7aa71c5f83
本次提交实现了完整的人员行为分析系统，包括： 1. 新增基于位置和跟踪ID的两种行为检测算法 2. 新增徘徊检测服务与行为处理器模块 3. 前后端集成算法配置界面与告警展示 4. 支持图片和视频流场景下的行为分析 5. 新增算法配置接口与文档说明 具体改动： - 新增loitering_detection模型目录与算法实现 - 新增AlgorithmConfig组件实现可视化配置 - 扩展图片/视频检测接口支持算法参数传递 - 新增行为告警推送与前端展示页面 - 优化检测服务，集成行为分析逻辑 - 移除冗余日志输出，完善代码注释
788 lines
19 KiB
Vue
788 lines
19 KiB
Vue
<template>
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<div class="image-detection-container">
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<!-- 左侧配置面板 -->
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<div class="left-panel" :style="{ width: leftPanelWidth + 'px' }">
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<el-card class="config-card" shadow="hover">
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<template #header>
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<div class="card-header">
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<el-icon class="header-icon"><Setting /></el-icon>
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<span>图片检测配置</span>
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</div>
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</template>
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<el-form label-position="top" class="config-form">
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<el-form-item label="选择模型">
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<el-select
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v-model="config.model"
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placeholder="选择检测模型"
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class="full-width"
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>
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<el-option
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v-for="model in models"
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:key="model.id"
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:label="model.name"
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:value="model.id"
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>
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<span>{{ model.name }}</span>
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<span class="model-size">{{ model.size }}</span>
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</el-option>
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</el-select>
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</el-form-item>
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<el-form-item>
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<template #label>
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<span>置信度阈值</span>
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<el-tooltip placement="top" :show-after="200">
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<template #content>
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<div style="max-width: 300px; line-height: 1.6;">
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<p><strong>置信度是什么？</strong></p>
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<p>表示模型对检测结果的"确定程度"，范围 0-1</p>
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<ul style="margin: 8px 0; padding-left: 16px;">
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<li>大于等于0.8：高置信度（绿色）- 模型非常确定</li>
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<li>0.6-0.8：中等置信度（黄色）- 模型比较确定</li>
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<li>小于0.6：低置信度（红色）- 模型不太确定</li>
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</ul>
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<p><strong>阈值作用：</strong></p>
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<p>低于此值的检测结果会被过滤掉</p>
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<p>建议：0.3-0.5（火灾检测可适当降低）</p>
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</div>
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</template>
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<el-icon class="help-icon"><QuestionFilled /></el-icon>
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</el-tooltip>
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</template>
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<el-slider
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v-model="config.confidence"
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:min="0.1"
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:max="1.0"
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:step="0.05"
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:format-tooltip="formatConfidence"
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/>
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<div class="slider-value">{{ config.confidence.toFixed(2) }}</div>
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</el-form-item>
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<el-form-item>
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<template #label>
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<span>IOU阈值</span>
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<el-tooltip placement="top" :show-after="200">
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<template #content>
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<div style="max-width: 320px; line-height: 1.6;">
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<p><strong>IOU是什么？</strong></p>
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<p>交并比(Intersection Over Union)，衡量两个检测框的重叠程度</p>
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<p style="margin: 8px 0;"><strong>计算公式：</strong></p>
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<p style=" padding: 4px 8px; border-radius: 4px; font-family: monospace;">IOU = 交集面积 / 并集面积</p>
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<p style="margin: 8px 0;"><strong>阈值作用：</strong></p>
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<p>用于NMS去重，IOU超过此值的框被认为是重复检测</p>
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<ul style="margin: 8px 0; padding-left: 16px;">
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<li>高阈值(0.7-0.9)：保留更多框，适合密集场景</li>
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<li>中阈值(0.45-0.6)：平衡，适合一般场景</li>
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<li>低阈值(0.1-0.3)：结果更精简，适合稀疏场景</li>
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</ul>
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<p><strong>建议：0.45-0.6</strong></p>
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</div>
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</template>
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<el-icon class="help-icon"><QuestionFilled /></el-icon>
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</el-tooltip>
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</template>
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<el-slider
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v-model="config.iou"
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:min="0.1"
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:max="0.9"
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:step="0.05"
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:format-tooltip="formatIOU"
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/>
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<div class="slider-value">{{ config.iou.toFixed(2) }}</div>
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</el-form-item>
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<!-- 算法配置（仅对人员检测模型显示） -->
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<AlgorithmConfig
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v-model="config.algorithmConfig"
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@change="onAlgorithmChange"
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:model-id="config.model"
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/>
