#!/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, analyze_duration=None, focus_threshold=None, scene=None, api_url=None, api_key=None, output_level=None): """调用API进行专注度分析""" 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 analyze_duration: ConstantEnum.DEFAULT_ANALYZE_DURATION = analyze_duration if focus_threshold: ConstantEnum.DEFAULT_FOCUS_THRESHOLD = focus_threshold if scene: ConstantEnum.DEFAULT_SCENE = scene try: input_path = input_path or url # 携带额外参数 params = {} if analyze_duration: params["analyze_duration"] = analyze_duration if focus_threshold: params["focus_threshold"] = focus_threshold if scene: params["scene"] = scene 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(open_id=open_id) 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", analyze_duration=30, focus_threshold=0.6, scene="classroom"): """格式化输出结果""" scene_map = { "classroom": "课堂学习", "office": "办公会议", "driving": "驾驶出行" } scene_cn = scene_map.get(scene, scene) 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('focusAnalysisResponse', {}), ensure_ascii=False, indent=2) else: return "⚠️ 暂无分析结果" return f""" 📊 专注度分析结构化结果 {result_json} """, result_id elif output_level == "basic": # 精简输出 data = result.get('data', {}) analysis = data.get('analysis', {}) return f""" 📊 专注度分析报告 {'=' * 40} 应用场景: {scene_cn} 分析时长: {analyze_duration} 分钟 整体专注度评分: {analysis.get('overall_focus_score', '未知')} 专注时长占比: {analysis.get('focus_ratio', '未知')}% 分心走神次数: {analysis.get('distraction_count', 0)} """ elif output_level == "standard": # 标准输出 data = result.get('data', {}) analysis = data.get('analysis', {}) time_stats = f""" 总分析时长: {analyze_duration} 分钟 专注时长: {analysis.get('focus_duration', 0)} 分钟 分心时长: {analysis.get('distraction_duration', 0)} 分钟 专注占比: {analysis.get('focus_ratio', 0)}%""" distraction_stats = "\n".join([f" ⏰ {item.get('time_period')}: 专注度 {item.get('avg_score')}" for item in analysis.get('time_period_stats', [])]) suggestions = "\n".join([f" 💡 {item}" for item in data.get('improve_suggestions', [])]) return f""" 📊 专注度分析报告 {'=' * 50} ⏰ 分析时间: {data.get('analysis_time', '未知')} 📌 应用场景: {scene_cn} 🎯 专注度阈值: {focus_threshold} 🔍 分析结果: {time_stats} 整体专注度评分: {analysis.get('overall_focus_score', '未知')} 分心走神总次数: {analysis.get('distraction_count', 0)} 是否整体达标: {'✅ 达标' if analysis.get('is_qualified') else '⚠️ 未达标'} 分段专注度统计: {distraction_stats if distraction_stats else ' 无分段统计'} 💡 专注度改善建议: {suggestions if suggestions else ' 当前专注度表现不错，请继续保持！'} {'=' * 50} > 注：本报告仅供参考，不能替代人工评估，具体改善方案请结合实际情况调整。 """ else: # 完整输出（JSON格式） return json.dumps(result, ensure_ascii=False, indent=2) def main(): parser = argparse.ArgumentParser(description="专注度分析工具") 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("--analyze-duration", type=int, default=ConstantEnum.DEFAULT__ANALYZE_DURATION, help="分析视频时长，单位：分钟，默认 30") parser.add_argument("--focus-threshold", type=float, default=ConstantEnum.DEFAULT__FOCUS_THRESHOLD, help="专注度阈值，低于该分值判定为分心，默认 0.6") parser.add_argument("--scene", choices=["classroom", "office", "driving"], default=ConstantEnum.DEFAULT__SCENE, help="应用场景：classroom(课堂学习), office(办公会议), driving(驾驶)，默认 classroom") 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="显示专注度分析列表清单") 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("🔍 正在进行专注度分析，请稍候...") output_content = analyze_video( input_path=args.input, url=args.url, analyze_duration=args.analyze_duration, focus_threshold=args.focus_threshold, scene=args.scene, 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"❌ 专注度分析失败: {str(e)}") exit(1) if __name__ == "__main__": main()