Add a progress bar corresponding to the gloss that can control the threshold.

Browse files

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

Files changed (3) hide show

SignX/eval/generate_gloss_frames.py +21 -9
SignX/eval/generate_interactive_alignment.py +666 -0
SignX/inference.sh +20 -1

SignX/eval/generate_gloss_frames.py CHANGED Viewed

@@ -15,6 +15,11 @@ import cv2
 from pathlib import Path
 import matplotlib.pyplot as plt
 import matplotlib.patches as mpatches
 def extract_video_frames(video_path, frame_indices):
     """从视频中提取指定索引的帧"""
@@ -136,19 +141,26 @@ def generate_gloss_to_frames_visualization(sample_dir, video_path, output_path):
         confidence = info.get('confidence', 'unknown')
         avg_attn = info.get('avg_attention', 0.0)
-        info_text = f"""特征帧: {feat_start} → {feat_peak} → {feat_end}
-相对时间: {rel_start:.1f}% → {rel_end:.1f}%
-原始帧: {vid_start} → {vid_peak} → {vid_end}
-总特征帧: {total_feat}
-总视频帧: {total_video_frames}
-置信度: {confidence}
-注意力: {avg_attn:.3f}"""
-        ax_info.text(0.1, 0.5, info_text,
-                     fontsize=10, family='monospace',
                      ha='left', va='center')
         ax_info.axis('off')
         # 列3：视频帧（Start | Peak | End）横向拼接

 from pathlib import Path
 import matplotlib.pyplot as plt
 import matplotlib.patches as mpatches
+import matplotlib.font_manager as fm
+# 设置中文字体支持
+plt.rcParams['font.sans-serif'] = ['WenQuanYi Micro Hei', 'DejaVu Sans']  # Linux中文字体
+plt.rcParams['axes.unicode_minus'] = False  # 解决负号显示问题
 def extract_video_frames(video_path, frame_indices):
     """从视频中提取指定索引的帧"""
         confidence = info.get('confidence', 'unknown')
         avg_attn = info.get('avg_attention', 0.0)
+        # 置信度颜色
+        conf_colors = {'high': 'green', 'medium': 'orange', 'low': 'red', 'unknown': 'gray'}
+        conf_color = conf_colors.get(confidence, 'gray')
+        info_text = f"""Feature idx: {feat_start} -> {feat_peak} -> {feat_end}
+Rel. time:   {rel_start:.1f}% -> {rel_end:.1f}%
+Video frame: {vid_start} -> {vid_peak} -> {vid_end}
+Total features: {total_feat}
+Total frames:   {total_video_frames}
+Confidence: {confidence.upper()}
+Attention:  {avg_attn:.3f}"""
+        ax_info.text(0.05, 0.5, info_text,
+                     fontsize=9, family='monospace',
                      ha='left', va='center')
+        # 添加置信度颜色条
+        ax_info.add_patch(mpatches.Rectangle((0.85, 0.2), 0.1, 0.6,
+                                             facecolor=conf_color, alpha=0.3))
         ax_info.axis('off')
         # 列3：视频帧（Start | Peak | End）横向拼接

