#!/usr/bin/env python3 import sys import os current_dir = os.path.dirname(os.path.abspath(__file__)) parent_dir = os.path.dirname(os.path.dirname(os.path.dirname(current_dir))) sys.path.insert(0, parent_dir) import argparse import json import mimetypes import traceback from datetime import datetime import requests import sys import os from .config import * from .skill import skill from skills.smyx_common.scripts.util import RequestUtil # 从config导入常量 SUPPORTED_FORMATS = ConstantEnum.SUPPORTED_FORMATS MAX_FILE_SIZE_MB = ConstantEnum.MAX_FILE_SIZE_MB def validate_file(file_path): """验证输入文件是否合法""" if not os.path.exists(file_path): raise FileNotFoundError(f"文件不存在: {file_path}") if not os.access(file_path, os.R_OK): raise PermissionError(f"文件没有读权限: {file_path}") ext = os.path.splitext(file_path)[1].lower()[1:] if ext not in SUPPORTED_FORMATS: raise ValueError(f"不支持的文件格式，支持的格式: {', '.join(SUPPORTED_FORMATS)}") file_size_mb = os.path.getsize(file_path) / (1024 * 1024) if file_size_mb > MAX_FILE_SIZE_MB: raise ValueError(f"文件过大，最大支持 {MAX_FILE_SIZE_MB}MB，当前文件大小: {file_size_mb:.1f}MB") return True def analyze_video(input_path=None, url=None, duration_min=None, api_url=None, api_key=None, output_level=None): """调用API进行宠物行为识别""" if not input_path and not url: raise ValueError("必须提供本地视频路径(--input)或网络视频URL(--url)") # 设置参数 if duration_min and duration_min > 0: ConstantEnum.DEFAULT_DURATION_MIN = duration_min try: input_path = input_path or url params = {} if duration_min and duration_min > 0: params["duration_min"] = duration_min return skill.get_output_analysis(input_path, params) except requests.exceptions.RequestException as e: traceback.print_stack() raise Exception(f"API请求失败: {str(e)}") def show_analyze_list(open_id, start_time=None, end_time=None): # if not open_id: # raise ValueError("必须提供本用户的OpenId/UserId") try: output_content = skill.get_output_analysis_list() return output_content except requests.exceptions.RequestException as e: traceback.print_stack() raise Exception(f"API请求失败: {str(e)}") def get_analysis_export_url(request_id=None): """调用API分析视频""" if not request_id: return "" return ApiEnum.DETAIL_EXPORT_URL + request_id def format_result(result, output_level="standard", duration_min=0): """格式化输出结果""" behavior_map = { "scratching": "抓挠", "chewing": "啃咬", "destroying": "拆家", "jumping": "跳跃", "digging": "刨地", "chasing": "追逐", "anxiety": "独处焦虑" } if output_level == "json": result_id = None if result is not None: result_json = result result_id = result_json.get('id', {}) result_json = json.dumps(result_json.get('behaviorDetectionResponse', {}), ensure_ascii=False, indent=2) else: return "⚠️ 暂无分析结果" return f""" 📊 宠物行为识别分析结构化结果 {result_json} """, result_id elif output_level == "basic": # 精简输出 data = result.get('data', {}) behavior_stats = data.get('behavior_stats', {}) abnormal_count = sum(v.get('count', 0) for k, v in behavior_stats.items() if k in ['scratching', 'chewing', 'destroying', 'anxiety']) return f""" 📊 宠物行为识别报告 {'=' * 40} 统计时长: {duration_min if duration_min > 0 else '自动识别'} 分钟 异常行为次数: {abnormal_count} 主要异常行为: {', '.join([behavior_map.get(k, k) for k, v in behavior_stats.items() if v.get('count', 0) > 0])} """ elif output_level == "standard": # 标准输出 data = result.get('data', {}) behavior_stats = data.get('behavior_stats', {}) abnormal_count = sum(v.get('count', 0) for k, v in behavior_stats.items() if k in ['scratching', 'chewing', 'destroying', 'anxiety']) behaviors = "\n".join( [f" {behavior_map.get(k, k)}: {v.get('count', 0)} 次，占比 {v.get('duration_percent', 0)}%" for k, v in behavior_stats.items()]) suggestions = "\n".join([f" 💡 {item}" for item in data.get('suggestions', ['无特殊建议'])]) return f""" 📊 宠物行为识别分析报告 {'=' * 50} ⏰ 分析时间: {data.get('analysis_time', '未知')} 📊 统计时长: {duration_min if duration_min > 0 else '自动识别'} 分钟 🔍 行为统计: 总异常行为次数: {abnormal_count} 各类行为统计: {behaviors if behaviors else ' ✅ 未识别到明显行为'} 💡 建议提示: {suggestions} {'=' * 50} > 注：本报告仅供宠物行为参考，行为矫正请咨询专业宠物训练师。 """ else: # 完整输出（JSON格式） return json.dumps(result, ensure_ascii=False, indent=2) def main(): parser = argparse.ArgumentParser(description="宠物行为识别工具") parser.add_argument("--input", help="本地视频文件路径") parser.add_argument("--url", help="网络视频的URL地址") parser.add_argument("--duration-min", type=float, default=ConstantEnum.DEFAULT__DURATION_MIN, help="统计时长（分钟），默认自动识别") parser.add_argument("--open-id", required=True, help="当前用户的OpenID/UserId/用户名/手机号") parser.add_argument("--list", action='store_true', help="显示宠物行为识别列表清单") parser.add_argument("--api-url", help="服务端API地址") parser.add_argument("--api-key", help="API访问密钥（必需）") parser.add_argument("--output", help="结果输出文件路径") parser.add_argument("--detail", choices=["basic", "standard", "json"], default=ConstantEnum.DEFAULT__OUTPUT_LEVEL, help="输出详细程度") parser.add_argument("--export-env-only", action='store_true', help="仅输出 export 命令设置环境变量，不执行分析") args = parser.parse_args() try: if args.open_id: # 设置 Python 进程内的环境变量 ConstantEnumBase.CURRENT__OPEN_ID = args.open_id # 检查必需参数 if args.list: open_id = ConstantEnum.CURRENT__OPEN_ID result = show_analyze_list(open_id) print(result) exit(0) # 检查必需参数 if not args.input and not args.url: print("❌ 错误: 必须提供 --input 或 --url 参数") exit(1) print("🔍 正在进行宠物行为识别分析，请稍候...") output_content = analyze_video( input_path=args.input, url=args.url, duration_min=args.duration_min, api_url=args.api_url, api_key=args.api_key, output_level=args.detail ) print(output_content) # 保存到文件 if args.output: with open(args.output, "w", encoding="utf-8") as f: if args.detail == "full": json.dump(result, f, ensure_ascii=False, indent=2) else: f.write(output_content) print(f"✅ 结果已保存到: {args.output}") except Exception as e: traceback.print_stack() print(f"❌ 宠物行为识别分析失败: {str(e)}") exit(1) if __name__ == "__main__": main()