如何在 Google AI Studio 與 Gemini 上使用 Nano Banana

from google import genai  
from PIL import Image  
from io import BytesIO  
import os  
from dotenv import load_dotenv  
load_dotenv()  # 從 .env 檔案載入 API 金鑰  
client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))  
# 定義圖片生成的提示詞  
prompt = "黃昏時分的未來城市景觀，霓虹燈映照在雨後濕潤的街道上"  
# 向 Gemini 2.5 Flash Image 發出圖片生成請求  
response = client.models.generate_content(  
    model="gemini-2.5-flash-image-preview",  
    contents=[prompt]  
)  
# 擷取並儲存生成的圖片  
for part in response.candidates[0].content.parts:  
    if part.inline_data is not None:  
        image = Image.open(BytesIO(part.inline_data.data))  
        image.save("generated_image.png")  
        print("圖片已儲存為 generated_image.png")  

from PIL import Image  
from io import BytesIO  
# 載入要編輯的現有圖片  
image_to_edit = Image.open("path/to/your/image.png")  
# 定義編輯提示詞  
edit_prompt = "使用提供的圖片，加入復古風格、溫暖的棕褐色調，並稍微模糊背景"  
response = client.models.generate_content(  
    model="gemini-2.5-flash-image-preview",  
    contents=[edit_prompt, image_to_edit]  
)  
# 處理回應並儲存編輯後的圖片  
for part in response.candidates[0].content.parts:  
    if part.inline_data is not None:  
        edited_image = Image.open(BytesIO(part.inline_data.data))  
        edited_image.save("edited_image.png")  
        print("編輯後的圖片已儲存為 edited_image.png")  

from PIL import Image  
from io import BytesIO  
base_image = Image.open("path/to/your/portrait.png")  
consistency_prompt = "Generate a new image using the provided portrait as reference. The subject should be smiling and looking directly at the camera, with the same facial features and style."  
response = client.models.generate_content(  
    model="gemini-2.5-flash-image-preview",  
    contents=[consistency_prompt, base_image]  
)  
for part in response.candidates[0].content.parts:  
    if part.inline_data is not None:  
        consistent_image = Image.open(BytesIO(part.inline_data.data))  
        consistent_image.save("consistent_image.png")  
        print("已將一致性圖片儲存為 consistent_image.png")  

from PIL import Image  
from io import BytesIO  
# 載入多張影像  
background = Image.open("path/to/background.png")  
product = Image.open("path/to/product.png")  
fusion_prompt = "將背景與產品影像結合。自然地將產品置入場景中，確保光線與陰影一致。"  
response = client.models.generate_content(  
    model="gemini-2.5-flash-image-preview",  
    contents=[fusion_prompt, background, product]  
)  
for part in response.candidates[0].content.parts:  
    if part.inline_data is not None:  
        fusion_image = Image.open(BytesIO(part.inline_data.data))  
        fusion_image.save("fused_image.png")  
        print("融合影像已儲存為 fused_image.png")  

from google import genai  
from PIL import Image  
from io import BytesIO  
import os  
from dotenv import load_dotenv  
load_dotenv()  
client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))  
# 步驟 1：根據文字提示生成圖片  
generation_prompt = "一幅寧靜的夕陽映照平靜湖面，伴隨柔和的雲彩與溫暖色調"  
response_gen = client.models.generate_content(  
    model="gemini-2.5-flash-image-preview",  
    contents=[generation_prompt]  
)  
for part in response_gen.candidates[0].content.parts:  
    if part.inline_data is not None:  
        gen_image = Image.open(BytesIO(part.inline_data.data))  
        gen_image.save("sunset_lake.png")  
        print("生成的圖片已儲存為 sunset_lake.png")  
# 步驟 2：透過新增物件來編輯現有圖片  
base_image = Image.open("sunset_lake.png")  
edit_prompt = "使用提供的圖片，在平靜的湖面上加入一艘小木船輕輕航行，並呈現真實反射效果。"  
response_edit = client.models.generate_content(  
    model="gemini-2.5-flash-image-preview",  
    contents=[edit_prompt, base_image]  
)  
for part in response_edit.candidates[0].content.parts:  
    if part.inline_data is not None:  
        edited_image = Image.open(BytesIO(part.inline_data.data))  
        edited_image.save("sunset_lake_boat.png")  
        print("編輯後的圖片已儲存為 sunset_lake_boat.png")  

flowchart TD  
    A["開始：定義需求"]  
    B["選擇平台：AI Studio 或 Gemini API"]  
    C["登入並存取 Gemini 2.5 Flash Image"]  
    D["輸入描述性提示詞 / 上傳圖片"]  
    E["生成初始圖片"]  
    F["檢視輸出結果"]  
    G["反覆調整：優化提示詞或編輯圖片"]  
    H["完成圖片並儲存輸出"]  
    A --> B  
    B --> C  
    C --> D  
    D --> E  
    E --> F  
    F --> G  
    G --> H  

flowchart TD  
    A["開始：設定環境"]  
    B["安裝所需套件"]  
    C["設定 API 金鑰 (.env)"]  
    D["使用 google-genai 撰寫 Python 腳本"]  
    E["定義提示詞及/或上傳圖片"]  
    F["呼叫 Gemini API 進行生成/編輯"]  
    G["處理回應並擷取圖片"]  
    H["儲存並檢視輸出結果"]  
    A --> B  
    B --> C  
    C --> D  
    D --> E  
    E --> F  
    F --> G  
    G --> H