SignX/eval/generate_interactive_alignment.py ADDED Viewed

	@@ -0,0 +1,666 @@

+#!/usr/bin/env python3
+"""
+生成交互式HTML可视化 - 可调整置信度阈值的gloss-to-feature对齐
+参考frame_alignment.png的布局风格
+使用方法：
+    python generate_interactive_alignment.py <sample_dir>
+例如：
+    python generate_interactive_alignment.py detailed_prediction_20251226_022246/sample_000
+"""
+import sys
+import json
+import numpy as np
+from pathlib import Path
+def generate_interactive_html(sample_dir, output_path):
+    """生成交互式HTML可视化 - 参考frame_alignment.png的风格"""
+    sample_dir = Path(sample_dir)
+    # 1. 读取注意力权重
+    attention_weights = np.load(sample_dir / "attention_weights.npy")
+    # shape: [time_steps, src_len, beam_size]
+    # 取beam 0的权重
+    attn_weights = attention_weights[:, :, 0]  # [time_steps, src_len]
+    # 2. 读取翻译结果
+    with open(sample_dir / "translation.txt", 'r') as f:
+        lines = f.readlines()
+        gloss_sequence = None
+        for line in lines:
+            if line.startswith('Clean:'):
+                gloss_sequence = line.replace('Clean:', '').strip()
+                break
+    if not gloss_sequence:
+        print("无法找到翻译结果")
+        return
+    glosses = gloss_sequence.split()
+    num_glosses = len(glosses)
+    num_features = attn_weights.shape[1]
+    print(f"Gloss序列: {glosses}")
+    print(f"特征数量: {num_features}")
+    print(f"Attention shape: {attn_weights.shape}")
+    # 3. 将attention权重转换为JSON可序列化格式
+    # 只取前num_glosses行（实际的gloss，不包括padding）
+    attn_data = []
+    for word_idx in range(min(num_glosses, attn_weights.shape[0])):
+        weights = attn_weights[word_idx, :].tolist()
+        attn_data.append({
+            'word': glosses[word_idx],
+            'word_idx': word_idx,
+            'weights': weights
+        })
+    # 4. 生成HTML内容
+    html_content = f"""<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Interactive Word-Frame Alignment</title>
+    <style>
+        body {{
+            font-family: 'Arial', sans-serif;
+            margin: 20px;
+            background-color: #f5f5f5;
+        }}
+        .container {{
+            max-width: 1800px;
+            margin: 0 auto;
+            background-color: white;
+            padding: 30px;
+            border-radius: 8px;
+            box-shadow: 0 2px 10px rgba(0,0,0,0.1);
+        }}
+        h1 {{
+            color: #333;
+            border-bottom: 3px solid #4CAF50;
+            padding-bottom: 10px;
+            margin-bottom: 20px;
+        }}
+        .stats {{
+            background-color: #E3F2FD;
+            padding: 15px;
+            border-radius: 5px;
+            margin-bottom: 20px;
+            border-left: 4px solid #2196F3;
+            font-size: 14px;
+        }}
+        .controls {{
+            background-color: #f9f9f9;
+            padding: 20px;
+            border-radius: 5px;
+            margin-bottom: 30px;
+            border: 1px solid #ddd;
+        }}
+        .control-group {{
+            margin-bottom: 15px;
+        }}
+        label {{
+            font-weight: bold;
+            display: inline-block;
+            width: 250px;
+            color: #555;
+        }}
+        input[type="range"] {{
+            width: 400px;
+            vertical-align: middle;
+        }}
+        .value-display {{
+            display: inline-block;
+            width: 80px;
+            font-family: monospace;
+            font-size: 14px;
+            color: #2196F3;
+            font-weight: bold;
+        }}
+        .reset-btn {{
+            margin-top: 15px;
+            padding: 10px 25px;
+            background-color: #2196F3;
+            color: white;
+            border: none;
+            border-radius: 5px;
+            cursor: pointer;
+            font-size: 14px;
+            font-weight: bold;
+        }}
+        .reset-btn:hover {{
+            background-color: #1976D2;
+        }}
+        canvas {{
+            border: 1px solid #999;
+            display: block;
+            margin: 20px auto;
+            background: white;
+        }}
+        .legend {{
+            margin-top: 20px;
+            padding: 15px;
+            background-color: #fff;
+            border: 1px solid #ddd;
+            border-radius: 5px;
+        }}
+        .legend-item {{
+            display: inline-block;
+            margin-right: 25px;
+            font-size: 13px;
+            margin-bottom: 10px;
+        }}
+        .color-box {{
+            display: inline-block;
+            width: 30px;
+            height: 15px;
+            margin-right: 8px;
+            vertical-align: middle;
+            border: 1px solid #666;
+        }}
+        .info-panel {{
+            margin-top: 20px;
+            padding: 15px;
+            background-color: #f9f9f9;
+            border-radius: 5px;
+            border: 1px solid #ddd;
+        }}
+        .confidence {{
+            display: inline-block;
+            padding: 3px 10px;
+            border-radius: 10px;
+            font-weight: bold;
+            font-size: 11px;
+            text-transform: uppercase;
+        }}
+        .confidence.high {{
+            background-color: #4CAF50;
+            color: white;
+        }}
+        .confidence.medium {{
