gpt-image-2 画像生成と編集

from openai import OpenAI
import base64

client = OpenAI(
    base_url="https://api.qcode.cc/qcode-img/v1",
    api_key="cr_YOUR_QCODE_API_KEY",
    timeout=180.0,  # 1 枚あたり 30–120 秒、180 秒以上を指定
)

result = client.images.generate(
    model="gpt-image-2",
    prompt="A cyberpunk Tokyo street at night, neon reflecting in rain puddles",
    size="1024x1024",
    quality="low",
    n=1,
)

with open("output.png", "wb") as f:
    f.write(base64.b64decode(result.data[0].b64_json))

from openai import OpenAI
import base64

client = OpenAI(
    base_url="https://api.qcode.cc/qcode-img/v1",
    api_key="cr_YOUR_QCODE_API_KEY",
    timeout=180.0,
)

result = client.images.edit(
    model="gpt-image-2",
    image=open("cat.png", "rb"),
    mask=open("mask.png", "rb"),          # オプション：PNG alpha、透明部分が再描画領域
    prompt="put a tiny crown on the cat",
    size="1024x1024",
    quality="high",
    extra_body={"input_fidelity": "high"},  # 高忠実度、元画像の詳細を保持
)

with open("edited.png", "wb") as f:
    f.write(base64.b64decode(result.data[0].b64_json))

{
  "model": "gpt-image-2",
  "prompt": "A small ceramic vase with sunflower, photorealistic",
  "size": "1024x1024",
  "quality": "low",
  "n": 1
}

{
  "created": 1777135432,
  "data": [
    {
      "b64_json": "iVBORw0KGgo...(base64 PNG/JPEG/WebP, 1-3 MB)",
      "revised_prompt": "A small ceramic vase with sunflower..."
    }
  ]
}

{
  "error": {
    "type": "rate_limit_error",
    "code": "image_daily_limit",
    "message": "Daily image generation count limit reached..."
  }
}

from openai import OpenAI
import base64

client = OpenAI(
    base_url="https://api.qcode.cc/qcode-img/v1",
    api_key="cr_YOUR_QCODE_API_KEY",
    timeout=180.0,
)

result = client.images.generate(
    model="gpt-image-2",
    prompt="A cyberpunk Tokyo street at night, neon reflecting in rain puddles",
    size="1024x1024",
    quality="low",
    n=1,
)

img_bytes = base64.b64decode(result.data[0].b64_json)
with open("output.png", "wb") as f:
    f.write(img_bytes)
print("output.png を保存しました")

from openai import OpenAI
import base64

client = OpenAI(
    base_url="https://api.qcode.cc/qcode-img/v1",
    api_key="cr_YOUR_QCODE_API_KEY",
    timeout=180.0,
)

result = client.images.edit(
    model="gpt-image-2",
    image=open("cat.png", "rb"),
    mask=open("mask.png", "rb"),
    prompt="put a tiny crown on the cat",
    size="1024x1024",
    quality="high",
    extra_body={
        "input_fidelity": "high",
        "background": "transparent",
        "output_format": "png",
    },
)

img = base64.b64decode(result.data[0].b64_json)
with open("edited.png", "wb") as f:
    f.write(img)

result = client.images.edit(
    model="gpt-image-2",
    image=[
        open("scene.png", "rb"),       # 1 枚目：シーン背景
        open("product.png", "rb"),     # 2 枚目：配置する商品
    ],
    prompt="Place the product naturally into the scene, match the lighting and shadows.",
    size="1536x1024",
    quality="high",
    extra_body={"input_fidelity": "high"},
)

curl https://api.qcode.cc/qcode-img/v1/images/generations \
  -H "Authorization: Bearer cr_YOUR_QCODE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "A cyberpunk Tokyo street at night",
    "size": "1024x1024",
    "quality": "low",
    "n": 1
  }' \
  | jq -r ".data[0].b64_json" | base64 -d > output.png

curl https://api.qcode.cc/qcode-img/v1/images/edits \
  -H "Authorization: Bearer cr_YOUR_QCODE_API_KEY" \
  -F "model=gpt-image-2" \
  -F "image=@cat.png" \
  -F "mask=@mask.png" \
  -F "prompt=put a tiny crown on the cat" \
  -F "size=1024x1024" \
  -F "quality=high" \
  -F "input_fidelity=high" \
  -F "background=transparent" \
  -F "output_format=png" \
  | jq -r ".data[0].b64_json" | base64 -d > edited.png

curl https://api.qcode.cc/qcode-img/v1/images/edits \
  -H "Authorization: Bearer cr_YOUR_QCODE_API_KEY" \
  -F "model=gpt-image-2" \
  -F "image=@scene.png" \
  -F "image=@product.png" \
  -F "prompt=Place the product naturally into the scene" \
  -F "size=1536x1024" \
  -F "quality=high" \
  -F "input_fidelity=high"

const r = await fetch("https://api.qcode.cc/qcode-img/v1/images/generations", {
  method: "POST",
  headers: {
    "Authorization": "Bearer cr_YOUR_QCODE_API_KEY",
    "Content-Type":  "application/json",
  },
  body: JSON.stringify({
    model: "gpt-image-2",
    prompt: "A cyberpunk Tokyo street at night",
    size: "1024x1024",
    quality: "low",
    n: 1,
  }),
});
const json = await r.json();
const dataUrl = "data:image/png;base64," + json.data[0].b64_json;
document.querySelector("img").src = dataUrl;

const fd = new FormData();
fd.append("model", "gpt-image-2");
fd.append("image", imageFile);              // <input type="file"> からの File オブジェクト
fd.append("mask", maskFile);                // オプション
fd.append("prompt", "put a tiny crown on the cat");
fd.append("size", "1024x1024");
fd.append("quality", "high");
fd.append("input_fidelity", "high");
fd.append("background", "transparent");
fd.append("output_format", "png");

const r = await fetch("https://api.qcode.cc/qcode-img/v1/images/edits", {
  method: "POST",
  headers: { "Authorization": "Bearer cr_YOUR_QCODE_API_KEY" },
  // Content-Type は手動で設定しないでください — FormData が boundary 付き multipart/form-data を自動設定します
  body: fd,
});
const json = await r.json();
const dataUrl = "data:image/png;base64," + json.data[0].b64_json;
document.querySelector("img").src = dataUrl;

A vintage poster in Bauhaus style, bold black text "MORNING COFFEE" centered,
warm orange and cream color palette, geometric shapes, slightly textured paper background

# 部分修復 + 高忠実度：猫に小さな冠を追加、他は元のまま
prompt = "Put a tiny golden crown on the cat's head. Keep everything else unchanged."
input_fidelity = "high"
mask = (頭部分のみが透明な alpha PNG)