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</el-form>
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</el-card>
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</div>
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<!-- 拖拽调整条 -->
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<div
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class="resize-handle"
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@mousedown="startResize"
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:class="{ 'resizing': isResizing }"
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>
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<div class="resize-indicator"></div>
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</div>
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<!-- 右侧展示区域 -->
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<div class="right-panel" :style="{ width: `calc(100% - ${leftPanelWidth}px - 8px)` }">
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<!-- 检测结果和统计信息并排 -->
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<el-row :gutter="20">
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<!-- 检测结果区域 -->
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<el-col :span="stats ? 16 : 24">
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<el-card class="image-card result-card" shadow="hover">
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<template #header>
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<div class="card-header">
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<div class="header-left">
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<el-icon class="header-icon"><View /></el-icon>
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<span>检测结果</span>
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</div>
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<el-upload
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:action="uploadUrl"
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:on-success="handleUploadSuccess"
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:before-upload="beforeUpload"
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:show-file-list="false"
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accept="image/*"
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class="header-upload"
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>
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<el-button type="primary" size="small">
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<el-icon><UploadFilled /></el-icon>
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<span>{{ resultImage ? '上传新图片' : '上传图片' }}</span>
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</el-button>
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</el-upload>
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</div>
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</template>
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<div class="image-container">
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<img
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v-if="resultImage"
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:src="resultImage"
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class="display-image"
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alt="检测结果"
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/>
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<div v-else class="empty-placeholder">
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<el-icon class="empty-icon"><Picture /></el-icon>
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<p class="empty-text">请上传图片进行检测</p>
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<p class="empty-hint">支持 JPG、PNG、WEBP 格式</p>
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</div>
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</div>
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</el-card>
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</el-col>
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<!-- 统计信息 -->
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<el-col v-if="stats" :span="8">
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<el-card class="stats-card" shadow="hover">
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<template #header>
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<div class="card-header">
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<el-icon class="header-icon"><DataLine /></el-icon>
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<span>检测统计</span>
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</div>
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</template>
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<div class="stats-content">
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<div class="stat-item">
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<div class="stat-label">检测数量</div>
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<el-tag size="large" type="primary">{{ stats.total_detections }} 个</el-tag>
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</div>
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<div class="stat-item">
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<div class="stat-label">平均置信度</div>
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<el-tag size="large" :type="getConfidenceType(stats.avg_confidence)">
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{{ stats.avg_confidence?.toFixed(2) }}
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</el-tag>
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</div>
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<div class="stat-item">
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<div class="stat-label">处理时间</div>
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<el-tag size="large" type="info">{{ stats.processing_time?.toFixed(2) }}s</el-tag>
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</div>
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<div class="stat-item">
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<div class="stat-label">使用模型</div>
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<el-tag size="large" type="success">{{ modelName }}</el-tag>
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</div>
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</div>
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</el-card>
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</el-col>
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</el-row>
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<!-- 检测详情 -->
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<el-card v-if="detections.length > 0" class="details-card" shadow="hover">
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<template #header>
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<div class="card-header">
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<el-icon class="header-icon"><List /></el-icon>
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<span>检测详情</span>
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</div>
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</template>
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<el-table :data="detections" border class="details-table">
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<el-table-column prop="label" label="类别" min-width="120" />
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<el-table-column prop="confidence" label="置信度" width="120">
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<template #default="scope">
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<el-tag :type="getConfidenceType(scope.row.confidence)">
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{{ scope.row.confidence }}
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</el-tag>
