262 lines
8.3 KiB
Python
Executable File
262 lines
8.3 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Phase 4B RMT-PPAD 评估结果可视化脚本
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解析评估结果文件并生成可视化输出
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"""
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import argparse
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import pickle
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import os
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import numpy as np
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import matplotlib.pyplot as plt
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import seaborn as sns
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from pathlib import Path
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def parse_results(results_file):
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"""解析MMDetection3D评估结果文件"""
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print(f"📂 读取结果文件: {results_file}")
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if not os.path.exists(results_file):
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print(f"❌ 文件不存在: {results_file}")
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return None
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with open(results_file, 'rb') as f:
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results = pickle.load(f)
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return results
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def visualize_bbox_metrics(results, save_path="bbox_metrics.png"):
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"""可视化3D检测指标"""
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print("📊 可视化3D检测指标...")
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if 'bbox' not in results:
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print("⚠️ 没有找到bbox指标")
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return
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bbox_results = results['bbox']
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# 解析不同类别的指标
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classes = []
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aps = []
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ap_50s = []
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ap_75s = []
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for class_name, metrics in bbox_results.items():
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if class_name.startswith('car') or class_name.startswith('truck') or \
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class_name.startswith('bus') or class_name.startswith('pedestrian'):
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classes.append(class_name.split('_')[0]) # 去掉AP后缀
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aps.append(metrics.get('ap', 0))
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ap_50s.append(metrics.get('ap_0.5', 0))
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ap_75s.append(metrics.get('ap_0.75', 0))
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if not classes:
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print("⚠️ 没有找到有效的类别指标")
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return
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# 创建图表
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fig, axes = plt.subplots(1, 3, figsize=(15, 5))
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x = np.arange(len(classes))
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width = 0.25
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# AP@0.5:0.95
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axes[0].bar(x - width, aps, width, label='AP@0.5:0.95', color='skyblue')
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axes[0].set_title('Average Precision (AP@0.5:0.95)')
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axes[0].set_xticks(x)
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axes[0].set_xticklabels(classes, rotation=45)
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axes[0].set_ylabel('AP')
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axes[0].grid(True, alpha=0.3)
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# AP@0.5
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axes[1].bar(x, ap_50s, width, label='AP@0.5', color='lightgreen')
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axes[1].set_title('Average Precision (AP@0.5)')
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axes[1].set_xticks(x)
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axes[1].set_xticklabels(classes, rotation=45)
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axes[1].set_ylabel('AP')
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axes[1].grid(True, alpha=0.3)
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# AP@0.75
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axes[2].bar(x + width, ap_75s, width, label='AP@0.75', color='salmon')
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axes[2].set_title('Average Precision (AP@0.75)')
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axes[2].set_xticks(x)
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axes[2].set_xticklabels(classes, rotation=45)
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axes[2].set_ylabel('AP')
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axes[2].grid(True, alpha=0.3)
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plt.tight_layout()
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plt.savefig(save_path, dpi=300, bbox_inches='tight')
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plt.close()
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print(f"✅ 3D检测指标图表已保存: {save_path}")
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def visualize_map_metrics(results, save_path="map_metrics.png"):
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"""可视化BEV分割指标"""
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print("🗺️ 可视化BEV分割指标...")
