图片生成

from google import genai from google.genai import types from PIL import Image from io import BytesIO import base64  client = genai.Client()  contents = ('Hi, can you create a 3d rendered image of a pig '             'with wings and a top hat flying over a happy '             'futuristic scifi city with lots of greenery?')  response = client.models.generate_content(     model="gemini-2.0-flash-preview-image-generation",     contents=contents,     config=types.GenerateContentConfig(       response_modalities=['TEXT', 'IMAGE']     ) )  for part in response.candidates[0].content.parts:   if part.text is not None:     print(part.text)   elif part.inline_data is not None:     image = Image.open(BytesIO((part.inline_data.data)))     image.save('gemini-native-image.png')     image.show() 

import { GoogleGenAI, Modality } from "@google/genai"; import * as fs from "node:fs";  async function main() {    const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });    const contents =     "Hi, can you create a 3d rendered image of a pig " +     "with wings and a top hat flying over a happy " +     "futuristic scifi city with lots of greenery?";    // Set responseModalities to include "Image" so the model can generate  an image   const response = await ai.models.generateContent({     model: "gemini-2.0-flash-preview-image-generation",     contents: contents,     config: {       responseModalities: [Modality.TEXT, Modality.IMAGE],     },   });   for (const part of response.candidates[0].content.parts) {     // Based on the part type, either show the text or save the image     if (part.text) {       console.log(part.text);     } else if (part.inlineData) {       const imageData = part.inlineData.data;       const buffer = Buffer.from(imageData, "base64");       fs.writeFileSync("gemini-native-image.png", buffer);       console.log("Image saved as gemini-native-image.png");     }   } }  main(); 

package main  import (   "context"   "fmt"   "os"   "google.golang.org/genai" )  func main() {    ctx := context.Background()   client, _ := genai.NewClient(ctx, &genai.ClientConfig{       APIKey:  os.Getenv("GEMINI_API_KEY"),       Backend: genai.BackendGeminiAPI,   })    config := &genai.GenerateContentConfig{       ResponseModalities: []string{"TEXT", "IMAGE"},   }    result, _ := client.Models.GenerateContent(       ctx,       "gemini-2.0-flash-preview-image-generation",       genai.Text("Hi, can you create a 3d rendered image of a pig " +                  "with wings and a top hat flying over a happy " +                  "futuristic scifi city with lots of greenery?"),       config,   )    for _, part := range result.Candidates[0].Content.Parts {       if part.Text != "" {           fmt.Println(part.Text)       } else if part.InlineData != nil {           imageBytes := part.InlineData.Data           outputFilename := "gemini_generated_image.png"           _ = os.WriteFile(outputFilename, imageBytes, 0644)       }   } } 

curl -s -X POST \   "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-preview-image-generation:generateContent?key=$GEMINI_API_KEY" \   -H "Content-Type: application/json" \   -d '{     "contents": [{       "parts": [         {"text": "Hi, can you create a 3d rendered image of a pig with wings and a top hat flying over a happy futuristic scifi city with lots of greenery?"}       ]     }],     "generationConfig":{"responseModalities":["TEXT","IMAGE"]}   }' \   | grep -o '"data": "[^"]*"' \   | cut -d'"' -f4 \   | base64 --decode > gemini-native-image.png 

from google import genai from google.genai import types from PIL import Image from io import BytesIO  import PIL.Image  image = PIL.Image.open('/path/to/image.png')  client = genai.Client()  text_input = ('Hi, This is a picture of me.'             'Can you add a llama next to me?',)  response = client.models.generate_content(     model="gemini-2.0-flash-preview-image-generation",     contents=[text_input, image],     config=types.GenerateContentConfig(       response_modalities=['TEXT', 'IMAGE']     ) )  for part in response.candidates[0].content.parts:   if part.text is not None:     print(part.text)   elif part.inline_data is not None:     image = Image.open(BytesIO(part.inline_data.data))     image.show() 

import { GoogleGenAI, Modality } from "@google/genai"; import * as fs from "node:fs";  async function main() {    const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });    // Load the image from the local file system   const imagePath = "path/to/image.png";   const imageData = fs.readFileSync(imagePath);   const base64Image = imageData.toString("base64");    // Prepare the content parts   const contents = [     { text: "Can you add a llama next to the image?" },     {       inlineData: {         mimeType: "image/png",         data: base64Image,       },     },   ];    // Set responseModalities to include "Image" so the model can generate an image   const response = await ai.models.generateContent({     model: "gemini-2.0-flash-preview-image-generation",     contents: contents,     config: {       responseModalities: [Modality.TEXT, Modality.IMAGE],     },   });   for (const part of response.candidates[0].content.parts) {     // Based on the part type, either show the text or save the image     if (part.text) {       console.log(part.text);     } else if (part.inlineData) {       const imageData = part.inlineData.data;       const buffer = Buffer.from(imageData, "base64");       fs.writeFileSync("gemini-native-image.png", buffer);       console.log("Image saved as gemini-native-image.png");     }   } }  main(); 