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</template>
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</el-table-column>
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<el-table-column prop="bbox" label="位置" min-width="200">
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<template #default="scope">
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<code class="bbox-code">[{{ scope.row.bbox.join(', ') }}]</code>
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</template>
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</el-table-column>
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</el-table>
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</el-card>
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</div>
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</div>
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</template>
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<script setup>
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import { ref, computed } from 'vue'
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import { ElMessage } from 'element-plus'
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import {
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UploadFilled,
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Picture,
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Document,
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Setting,
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View,
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DataLine,
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List,
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QuestionFilled
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} from '@element-plus/icons-vue'
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import { detectionApi } from '@/api/detection'
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import AlgorithmConfig from './AlgorithmConfig.vue'
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const props = defineProps({
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models: {
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type: Array,
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default: () => []
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}
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})
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const config = ref({
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model: props.models.length > 0 ? props.models[0].id : 'fire_detection',
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confidence: 0.5,
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iou: 0.45,
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algorithmConfig: {}
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})
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// 可拖拽调整宽度相关
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const leftPanelWidth = ref(320)
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const isResizing = ref(false)
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const startX = ref(0)
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const startWidth = ref(0)
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const startResize = (e) => {
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isResizing.value = true
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startX.value = e.clientX
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startWidth.value = leftPanelWidth.value
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document.addEventListener('mousemove', handleResize)
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document.addEventListener('mouseup', stopResize)
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}
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const handleResize = (e) => {
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if (!isResizing.value) return
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const delta = e.clientX - startX.value
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const newWidth = startWidth.value + delta
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leftPanelWidth.value = Math.max(280, Math.min(500, newWidth))
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}
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const stopResize = () => {
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isResizing.value = false
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document.removeEventListener('mousemove', handleResize)
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document.removeEventListener('mouseup', stopResize)
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}
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const originalImage = ref('')
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const resultImage = ref('')
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const detections = ref([])
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const stats = ref(null)
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const uploadUrl = computed(() => {
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const params = new URLSearchParams({
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model_id: config.value.model,
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confidence: config.value.confidence,
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iou: config.value.iou
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})
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// 添加算法配置
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if (config.value.algorithmConfig && Object.keys(config.value.algorithmConfig).length > 0) {
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params.append('algorithm_config', JSON.stringify(config.value.algorithmConfig))
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}
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return `/api/detect/image?${params.toString()}`
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})
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const formatConfidence = (value) => {
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return `置信度: ${value.toFixed(2)}`
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}
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const formatIOU = (value) => {
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return `IOU: ${value.toFixed(2)}`
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}
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const beforeUpload = (file) => {
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const isImage = file.type.startsWith('image/')
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if (!isImage) {
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ElMessage.error('只能上传图片文件')
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return false
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}
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originalImage.value = URL.createObjectURL(file)
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return true
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}
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const handleUploadSuccess = (response) => {
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console.log('Upload success response:', response)
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if (response.success) {
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// 使用 base64 图片数据
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if (response.data.image_base64) {
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resultImage.value = `data:image/jpeg;base64,${response.data.image_base64}`
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console.log('Result image set, length:', response.data.image_base64.length)
