이미지 생성

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
        }
      }'