+            background-color: #FF9800;
+            color: white;
+        }}
+        .confidence.low {{
+            background-color: #f44336;
+            color: white;
+        }}
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>🎯 Interactive Word-to-Frame Alignment Visualizer</h1>
+        <div class="stats">
+            <strong>Translation:</strong> {' '.join(glosses)}<br>
+            <strong>Total Words:</strong> {num_glosses} |
+            <strong>Total Features:</strong> {num_features}
+        </div>
+        <div class="controls">
+            <h3>⚙️ Threshold Controls</h3>
+            <div class="control-group">
+                <label for="peak-threshold">Peak Threshold (% of max):</label>
+                <input type="range" id="peak-threshold" min="1" max="100" value="30" step="1">
+                <span class="value-display" id="peak-threshold-value">30%</span>
+                <br>
+                <small style="margin-left: 255px; color: #666;">
+                    帧的注意力权重 ≥ (峰值权重 × 阈值%) 时被认为是"显著帧"
+                </small>
+            </div>
+            <div class="control-group">
+                <label for="confidence-high">High Confidence (avg attn >):</label>
+                <input type="range" id="confidence-high" min="0" max="100" value="50" step="1">
+                <span class="value-display" id="confidence-high-value">0.50</span>
+            </div>
+            <div class="control-group">
+                <label for="confidence-medium">Medium Confidence (avg attn >):</label>
+                <input type="range" id="confidence-medium" min="0" max="100" value="20" step="1">
+                <span class="value-display" id="confidence-medium-value">0.20</span>
+            </div>
+            <button class="reset-btn" onclick="resetDefaults()">
+                Reset to Defaults
+            </button>
+        </div>
+        <div>
+            <h3>Word-to-Frame Alignment</h3>
+            <p style="color: #666; font-size: 13px;">
+                每个词显示为彩色矩形，宽度表示该词对应的特征帧范围。★ = 峰值帧。矩形内部显示注意力权重波形。
+            </p>
+            <canvas id="alignment-canvas" width="1600" height="600"></canvas>
+            <h3 style="margin-top: 30px;">Timeline Progress Bar</h3>
+            <canvas id="timeline-canvas" width="1600" height="100"></canvas>
+            <div class="legend">
+                <strong>Legend:</strong><br><br>
+                <div class="legend-item">
+                    <span class="confidence high">High</span>
+                    <span class="confidence medium">Medium</span>
+                    <span class="confidence low">Low</span>
+                    Confidence Levels (opacity reflects confidence)
+                </div>
+                <div class="legend-item">
+                    <span style="color: red; font-size: 20px;">★</span>
+                    Peak Frame (highest attention)
+                </div>
+                <div class="legend-item">
+                    <span style="color: blue;">━</span>
+                    Attention Waveform (within word region)
+                </div>
+            </div>
+        </div>
+        <div class="info-panel">
+            <h3>Alignment Details</h3>
+            <div id="alignment-details"></div>
+        </div>
+    </div>
+    <script>
+        // Attention data from Python
+        const attentionData = {json.dumps(attn_data, ensure_ascii=False)};
+        const numGlosses = {num_glosses};
+        const numFeatures = {num_features};
+        // Colors for different words (matching matplotlib tab20)
+        const colors = [
+            '#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd',
+            '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf',
+            '#aec7e8', '#ffbb78', '#98df8a', '#ff9896', '#c5b0d5',
+            '#c49c94', '#f7b6d2', '#c7c7c7', '#dbdb8d', '#9edae5'
+        ];
+        // Get controls
+        const peakThresholdSlider = document.getElementById('peak-threshold');
+        const peakThresholdValue = document.getElementById('peak-threshold-value');
+        const confidenceHighSlider = document.getElementById('confidence-high');
+        const confidenceHighValue = document.getElementById('confidence-high-value');
+        const confidenceMediumSlider = document.getElementById('confidence-medium');
+        const confidenceMediumValue = document.getElementById('confidence-medium-value');
+        const alignmentCanvas = document.getElementById('alignment-canvas');
+        const timelineCanvas = document.getElementById('timeline-canvas');
+        const alignmentCtx = alignmentCanvas.getContext('2d');
+        const timelineCtx = timelineCanvas.getContext('2d');
+        // Update displays when sliders change
+        peakThresholdSlider.oninput = function() {{
+            peakThresholdValue.textContent = this.value + '%';
+            updateVisualization();
+        }};
+        confidenceHighSlider.oninput = function() {{
+            confidenceHighValue.textContent = (this.value / 100).toFixed(2);
+            updateVisualization();
+        }};
+        confidenceMediumSlider.oninput = function() {{
+            confidenceMediumValue.textContent = (this.value / 100).toFixed(2);