package main  import (  "context"  "fmt"  "os"  "google.golang.org/genai" )  func main() {   ctx := context.Background()  client, _ := genai.NewClient(ctx, &genai.ClientConfig{      APIKey:  os.Getenv("GEMINI_API_KEY"),      Backend: genai.BackendGeminiAPI,  })   imagePath := "/path/to/image.png"  imgData, _ := os.ReadFile(imagePath)   parts := []*genai.Part{    genai.NewPartFromText("Hi, This is a picture of me. Can you add a llama next to me?"),    &genai.Part{      InlineData: &genai.Blob{        MIMEType: "image/png",        Data:     imgData,      },    },  }   contents := []*genai.Content{    genai.NewContentFromParts(parts, genai.RoleUser),  }   config := &genai.GenerateContentConfig{      ResponseModalities: []string{"TEXT", "IMAGE"},  }   result, _ := client.Models.GenerateContent(      ctx,      "gemini-2.0-flash-preview-image-generation",      contents,      config,  )   for _, part := range result.Candidates[0].Content.Parts {      if part.Text != "" {          fmt.Println(part.Text)      } else if part.InlineData != nil {          imageBytes := part.InlineData.Data          outputFilename := "gemini_generated_image.png"          _ = os.WriteFile(outputFilename, imageBytes, 0644)      }  } } 

IMG_PATH=/path/to/your/image1.jpeg  if [[ "$(base64 --version 2>&1)" = *"FreeBSD"* ]]; then   B64FLAGS="--input" else   B64FLAGS="-w0" fi  IMG_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH" 2>&1)  curl -X POST \   "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-preview-image-generation:generateContent?key=$GEMINI_API_KEY" \     -H 'Content-Type: application/json' \     -d "{       \"contents\": [{         \"parts\":[             {\"text\": \"'Hi, This is a picture of me. Can you add a llama next to me\"},             {               \"inline_data\": {                 \"mime_type\":\"image/jpeg\",                 \"data\": \"$IMG_BASE64\"               }             }         ]       }],       \"generationConfig\": {\"responseModalities\": [\"TEXT\", \"IMAGE\"]}     }"  \   | grep -o '"data": "[^"]*"' \   | cut -d'"' -f4 \   | base64 --decode > gemini-edited-image.png 

from google import genai from google.genai import types from PIL import Image from io import BytesIO  client = genai.Client(api_key='GEMINI_API_KEY')  response = client.models.generate_images(     model='imagen-3.0-generate-002',     prompt='Robot holding a red skateboard',     config=types.GenerateImagesConfig(         number_of_images= 4,     ) ) for generated_image in response.generated_images:   image = Image.open(BytesIO(generated_image.image.image_bytes))   image.show() 

import { GoogleGenAI } from "@google/genai"; import * as fs from "node:fs";  async function main() {    const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });    const response = await ai.models.generateImages({     model: 'imagen-3.0-generate-002',     prompt: 'Robot holding a red skateboard',     config: {       numberOfImages: 4,     },   });    let idx = 1;   for (const generatedImage of response.generatedImages) {     let imgBytes = generatedImage.image.imageBytes;     const buffer = Buffer.from(imgBytes, "base64");     fs.writeFileSync(`imagen-${idx}.png`, buffer);     idx++;   } }  main(); 

package main  import (   "context"   "fmt"   "os"   "google.golang.org/genai" )  func main() {    ctx := context.Background()   client, _ := genai.NewClient(ctx, &genai.ClientConfig{       APIKey:  os.Getenv("GEMINI_API_KEY"),       Backend: genai.BackendGeminiAPI,   })    config := &genai.GenerateImagesConfig{       NumberOfImages: 4,   }    response, _ := client.Models.GenerateImages(       ctx,       "imagen-3.0-generate-002",       "Robot holding a red skateboard",       config,   )    for n, image := range response.GeneratedImages {       fname := fmt.Sprintf("imagen-%d.png", n)           _ = os.WriteFile(fname, image.Image.ImageBytes, 0644)   } } 

curl -X POST \     "https://generativelanguage.googleapis.com/v1beta/models/imagen-3.0-generate-002:predict?key=GEMINI_API_KEY" \     -H "Content-Type: application/json" \     -d '{         "instances": [           {             "prompt": "Robot holding a red skateboard"           }         ],         "parameters": {           "sampleCount": 4         }       }'