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if 'map' not in results:
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print("⚠️ 没有找到map指标")
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return
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map_results = results['map']
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# 解析分割类别
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classes = []
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ious = []
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dices = []
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for class_name, metrics in map_results.items():
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if 'IoU' in metrics and 'Dice' in metrics:
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# 去掉类别名称中的数字后缀
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clean_name = class_name.replace('_0', '').replace('_1', '').replace('_2', '') \
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.replace('_3', '').replace('_4', '').replace('_5', '')
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if clean_name not in classes:
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classes.append(clean_name)
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ious.append(metrics['IoU'])
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dices.append(metrics['Dice'])
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if not classes:
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print("⚠️ 没有找到有效的分割指标")
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return
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# 创建图表
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fig, ax = plt.subplots(figsize=(10, 6))
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x = np.arange(len(classes))
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width = 0.35
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bars1 = ax.bar(x - width/2, ious, width, label='IoU', color='lightblue', alpha=0.8)
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bars2 = ax.bar(x + width/2, dices, width, label='Dice', color='lightcoral', alpha=0.8)
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ax.set_xlabel('类别')
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ax.set_ylabel('分数')
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ax.set_title('BEV分割性能指标')
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ax.set_xticks(x)
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ax.set_xticklabels(classes, rotation=45, ha='right')
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ax.legend()
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ax.grid(True, alpha=0.3)
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# 添加数值标签
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for bar, value in zip(bars1, ious):
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height = bar.get_height()
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ax.text(bar.get_x() + bar.get_width()/2., height + 0.01,
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f'{value:.3f}', ha='center', va='bottom', fontsize=8)
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for bar, value in zip(bars2, dices):
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height = bar.get_height()
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ax.text(bar.get_x() + bar.get_width()/2., height + 0.01,
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f'{value:.3f}', ha='center', va='bottom', fontsize=8)
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plt.tight_layout()
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plt.savefig(save_path, dpi=300, bbox_inches='tight')
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plt.close()
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print(f"✅ BEV分割指标图表已保存: {save_path}")
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def print_summary(results, log_file=None):
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"""打印评估结果摘要"""
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print("\n" + "="*60)
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print("📈 Phase 4B RMT-PPAD 评估结果摘要")
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print("="*60)
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# 3D检测指标
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if 'bbox' in results:
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print("\n🚗 3D检测性能:")
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bbox_results = results['bbox']
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# 计算NDS (如果有的话)
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if 'NDS' in bbox_results:
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print(".4f")
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# 各类别AP
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for class_name, metrics in bbox_results.items():
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if isinstance(metrics, dict) and 'ap' in metrics:
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print(f" {class_name}: AP@0.5:0.95 = {metrics.get('ap', 0):.4f}, "
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f"AP@0.5 = {metrics.get('ap_0.5', 0):.4f}")
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# BEV分割指标
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if 'map' in results:
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print("\n🗺️ BEV分割性能:")
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map_results = results['map']
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total_iou = 0
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total_dice = 0
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count = 0
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for class_name, metrics in map_results.items():
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if isinstance(metrics, dict) and 'IoU' in metrics:
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iou = metrics['IoU']
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dice = metrics.get('Dice', 0)
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print(f" {class_name}: IoU = {iou:.4f}, Dice = {dice:.4f}")
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total_iou += iou
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total_dice += dice
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count += 1
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if count > 0:
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print(f" 平均IoU: {total_iou/count:.4f}, 平均Dice: {total_dice/count:.4f}")
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print("\n" + "="*60)
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# 保存到日志文件
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if log_file:
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with open(log_file, 'w') as f:
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f.write("Phase 4B RMT-PPAD 评估结果摘要\n\n")
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f.write("生成时间: " + str(np.datetime64('now')) + "\n\n")
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if 'bbox' in results:
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f.write("3D检测性能:\n")
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for class_name, metrics in results['bbox'].items():
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if isinstance(metrics, dict) and 'ap' in metrics:
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f.write(f" {class_name}: AP@0.5:0.95 = {metrics.get('ap', 0):.4f}\n")
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if 'map' in results:
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f.write("\nBEV分割性能:\n")
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for class_name, metrics in results['map'].items():
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if isinstance(metrics, dict) and 'IoU' in metrics:
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f.write(f" {class_name}: IoU = {metrics['IoU']:.4f}\n")
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print(f"📝 详细结果已保存到: {log_file}")
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def create_visualization_script(results_file, output_dir="visualization"):
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"""创建可视化脚本的主函数"""
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os.makedirs(output_dir, exist_ok=True)
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# 解析结果
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results = parse_results(results_file)
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if results is None:
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return
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# 生成可视化
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bbox_plot = os.path.join(output_dir, "bbox_metrics.png")
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map_plot = os.path.join(output_dir, "map_metrics.png")
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summary_file = os.path.join(output_dir, "evaluation_summary.txt")
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visualize_bbox_metrics(results, bbox_plot)
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visualize_map_metrics(results, map_plot)
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print_summary(results, summary_file)
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print(f"\n🎉 可视化完成！输出目录: {output_dir}")
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print(f" 📊 3D检测图表: {bbox_plot}")
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print(f" 🗺️ 分割图表: {map_plot}")
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print(f" 📝 结果摘要: {summary_file}")
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def main():
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parser = argparse.ArgumentParser(description="Phase 4B RMT-PPAD 评估结果可视化工具")
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parser.add_argument("results_file", help="评估结果文件路径 (.pkl)")
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parser.add_argument("--out-dir", default="visualization",
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help="输出目录 (默认: visualization)")
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args = parser.parse_args()
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print("🚀 Phase 4B RMT-PPAD 评估结果可视化工具")
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print(f"📁 结果文件: {args.results_file}")
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print(f"📂 输出目录: {args.out_dir}")
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print()
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create_visualization_script(args.results_file, args.out_dir)
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if __name__ == "__main__":
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main()
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