+            updateVisualization();
+        }};
+        function resetDefaults() {{
+            peakThresholdSlider.value = 30;
+            confidenceHighSlider.value = 50;
+            confidenceMediumSlider.value = 20;
+            peakThresholdValue.textContent = '30%';
+            confidenceHighValue.textContent = '0.50';
+            confidenceMediumValue.textContent = '0.20';
+            updateVisualization();
+        }}
+        function calculateAlignment(weights, peakThreshold) {{
+            // Find peak
+            let peakIdx = 0;
+            let peakWeight = weights[0];
+            for (let i = 1; i < weights.length; i++) {{
+                if (weights[i] > peakWeight) {{
+                    peakWeight = weights[i];
+                    peakIdx = i;
+                }}
+            }}
+            // Find significant frames
+            const threshold = peakWeight * (peakThreshold / 100);
+            let startIdx = peakIdx;
+            let endIdx = peakIdx;
+            let sumWeight = 0;
+            let count = 0;
+            for (let i = 0; i < weights.length; i++) {{
+                if (weights[i] >= threshold) {{
+                    if (i < startIdx) startIdx = i;
+                    if (i > endIdx) endIdx = i;
+                    sumWeight += weights[i];
+                    count++;
+                }}
+            }}
+            const avgWeight = count > 0 ? sumWeight / count : peakWeight;
+            return {{
+                startIdx: startIdx,
+                endIdx: endIdx,
+                peakIdx: peakIdx,
+                peakWeight: peakWeight,
+                avgWeight: avgWeight,
+                threshold: threshold
+            }};
+        }}
+        function getConfidenceLevel(avgWeight, highThreshold, mediumThreshold) {{
+            if (avgWeight > highThreshold) return 'high';
+            if (avgWeight > mediumThreshold) return 'medium';
+            return 'low';
+        }}
+        function drawAlignmentChart() {{
+            const peakThreshold = parseInt(peakThresholdSlider.value);
+            const highThreshold = parseInt(confidenceHighSlider.value) / 100;
+            const mediumThreshold = parseInt(confidenceMediumSlider.value) / 100;
+            // Canvas dimensions
+            const width = alignmentCanvas.width;
+            const height = alignmentCanvas.height;
+            const leftMargin = 180;
+            const rightMargin = 50;
+            const topMargin = 60;
+            const bottomMargin = 80;
+            const plotWidth = width - leftMargin - rightMargin;
+            const plotHeight = height - topMargin - bottomMargin;
+            const rowHeight = plotHeight / numGlosses;
+            const featureWidth = plotWidth / numFeatures;
+            // Clear canvas
+            alignmentCtx.clearRect(0, 0, width, height);
+            // Draw title
+            alignmentCtx.fillStyle = '#333';
+            alignmentCtx.font = 'bold 18px Arial';
+            alignmentCtx.textAlign = 'center';
+            alignmentCtx.fillText('Word-to-Frame Alignment', width / 2, 30);
+            alignmentCtx.font = '13px Arial';
+            alignmentCtx.fillText('(based on attention peaks, ★ = peak frame)', width / 2, 48);
+            // Calculate alignments
+            const alignments = [];
+            for (let wordIdx = 0; wordIdx < numGlosses; wordIdx++) {{
+                const data = attentionData[wordIdx];
+                const alignment = calculateAlignment(data.weights, peakThreshold);
+                alignment.word = data.word;
+                alignment.wordIdx = wordIdx;
+                alignment.weights = data.weights;
+                alignments.push(alignment);
+            }}
+            // Draw grid
+            alignmentCtx.strokeStyle = '#e0e0e0';
+            alignmentCtx.lineWidth = 0.5;
+            for (let i = 0; i <= numFeatures; i++) {{
+                const x = leftMargin + i * featureWidth;
+                alignmentCtx.beginPath();
+                alignmentCtx.moveTo(x, topMargin);
+                alignmentCtx.lineTo(x, topMargin + plotHeight);
+                alignmentCtx.stroke();
+            }}
+            // Draw word regions
+            for (let wordIdx = 0; wordIdx < numGlosses; wordIdx++) {{
+                const alignment = alignments[wordIdx];
+                const confidence = getConfidenceLevel(alignment.avgWeight, highThreshold, mediumThreshold);
+                const y = topMargin + wordIdx * rowHeight;
+                // Alpha based on confidence
+                const alpha = confidence === 'high' ? 0.9 : confidence === 'medium' ? 0.7 : 0.5;
+                // Draw rectangle for word region
+                const startX = leftMargin + alignment.startIdx * featureWidth;
+                const rectWidth = (alignment.endIdx - alignment.startIdx + 1) * featureWidth;
+                alignmentCtx.fillStyle = colors[wordIdx % 20];
+                alignmentCtx.globalAlpha = alpha;
+                alignmentCtx.fillRect(startX, y, rectWidth, rowHeight * 0.8);
+                alignmentCtx.globalAlpha = 1.0;
+                // Draw border