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} else {
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console.error('No image_base64 in response:', response.data)
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}
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detections.value = response.data.detections || []
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stats.value = response.data.stats
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// 处理告警信息
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if (response.data.alerts && response.data.alerts.length > 0) {
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alerts.value = response.data.alerts
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console.log('收到告警:', response.data.alerts)
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// 显示告警通知
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response.data.alerts.forEach(alert => {
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ElMessage({
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message: `行为告警: ${alert.type} - ${alert.message}`,
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type: 'warning',
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duration: 3000
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})
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})
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}
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ElMessage.success('检测完成')
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} else {
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ElMessage.error(response.message)
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}
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}
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const getConfidenceType = (confidence) => {
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if (!confidence && confidence !== 0) return 'info'
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if (confidence >= 0.8) return 'success'
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if (confidence >= 0.6) return 'warning'
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return 'danger'
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}
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const modelName = computed(() => {
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const model = props.models.find(m => m.id === config.value.model)
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return model ? model.name : config.value.model
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})
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const onAlgorithmChange = (algoConfig) => {
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config.value.algorithmConfig = algoConfig
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}
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</script>
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<style scoped>
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.image-detection-container {
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display: flex;
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width: 100%;
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height: calc(100vh - 100px);
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gap: 0;
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}
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.left-panel {
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flex-shrink: 0;
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overflow: hidden;
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}
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.left-panel .config-card {
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height: 100%;
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overflow-y: auto;
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}
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/* 拖拽调整条 */
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.resize-handle {
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width: 8px;
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flex-shrink: 0;
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cursor: col-resize;
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display: flex;
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align-items: center;
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justify-content: center;
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background: transparent;
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transition: background 0.2s;
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position: relative;
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}
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.resize-handle:hover {
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background: #d0d0d0;
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}
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.resize-handle.resizing {
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background: #409eff;
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cursor: col-resize;
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}
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.resize-indicator {
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width: 3px;
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height: 40px;
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background: #c0c4cc;
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border-radius: 2px;
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transition: background 0.2s;
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}
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.resize-handle:hover .resize-indicator,
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.resize-handle.resizing .resize-indicator {
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background: #409eff;
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}
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.right-panel {
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flex: 1;
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overflow-y: auto;
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overflow-x: hidden;
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}
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/* 卡片通用样式 */
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:deep(.el-card) {
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border-radius: 12px;
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border: none;
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transition: all 0.3s ease;
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}
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:deep(.el-card__header) {
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padding: 16px 20px;
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border-bottom: 1px solid #e4e7ed;
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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border-radius: 12px 12px 0 0;
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}
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/* 卡片头部样式 */
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.card-header {
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display: flex;
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align-items: center;
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justify-content: space-between;
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font-weight: 600;
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font-size: 16px;
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color: #fff;
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}
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.header-left {
