新增16个AI技能：包含图像生成、视频剪辑、数据分析、智能查询等功能模块
This commit is contained in:
hmo
287
.opencode/skills/image-service/scripts/image_to_text.py
Normal file
287
.opencode/skills/image-service/scripts/image_to_text.py
Normal file
@@ -0,0 +1,287 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
图生文脚本 (Image-to-Text) - 视觉识别
|
||||
使用 Qwen2.5-VL 模型分析图片内容并生成文字描述
|
||||
|
||||
Author: 翟星人
|
||||
"""
|
||||
|
||||
import httpx
|
||||
import base64
|
||||
import json
|
||||
import os
|
||||
from typing import Dict, Any, Optional, Union, List
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
class ImageToTextAnalyzer:
|
||||
"""图生文分析器 - 视觉识别"""
|
||||
|
||||
# 预定义的分析模式
|
||||
ANALYSIS_MODES = {
|
||||
"describe": "请详细描述这张图片的内容，包括：人物、场景、物品、颜色、布局等所有细节。",
|
||||
"ocr": "请仔细识别这张图片中的所有文字内容，按照文字在图片中的位置顺序输出。如果是中文，请保持原文输出。",
|
||||
"chart": "请分析这张图表的内容，包括：图表类型、数据趋势、关键数据点、标题标签、以及数据的结论或洞察。",
|
||||
"fashion": "请分析这张图片中人物的穿搭，包括：服装款式、颜色搭配、配饰、整体风格等。",
|
||||
"product": "请分析这张产品图片，包括：产品类型、外观特征、功能特点、品牌信息等。",
|
||||
"scene": "请描述这张图片的场景，包括：地点、环境、氛围、时间（白天/夜晚）等。"
|
||||
}
|
||||
|
||||
def __init__(self, config: Optional[Dict[str, str]] = None):
|
||||
"""
|
||||
初始化分析器
|
||||
|
||||
Args:
|
||||
config: 配置字典，包含 api_key, base_url, model
|
||||
如果不传则从环境变量或配置文件读取
|
||||
"""
|
||||
if config is None:
|
||||
config = self._load_config()
|
||||
|
||||
self.api_key = config.get('api_key') or config.get('VISION_API_KEY') or config.get('IMAGE_API_KEY')
|
||||
self.base_url = config.get('base_url') or config.get('VISION_API_BASE_URL') or config.get('IMAGE_API_BASE_URL')
|
||||
self.model = config.get('model') or config.get('VISION_MODEL') or 'qwen2.5-vl-72b-instruct'
|
||||
|
||||
if not self.api_key or not self.base_url:
|
||||
raise ValueError("缺少必要的 API 配置：api_key 和 base_url")
|
||||
|
||||
def _load_config(self) -> Dict[str, str]:
|
||||
"""从配置文件或环境变量加载配置"""
|
||||
config = {}
|
||||
|
||||
# 尝试从配置文件加载
|
||||
config_path = Path(__file__).parent.parent / 'config' / 'settings.json'
|
||||
if config_path.exists():
|
||||
with open(config_path, 'r', encoding='utf-8') as f:
|
||||
settings = json.load(f)
|
||||
# 优先使用 vision_api 配置
|
||||
vision_config = settings.get('vision_api', {})
|
||||
if vision_config:
|
||||
config['api_key'] = vision_config.get('key')
|
||||
config['base_url'] = vision_config.get('base_url')
|
||||
config['model'] = vision_config.get('model')
|
||||
else:
|
||||
# 回退到 image_api 配置
|
||||
api_config = settings.get('image_api', {})
|
||||
config['api_key'] = api_config.get('key')
|
||||
config['base_url'] = api_config.get('base_url')
|
||||
|
||||
# 环境变量优先级更高
|
||||
config['api_key'] = os.getenv('VISION_API_KEY', os.getenv('IMAGE_API_KEY', config.get('api_key')))
|
||||
config['base_url'] = os.getenv('VISION_API_BASE_URL', os.getenv('IMAGE_API_BASE_URL', config.get('base_url')))
|
||||
config['model'] = os.getenv('VISION_MODEL', config.get('model', 'qwen2.5-vl-72b-instruct'))
|
||||
|
||||
return config
|
||||
|
||||
@staticmethod
|
||||
def image_to_base64(image_path: str) -> str:
|
||||
"""
|
||||
将图片文件转换为 base64 编码（带 data URL 前缀）
|
||||
|
||||
Args:
|
||||
image_path: 图片文件路径
|
||||
|
||||
Returns:
|
||||
base64 编码字符串（含 data URL 前缀）
|
||||
"""
|
||||
path = Path(image_path)
|
||||
if not path.exists():
|
||||
raise FileNotFoundError(f"图片文件不存在: {image_path}")
|
||||
|
||||
# 获取 MIME 类型
|
||||
suffix = path.suffix.lower()
|
||||
mime_types = {
|
||||
'.jpg': 'image/jpeg',
|
||||
'.jpeg': 'image/jpeg',
|
||||
'.png': 'image/png',
|
||||
'.gif': 'image/gif',
|
||||
'.webp': 'image/webp'
|
||||
}
|
||||
mime_type = mime_types.get(suffix, 'image/png')
|
||||
|
||||
with open(image_path, 'rb') as f:
|
||||
b64_str = base64.b64encode(f.read()).decode('utf-8')
|
||||
|
||||
return f"data:{mime_type};base64,{b64_str}"
|
||||
|
||||
def analyze(
|
||||
self,
|
||||
image: Union[str, bytes],
|
||||
prompt: Optional[str] = None,
|
||||
mode: str = "describe",
|
||||
max_tokens: int = 2000,
|
||||
temperature: float = 0.7
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
分析图片并生成文字描述
|
||||
|
||||
Args:
|
||||
image: 图片路径、URL 或 base64 字符串
|
||||
prompt: 自定义分析提示词（如果提供则忽略 mode）
|
||||
mode: 分析模式 (describe/ocr/chart/fashion/product/scene)
|
||||
max_tokens: 最大输出 token 数
|
||||
temperature: 温度参数
|
||||
|
||||
Returns:
|
||||
包含分析结果的字典
|
||||
"""
|
||||
# 确定使用的提示词
|