+                alignmentCtx.strokeStyle = '#000';
+                alignmentCtx.lineWidth = 2;
+                alignmentCtx.strokeRect(startX, y, rectWidth, rowHeight * 0.8);
+                // Draw attention waveform inside rectangle
+                alignmentCtx.strokeStyle = 'rgba(0, 0, 255, 0.8)';
+                alignmentCtx.lineWidth = 1.5;
+                alignmentCtx.beginPath();
+                for (let i = alignment.startIdx; i <= alignment.endIdx; i++) {{
+                    const x = leftMargin + i * featureWidth + featureWidth / 2;
+                    const weight = alignment.weights[i];
+                    const maxWeight = alignment.peakWeight;
+                    const normalizedWeight = weight / (maxWeight * 1.2); // Scale for visibility
+                    const waveY = y + rowHeight * 0.8 - (normalizedWeight * rowHeight * 0.6);
+                    if (i === alignment.startIdx) {{
+                        alignmentCtx.moveTo(x, waveY);
+                    }} else {{
+                        alignmentCtx.lineTo(x, waveY);
+                    }}
+                }}
+                alignmentCtx.stroke();
+                // Draw word label
+                const labelX = startX + rectWidth / 2;
+                const labelY = y + rowHeight * 0.4;
+                alignmentCtx.fillStyle = 'rgba(0, 0, 0, 0.7)';
+                alignmentCtx.fillRect(labelX - 60, labelY - 12, 120, 24);
+                alignmentCtx.fillStyle = '#fff';
+                alignmentCtx.font = 'bold 13px Arial';
+                alignmentCtx.textAlign = 'center';
+                alignmentCtx.textBaseline = 'middle';
+                alignmentCtx.fillText(alignment.word, labelX, labelY);
+                // Mark peak frame with star
+                const peakX = leftMargin + alignment.peakIdx * featureWidth + featureWidth / 2;
+                const peakY = y + rowHeight * 0.4;
+                // Draw star
+                alignmentCtx.fillStyle = '#ff0000';
+                alignmentCtx.strokeStyle = '#ffff00';
+                alignmentCtx.lineWidth = 1.5;
+                alignmentCtx.font = '20px Arial';
+                alignmentCtx.textAlign = 'center';
+                alignmentCtx.strokeText('★', peakX, peakY);
+                alignmentCtx.fillText('★', peakX, peakY);
+                // Y-axis label (word names)
+                alignmentCtx.fillStyle = '#333';
+                alignmentCtx.font = '12px Arial';
+                alignmentCtx.textAlign = 'right';
+                alignmentCtx.textBaseline = 'middle';
+                alignmentCtx.fillText(alignment.word, leftMargin - 10, y + rowHeight * 0.4);
+            }}
+            // Draw horizontal grid lines
+            alignmentCtx.strokeStyle = '#ccc';
+            alignmentCtx.lineWidth = 0.5;
+            for (let i = 0; i <= numGlosses; i++) {{
+                const y = topMargin + i * rowHeight;
+                alignmentCtx.beginPath();
+                alignmentCtx.moveTo(leftMargin, y);
+                alignmentCtx.lineTo(leftMargin + plotWidth, y);
+                alignmentCtx.stroke();
+            }}
+            // Draw axes
+            alignmentCtx.strokeStyle = '#000';
+            alignmentCtx.lineWidth = 2;
+            alignmentCtx.strokeRect(leftMargin, topMargin, plotWidth, plotHeight);
+            // X-axis labels (frame indices)
+            alignmentCtx.fillStyle = '#000';
+            alignmentCtx.font = '11px Arial';
+            alignmentCtx.textAlign = 'center';
+            alignmentCtx.textBaseline = 'top';
+            for (let i = 0; i < numFeatures; i++) {{
+                const x = leftMargin + i * featureWidth + featureWidth / 2;
+                alignmentCtx.fillText(i.toString(), x, topMargin + plotHeight + 10);
+            }}
+            // Axis titles
+            alignmentCtx.fillStyle = '#333';
+            alignmentCtx.font = 'bold 14px Arial';
+            alignmentCtx.textAlign = 'center';
+            alignmentCtx.fillText('Feature Frame Index', leftMargin + plotWidth / 2, height - 20);
+            alignmentCtx.save();
+            alignmentCtx.translate(30, topMargin + plotHeight / 2);
+            alignmentCtx.rotate(-Math.PI / 2);
+            alignmentCtx.fillText('Generated Word', 0, 0);
+            alignmentCtx.restore();
+            return alignments;
+        }}
+        function drawTimeline(alignments) {{
+            const highThreshold = parseInt(confidenceHighSlider.value) / 100;
+            const mediumThreshold = parseInt(confidenceMediumSlider.value) / 100;
+            const width = timelineCanvas.width;
+            const height = timelineCanvas.height;
+            const leftMargin = 180;
+            const rightMargin = 50;
+            const plotWidth = width - leftMargin - rightMargin;
+            const featureWidth = plotWidth / numFeatures;
+            // Clear canvas
+            timelineCtx.clearRect(0, 0, width, height);
+            // Background bar
+            timelineCtx.fillStyle = '#ddd';
+            timelineCtx.fillRect(leftMargin, 30, plotWidth, 40);
+            timelineCtx.strokeStyle = '#000';
+            timelineCtx.lineWidth = 2;
