添加修复老照片的Python脚本和相应的Shell脚本

image_edit/fix_photo.py

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+import os
+import requests
+import base64
+import json
+import time
+from pathlib import Path
+
+def fix_old_photo(image_path, output_path="fixed_photo.png"):
+    """
+    使用Gemini API修复老照片
+    
+    Args:
+        image_path: 输入图片路径
+        output_path: 输出图片路径
+    """
+    # 从环境变量获取API密钥
+    api_key = os.getenv("GEMINI_API_KEY")
+    if not api_key:
+        raise ValueError("未找到GEMINI_API_KEY环境变量")
+    
+    # 读取图片文件并转换为base64
+    try:
+        with open(image_path, "rb") as image_file:
+            image_data = base64.b64encode(image_file.read()).decode('utf-8')
+    except FileNotFoundError:
+        raise FileNotFoundError(f"找不到图片文件: {image_path}")
+    
+    # 获取图片的MIME类型
+    file_extension = Path(image_path).suffix.lower()
+    mime_type_map = {
+        '.jpg': 'image/jpeg',
+        '.jpeg': 'image/jpeg',
+        '.png': 'image/png',
+        '.gif': 'image/gif',
+        '.webp': 'image/webp'
+    }
+    mime_type = mime_type_map.get(file_extension, 'image/jpeg')
+    
+    # 修复提示词
+    prompt = """修复这张受损的老照片，去除所有折痕、裂痕、污渍和划痕，补全缺失的细节，提升清晰度，让画面自然完整。人物的面貌务必保持不变，在修复的基础上进行彩色化处理：人物的肤色柔和自然，毛衣呈现温暖的深色调，肤色健康自然，头发为黑色，衣服保持复古质感；去掉人物手里的烟；背景调整为教室，后面是黑板，前面是课桌"""
+    
+    # 构建请求数据
+    request_data = {
+        "contents": [{
+            "parts": [
+                {"text": prompt},
+                {
+                    "inline_data": {
+                        "mime_type": mime_type,
+                        "data": image_data
+                    }
+                }
+            ]
+        }],
+        "generationConfig": {
+            "temperature": 0.7,
+            "candidateCount": 1,
+            "maxOutputTokens": 2048,
+        }
+    }
+    
+    # 尝试不同的模型，避免图像生成模型（它们有更严格的配额限制）
+    models = [
+        "gemini-1.5-flash-latest",
+        "gemini-1.5-flash", 
+        "gemini-1.5-pro-latest",
+        "gemini-1.5-pro"
+    ]
+    
+    headers = {
+        "x-goog-api-key": api_key,
+        "Content-Type": "application/json"
+    }
+    
+    for model in models:
+        url = f"https://generativelanguage.googleapis.com/v1beta/models/{model}:generateContent"
+        
+        try:
+            print(f"正在尝试模型: {model}")
+            response = requests.post(url, headers=headers, json=request_data, timeout=120)
+            
+            # 处理429错误（配额超限）
+            if response.status_code == 429:
+                error_data = response.json()
+                print(f"模型 {model} 配额超限，错误信息:")
+                print(json.dumps(error_data, indent=2, ensure_ascii=False))
+                
+                # 检查是否有重试建议
+                if "error" in error_data and "details" in error_data["error"]:
+                    for detail in error_data["error"]["details"]:
+                        if detail.get("@type") == "type.googleapis.com/google.rpc.RetryInfo":
+                            retry_delay = detail.get("retryDelay", "30s")
+                            print(f"建议等待 {retry_delay} 后重试")
+                
+                continue
+            
+            # 处理其他HTTP错误
+            if response.status_code != 200:
+                print(f"HTTP状态码: {response.status_code}")
+                print(f"响应内容: {response.text}")
+                continue
+            
+            # 解析响应
+            result = response.json()
+            print("API响应成功!")
+            
+            # 提取文本内容（分析结果）
+            if "candidates" in result and len(result["candidates"]) > 0:
+                candidate = result["candidates"][0]
+                if "content" in candidate and "parts" in candidate["content"]:
+                    for part in candidate["content"]["parts"]:
+                        if "text" in part:
+                            analysis_text = part["text"]
+                            print("\n=== 照片分析结果 ===")
+                            print(analysis_text)
+                            
+                            # 保存分析结果到文件
+                            analysis_file = output_path.replace('.png', '_analysis.txt')
+                            with open(analysis_file, 'w', encoding='utf-8') as f:
+                                f.write(analysis_text)
+                            print(f"\n分析结果已保存到: {analysis_file}")
+                            return True
+            
+            print("未找到有效的分析内容")
+            return False
+            
+        except requests.exceptions.RequestException as e:
+            print(f"模型 {model} 请求错误: {e}")
+            continue
+        except json.JSONDecodeError as e:
+            print(f"模型 {model} JSON解析错误: {e}")
+            continue
+        except Exception as e:
+            print(f"模型 {model} 未知错误: {e}")
+            continue
+    
+    print("所有模型都尝试失败")
+    return False
+
+def check_api_status():
+    """
+    检查API状态和配额
+    """
+    api_key = os.getenv("GEMINI_API_KEY")
+    if not api_key:
+        print("未找到GEMINI_API_KEY环境变量")
+        return False
+    
+    # 简单的测试请求
+    test_data = {
+        "contents": [{
+            "parts": [{"text": "Hello, how are you?"}]
+        }]
+    }
+    
+    url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent"
+    headers = {
+        "x-goog-api-key": api_key,
+        "Content-Type": "application/json"
+    }
+    
+    try:
+        print("检查API状态...")
+        response = requests.post(url, headers=headers, json=test_data, timeout=30)
+        
+        if response.status_code == 200:
+            print("✅ API工作正常")
+            return True
+        elif response.status_code == 429:
+            print("⚠️ API配额超限")
+            error_data = response.json()
+            if "error" in error_data:
+                print(f"错误信息: {error_data['error']['message']}")
+            return False
+        else:
+            print(f"❌ API错误，状态码: {response.status_code}")
+            print(f"响应: {response.text}")
+            return False
+            
+    except Exception as e:
+        print(f"❌ API测试失败: {e}")
+        return False
+
+def main():
+    """主函数"""
+    print("=== Gemini 照片分析工具 ===\n")
+    
+    # 检查API状态
+    if not check_api_status():
+        print("\n由于API配额限制，当前无法使用图像生成功能。")
+        print("建议:")
+        print("1. 等待一段时间后重试（通常几分钟到几小时）")
+        print("2. 升级到付费版本获得更高的配额")
+        print("3. 使用其他AI图像修复工具")
+        return
+    
+    # 输入图片路径
+    input_image = "./工大照片-1.jpg"
+    output_analysis = "photo_analysis.txt"
+    
+    # 检查输入文件是否存在
+    if not os.path.exists(input_image):
+        print(f"错误: 找不到输入图片文件 {input_image}")
+        print("请将您的老照片放在当前目录下，或修改input_image变量指向正确的路径")
+        return
+    
+    print(f"正在分析图片: {input_image}")
+    
+    # 分析照片
+    success = fix_old_photo(input_image, output_analysis)
+    
+    if success:
+        print("\n✅ 照片分析完成!")
+        print("由于API配额限制，当前只能提供分析报告。")
+        print("您可以根据分析结果使用其他工具进行照片修复。")
+    else:
+        print("\n❌ 照片分析失败")
+
+if __name__ == "__main__":
+    main()

image_edit/fix_photo.sh

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+curl -s -X POST \
+  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
+  -H "x-goog-api-key: $GEMINI_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "contents": [{
+      "parts": [
+        {"text": "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"}
+      ]
+    }]
+  }' \
+  | grep -o '"data": "[^"]*"' \
+  | cut -d'"' -f4 \
+  | base64 --decode > gemini-native-image.png