\n from google.genai.types import HttpOptions, Part\n\n client = genai.Client(http_options=HttpOptions(api_version=\"v1\"))\n response = client.models.generate_content(\n model=\"gemini-2.5-flash\",\n contents=[\n \"What is shown in this image?\",\n Part.from_uri(\n file_uri=\"gs://cloud-samples-data/generative-ai/image/scones.jpg\",\n mime_type=\"image/jpeg\",\n ),\n ],\n )\n print(response.text)\n # Example response:\n # The image shows a flat lay of blueberry scones arranged on parchment paper. There are ...\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=googlegenaisdk)."]]