+            timelineCtx.strokeRect(leftMargin, 30, plotWidth, 40);
+            // Draw word regions on timeline
+            for (let wordIdx = 0; wordIdx < alignments.length; wordIdx++) {{
+                const alignment = alignments[wordIdx];
+                const confidence = getConfidenceLevel(alignment.avgWeight, highThreshold, mediumThreshold);
+                const alpha = confidence === 'high' ? 0.9 : confidence === 'medium' ? 0.7 : 0.5;
+                const startX = leftMargin + alignment.startIdx * featureWidth;
+                const rectWidth = (alignment.endIdx - alignment.startIdx + 1) * featureWidth;
+                timelineCtx.fillStyle = colors[wordIdx % 20];
+                timelineCtx.globalAlpha = alpha;
+                timelineCtx.fillRect(startX, 30, rectWidth, 40);
+                timelineCtx.globalAlpha = 1.0;
+                timelineCtx.strokeStyle = '#000';
+                timelineCtx.lineWidth = 0.5;
+                timelineCtx.strokeRect(startX, 30, rectWidth, 40);
+            }}
+            // Title
+            timelineCtx.fillStyle = '#333';
+            timelineCtx.font = 'bold 13px Arial';
+            timelineCtx.textAlign = 'left';
+            timelineCtx.fillText('Timeline Progress Bar', leftMargin, 20);
+        }}
+        function updateDetailsPanel(alignments, highThreshold, mediumThreshold) {{
+            const panel = document.getElementById('alignment-details');
+            let html = '<table style="width: 100%; border-collapse: collapse;">';
+            html += '<tr style="background: #f0f0f0; font-weight: bold;">';
+            html += '<th style="padding: 8px; border: 1px solid #ddd;">Word</th>';
+            html += '<th style="padding: 8px; border: 1px solid #ddd;">Feature Range</th>';
+            html += '<th style="padding: 8px; border: 1px solid #ddd;">Peak</th>';
+            html += '<th style="padding: 8px; border: 1px solid #ddd;">Span</th>';
+            html += '<th style="padding: 8px; border: 1px solid #ddd;">Avg Attention</th>';
+            html += '<th style="padding: 8px; border: 1px solid #ddd;">Confidence</th>';
+            html += '</tr>';
+            for (const align of alignments) {{
+                const confidence = getConfidenceLevel(align.avgWeight, highThreshold, mediumThreshold);
+                const span = align.endIdx - align.startIdx + 1;
+                html += '<tr>';
+                html += `<td style="padding: 8px; border: 1px solid #ddd;"><strong>${{align.word}}</strong></td>`;
+                html += `<td style="padding: 8px; border: 1px solid #ddd;">${{align.startIdx}} → ${{align.endIdx}}</td>`;
+                html += `<td style="padding: 8px; border: 1px solid #ddd;">${{align.peakIdx}}</td>`;
+                html += `<td style="padding: 8px; border: 1px solid #ddd;">${{span}}</td>`;
+                html += `<td style="padding: 8px; border: 1px solid #ddd;">${{align.avgWeight.toFixed(4)}}</td>`;
+                html += `<td style="padding: 8px; border: 1px solid #ddd;"><span class="confidence ${{confidence}}">${{confidence}}</span></td>`;
+                html += '</tr>';
+            }}
+            html += '</table>';
+            panel.innerHTML = html;
+        }}
+        function updateVisualization() {{
+            const alignments = drawAlignmentChart();
+            drawTimeline(alignments);
+            const highThreshold = parseInt(confidenceHighSlider.value) / 100;
+            const mediumThreshold = parseInt(confidenceMediumSlider.value) / 100;
+            updateDetailsPanel(alignments, highThreshold, mediumThreshold);
+        }}
+        // Event listeners for sliders
+        peakSlider.addEventListener('input', function() {{
+            peakValue.textContent = peakSlider.value + '%';
+            updateVisualization();
+        }});
+        confidenceHighSlider.addEventListener('input', function() {{
+            const val = parseInt(confidenceHighSlider.value) / 100;
+            confidenceHighValue.textContent = val.toFixed(2);
+            updateVisualization();
+        }});
+        confidenceMediumSlider.addEventListener('input', function() {{
+            const val = parseInt(confidenceMediumSlider.value) / 100;
+            confidenceMediumValue.textContent = val.toFixed(2);
+            updateVisualization();
+        }});
+        // Initial visualization
+        updateVisualization();
+    </script>
+</body>
+</html>
+"""
+    # 5. 保存HTML文件
+    with open(output_path, 'w', encoding='utf-8') as f:
+        f.write(html_content)
+    print(f"✓ 已生成交互式HTML: {output_path}")
+    print(f"  在浏览器中打开此文件，使用滑块调整阈值")
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("使用方法: python generate_interactive_alignment.py <sample_dir>")
+        print("例如: python generate_interactive_alignment.py detailed_prediction_20251226_022246/sample_000")
+        sys.exit(1)
+    sample_dir = Path(sys.argv[1])
+    if not sample_dir.exists():
+        print(f"错误: 目录不存在: {sample_dir}")
+        sys.exit(1)
+    output_path = sample_dir / "interactive_alignment.html"
+    generate_interactive_html(sample_dir, output_path)
+    print(f"\n使用方法:")
+    print(f"  在浏览器中打开: {output_path.absolute()}")
+    print(f"  调整滑块实时查看不同阈值下的对齐效果")