||||
if prompt is None:
|
||||
prompt = self.ANALYSIS_MODES.get(mode, self.ANALYSIS_MODES["describe"])
|
||||
|
||||
# 处理图片输入
|
||||
if isinstance(image, str):
|
||||
if os.path.isfile(image):
|
||||
image_url = self.image_to_base64(image)
|
||||
elif image.startswith('data:') or image.startswith('http'):
|
||||
image_url = image
|
||||
else:
|
||||
# 假设是纯 base64 字符串
|
||||
image_url = f"data:image/png;base64,{image}"
|
||||
else:
|
||||
image_url = f"data:image/png;base64,{base64.b64encode(image).decode('utf-8')}"
|
||||
|
||||
# 构建请求
|
||||
payload = {
|
||||
"model": self.model,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": prompt
|
||||
},
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {
|
||||
"url": image_url
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"max_tokens": max_tokens,
|
||||
"temperature": temperature
|
||||
}
|
||||
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {self.api_key}"
|
||||
}
|
||||
|
||||
try:
|
||||
with httpx.Client(timeout=120.0) as client:
|
||||
response = client.post(
|
||||
f"{self.base_url}/chat/completions",
|
||||
headers=headers,
|
||||
json=payload
|
||||
)
|
||||
response.raise_for_status()
|
||||
result = response.json()
|
||||
|
||||
# 提取文本内容
|
||||
content = result.get("choices", [{}])[0].get("message", {}).get("content", "")
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"content": content,
|
||||
"mode": mode,
|
||||
"usage": result.get("usage", {})
|
||||
}
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
return {
|
||||
"success": False,
|
||||
"error": f"HTTP 错误: {e.response.status_code}",
|
||||
"detail": str(e)
|
||||
}
|
||||
except Exception as e:
|
||||
return {
|
||||
"success": False,
|
||||
"error": "分析失败",
|
||||
"detail": str(e)
|
||||
}
|
||||
|
||||
def describe(self, image: Union[str, bytes]) -> Dict[str, Any]:
|
||||
"""通用图片描述"""
|
||||
return self.analyze(image, mode="describe")
|
||||
|
||||
def ocr(self, image: Union[str, bytes]) -> Dict[str, Any]:
|
||||
"""文字识别 (OCR)"""
|
||||
return self.analyze(image, mode="ocr")
|
||||
|
||||
def analyze_chart(self, image: Union[str, bytes]) -> Dict[str, Any]:
|
||||
"""图表分析"""
|
||||
return self.analyze(image, mode="chart")
|
||||
|
||||
def analyze_fashion(self, image: Union[str, bytes]) -> Dict[str, Any]:
|
||||
"""穿搭分析"""
|
||||
return self.analyze(image, mode="fashion")
|
||||
|
||||
def analyze_product(self, image: Union[str, bytes]) -> Dict[str, Any]:
|
||||
"""产品分析"""
|
||||
return self.analyze(image, mode="product")
|
||||
|
||||
def analyze_scene(self, image: Union[str, bytes]) -> Dict[str, Any]:
|
||||
"""场景分析"""
|
||||
return self.analyze(image, mode="scene")
|
||||
|
||||
def batch_analyze(
|
||||
self,
|
||||
images: List[str],
|
||||
mode: str = "describe"
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
批量分析多张图片
|
||||
|
||||
Args:
|
||||
images: 图片路径列表
|
||||
mode: 分析模式
|
||||
|
||||
Returns:
|
||||
分析结果列表
|
||||
"""
|
||||
results = []
|
||||
for image in images:
|
||||
result = self.analyze(image, mode=mode)
|
||||
result["image"] = image
|
||||
results.append(result)
|
||||
return results
|
||||
|
||||
|
||||
def main():
|
||||
"""命令行入口"""
|
||||
import argparse
|
||||
|
||||
parser = argparse.ArgumentParser(description='图生文分析工具（视觉识别）')
|
||||
parser.add_argument('image', help='输入图片路径')
|
||||
parser.add_argument('-m', '--mode', default='describe',
|
||||
choices=['describe', 'ocr', 'chart', 'fashion', 'product', 'scene'],
|
||||
help='分析模式')
|
||||
parser.add_argument('-p', '--prompt', help='自定义分析提示词')
|
||||
parser.add_argument('--max-tokens', type=int, default=2000, help='最大输出 token 数')
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
analyzer = ImageToTextAnalyzer()
|
||||
result = analyzer.analyze(
|
||||
image=args.image,
|
||||
prompt=args.prompt,
|
||||
mode=args.mode,
|
||||
max_tokens=args.max_tokens
|
||||
)
|
||||
|
||||
if result["success"]:
|
||||
print(f"\n=== 分析结果 ({result['mode']}) ===\n")
|
||||
print(result["content"])
|
||||
print(f"\n=== Token 使用 ===")
|
||||
print(f"输入: {result['usage'].get('prompt_tokens', 'N/A')}")
|
||||
print(f"输出: {result['usage'].get('completion_tokens', 'N/A')}")
|
||||
else:
|
||||
print(f"分析失败: {result['error']}")
|
||||
print(f"详情: {result.get('detail', 'N/A')}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user