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display: flex;
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align-items: center;
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gap: 8px;
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}
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.header-icon {
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font-size: 18px;
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}
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.header-upload :deep(.el-upload) {
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display: block;
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}
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/* 配置卡片样式 */
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.config-card {
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height: auto;
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max-height: calc(100vh - 100px);
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overflow-y: auto;
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}
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.config-card :deep(.el-card__body) {
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padding: 24px;
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}
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.config-form :deep(.el-form-item) {
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margin-bottom: 20px;
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}
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.config-form :deep(.el-form-item__label) {
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font-weight: 500;
|
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font-size: 14px;
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color: #303133;
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padding-bottom: 8px;
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}
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.full-width {
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width: 100%;
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}
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|
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/* 模型选择器 */
|
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.model-size {
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float: right;
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color: #909399;
|
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font-size: 12px;
|
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}
|
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|
||
/* 滑块样式 */
|
||
.slider-value {
|
||
text-align: center;
|
||
font-size: 14px;
|
||
font-weight: 600;
|
||
color: #409eff;
|
||
margin-top: 8px;
|
||
padding: 6px 12px;
|
||
background: #ecf5ff;
|
||
border-radius: 20px;
|
||
display: inline-block;
|
||
min-width: 60px;
|
||
}
|
||
|
||
/* 空状态占位区域 */
|
||
.empty-placeholder {
|
||
display: flex;
|
||
flex-direction: column;
|
||
align-items: center;
|
||
justify-content: center;
|
||
width: 100%;
|
||
height: 100%;
|
||
color: #909399;
|
||
}
|
||
|
||
.empty-icon {
|
||
font-size: 64px;
|
||
color: #dcdfe6;
|
||
margin-bottom: 16px;
|
||
}
|
||
|
||
.empty-text {
|
||
font-size: 16px;
|
||
color: #606266;
|
||
margin: 0 0 8px 0;
|
||
}
|
||
|
||
.empty-hint {
|
||
font-size: 13px;
|
||
color: #909399;
|
||
margin: 0;
|
||
}
|
||
|
||
/* 图片展示区域 */
|
||
.image-card {
|
||
margin-bottom: 20px;
|
||
}
|
||
|
||
.result-card {
|
||
margin-bottom: 20px;
|
||
}
|
||
|
||
.image-card :deep(.el-card__body) {
|
||
padding: 0;
|
||
}
|
||
|
||
.image-container {
|
||
width: 100%;
|
||
aspect-ratio: 16 / 9;
|
||
min-height: 400px;
|
||
max-height: 600px;
|
||
display: flex;
|
||
align-items: center;
|
||
justify-content: center;
|
||
background: #f5f7fa;
|
||
border-radius: 0 0 12px 12px;
|
||
overflow: hidden;
|
||
position: relative;
|
||
}
|
||
|
||
.display-image {
|
||
width: 100%;
|
||
height: 100%;
|
||
object-fit: contain;
|
||
background: #000;
|
||
}
|
||
|
||
.placeholder {
|
||
text-align: center;
|
||
color: #909399;
|
||
padding: 40px 20px;
|
||
}
|
||
|
||
.placeholder-icon {
|
||
font-size: 64px;
|
||
color: #dcdfe6;
|
||
margin-bottom: 16px;
|
||
}
|
||
|
||
.placeholder p {
|
||
font-size: 14px;
|
||
margin: 0;
|
||
}
|
||
|
||
/* 统计卡片 */
|
||
.stats-card {
|
||
margin-bottom: 20px;
|
||
height: calc(100% - 20px);
|
||
}
|
||
|
||
.stats-card :deep(.el-card__body) {
|
||
padding: 20px;
|
||
}
|
||
|
||
.stats-content {
|
||
display: flex;
|
||
flex-direction: column;
|
||
gap: 16px;
|
||
}
|
||
|
||
.stat-item {
|
||
display: flex;
|
||
flex-direction: column;
|
||
gap: 8px;
|
||
padding: 12px;
|
||
background: #f5f7fa;
|
||
border-radius: 8px;
|
||
}
|
||
|
||
.stat-label {
|
||
font-size: 13px;
|
||
color: #606266;
|
||
font-weight: 500;
|
||
}
|
||
|
||
.stat-item :deep(.el-tag) {
|
||
font-size: 14px;
|
||
font-weight: 500;
|
||
align-self: flex-start;
|
||
}
|
||
|
||
/* 详情卡片 */
|
||
.details-card {
|
||
margin-bottom: 20px;
|
||
}
|
||
|
||
.details-card :deep(.el-card__body) {
|
||
padding: 0;
|
||
}
|
||
|
||
.details-table :deep(.el-table__header) {
|
||
background: #f5f7fa;
|
||
}
|
||
|
||
.details-table :deep(.el-table__header th) {
|
||
background: #f5f7fa;
|
||
font-weight: 600;
|
||
color: #303133;
|
||
}
|
||
|
||
.bbox-code {
|
||
background: #f5f7fa;
|
||
padding: 4px 8px;
|
||
border-radius: 4px;
|
||
font-family: 'Courier New', monospace;
|
||
font-size: 12px;
|
||
color: #606266;
|
||
}
|
||
|
||
/* 帮助图标样式 */
|
||
.help-icon {
|
||
margin-left: 6px;
|
||
font-size: 14px;
|
||
color: #909399;
|
||
cursor: pointer;
|
||
transition: color 0.2s;
|
||
}
|
||
|
||
.help-icon:hover {
|
||
color: #409eff;
|
||
}
|
||
|
||
/* 告警卡片 */
|
||
.alerts-card {
|
||
margin-bottom: 20px;
|
||
border: 2px solid #f56c6c;
|
||
}
|
||
|
||
.alerts-card .card-header {
|
||
display: flex;
|
||
justify-content: space-between;
|
||
align-items: center;
|
||
}
|
||
|
||
.alert-count {
|
||
margin-left: 8px;
|
||
}
|
||
|
||
.alerts-container {
|
||
max-height: 400px;
|
||
overflow-y: auto;
|
||
padding: 16px;
|
||
}
|
||
|
||
.alert-item {
|
||
background: #fef0f0;
|
||
border-left: 4px solid #f56c6c;
|
||
padding: 12px;
|
||
border-radius: 4px;
|
||
margin-bottom: 12px;
|
||
}
|
||
|
||
.alert-header {
|
||
display: flex;
|
||
align-items: center;
|
||
gap: 12px;
|
||
margin-bottom: 8px;
|
||
}
|
||
|
||
.alert-time {
|
||
font-size: 12px;
|
||
color: #909399;
|
||
}
|
||
|
||
.alert-detail {
|
||
display: flex;
|
||
align-items: center;
|
||
gap: 12px;
|
||
margin-bottom: 6px;
|
||
}
|
||
|
||
.alert-message {
|
||
font-size: 14px;
|
||
color: #f56c6c;
|
||
font-weight: 500;
|
||
}
|
||
|
||
.alert-duration {
|
||
font-size: 13px;
|
||
color: #606266;
|
||
background: #fff;
|
||
padding: 2px 8px;
|
||
border-radius: 4px;
|
||
}
|
||
|
||
.alert-bbox {
|
||
font-size: 12px;
|
||
color: #606266;
|
||
background: #fff;
|
||
padding: 4px 8px;
|
||
border-radius: 4px;
|
||
display: inline-block;
|
||
}
|
||
|
||
/* 响应式布局 */
|
||
@media (max-width: 768px) {
|
||
.image-detection-container {
|
||
flex-direction: column;
|
||
height: auto;
|
||
}
|
||
|
||
.left-panel {
|
||
width: 100% !important;
|
||
}
|
||
|
||
.config-card {
|
||
max-height: none;
|
||
margin-bottom: 16px;
|
||
}
|
||
|
||
.resize-handle {
|
||
display: none;
|
||
}
|
||
|
||
.right-panel {
|
||
width: 100% !important;
|
||
}
|
||
|
||
.image-container {
|
||
aspect-ratio: 4 / 3;
|
||
min-height: 200px;
|
||
}
|
||
|
||
.stats-descriptions :deep(.el-descriptions__body) {
|
||
display: grid;
|
||
grid-template-columns: 1fr 1fr;
|
||
gap: 8px;
|
||
}
|
||
|
||
.stats-descriptions :deep(.el-descriptions__cell) {
|
||
padding: 12px;
|
||
}
|
||
}
|
||
|
||
@media (max-width: 480px) {
|
||
.image-container {
|
||
aspect-ratio: 1 / 1;
|
||
min-height: 180px;
|
||
}
|
||
}
|
||
</style>
|