SignX/inference.sh CHANGED Viewed

@@ -251,7 +251,26 @@ if [ -f "$TEMP_DIR/prediction.txt" ]; then
             echo ""
             echo -e "${BLUE}生成 Gloss-to-Frames 可视化...${NC}"
             if [ -f "$SCRIPT_DIR/eval/generate_gloss_frames.py" ]; then
-                python "$SCRIPT_DIR/eval/generate_gloss_frames.py" "$dest_path" "$VIDEO_PATH" 2>&1 | grep -E "(处理|提取|生成|完成|✓)"
             else
                 echo "  ⓘ generate_gloss_frames.py 未找到，跳过后处理"
             fi

             echo ""
             echo -e "${BLUE}生成 Gloss-to-Frames 可视化...${NC}"
             if [ -f "$SCRIPT_DIR/eval/generate_gloss_frames.py" ]; then
+                # 切换回 signx-slt 环境 (有 matplotlib 和 cv2)
+                conda activate signx-slt
+                python "$SCRIPT_DIR/eval/generate_gloss_frames.py" "$dest_path" "$VIDEO_PATH"
+                # 生成交互式HTML可视化
+                echo ""
+                echo -e "${BLUE}生成交互式HTML可视化...${NC}"
+                if [ -f "$SCRIPT_DIR/eval/generate_interactive_alignment.py" ]; then
+                    # 处理所有样本
+                    for sample_dir in "$dest_path"/sample_*; do
+                        if [ -d "$sample_dir" ]; then
+                            python "$SCRIPT_DIR/eval/generate_interactive_alignment.py" "$sample_dir"
+                        fi
+                    done
+                else
+                    echo "  ⓘ generate_interactive_alignment.py 未找到，跳过交互式HTML生成"
+                fi
+                # 切换回 slt_tf1 环境
+                conda activate slt_tf1
             else
                 echo "  ⓘ generate_gloss_frames.py 未找到，跳过后处理"
             fi