单目3D初始代码

tools/scripts_for_gt/visualization/test_visualization.py

@@ -0,0 +1,187 @@
+"""
+快速测试脚本 - 自动查找并可视化第一个有效样本
+
+用途：自动从验证集中查找一个带标签的样本并进行可视化，用于测试脚本功能
+
+使用方法：
+    python scripts_for_gt/test_visualization.py --data data/mono3d.yaml
+"""
+
+import argparse
+import sys
+from pathlib import Path
+import yaml
+
+# Add project root to path
+FILE = Path(__file__).resolve()
+ROOT = FILE.parents[1]
+if str(ROOT) not in sys.path:
+    sys.path.append(str(ROOT))
+
+from visualize_single_frame import visualize_single_frame
+
+
+def find_first_valid_sample(data_yaml_path):
+    """从数据集配置中查找第一个有效样本
+    
+    Args:
+        data_yaml_path: 数据集YAML配置文件路径
+        
+    Returns:
+        tuple: (image_path, label_path, calib_path) 或 None
+    """
+    # 读取数据集配置
+    with open(data_yaml_path, 'r') as f:
+        data = yaml.safe_load(f)
+    
+    # 获取验证集路径
+    val_path = data.get('val')
+    if val_path is None:
+        print("错误：数据集配置中未找到'val'字段")
+        return None
+    
+    # 如果是相对路径，相对于yaml文件的位置
+    val_path = Path(val_path)
+    if not val_path.is_absolute():
+        val_path = Path(data_yaml_path).parent / val_path
+    
+    # 读取验证集图像列表
+    if val_path.is_file():
+        # 如果是文件列表
+        with open(val_path, 'r') as f:
+            image_files = [line.strip() for line in f.readlines() if line.strip()]
+    else:
+        # 如果是目录
+        image_files = list(val_path.glob("**/*.jpg"))
+        image_files.extend(list(val_path.glob("**/*.png")))
+    
+    print(f"在验证集中找到 {len(image_files)} 个图像文件")
+    
+    # 遍历查找第一个有标签的样本
+    for image_path in image_files:
+        image_rel_path = Path(image_path)
+        
+        image_path = val_path.parent / image_rel_path if not image_rel_path.is_absolute() else image_rel_path
+        # 推断标签路径
+        label_path = Path(str(image_path).replace('/images/', '/labels/').replace('.jpg', '.txt').replace('.png', '.txt'))
+        
+        # 推断标定路径
+        calib_path = image_path.parent.parent / 'calib' / 'L2_calib' / 'camera4.json'
+        
+        if label_path.exists():
+            print(f"\n找到有效样本:")
+            print(f"  图像: {image_path}")
+            print(f"  标签: {label_path}")
+            print(f"  标定: {calib_path if calib_path.exists() else '未找到'}")
+            return str(image_path), str(label_path), str(calib_path) if calib_path.exists() else None
+    
+    print("错误：未找到有效样本")
+    return None
+
+
+def test_visualization(data_yaml_path, output_dir="./test_gt_viz", use_roi=True):
+    """测试可视化功能
+    
+    Args:
+        data_yaml_path: 数据集YAML配置文件路径
+        output_dir: 输出目录
+        use_roi: 是否使用ROI变换
+    """
+    # 读取数据集配置
+    with open(data_yaml_path, 'r') as f:
+        data = yaml.safe_load(f)
+    
+    # 查找第一个有效样本
+    result = find_first_valid_sample(data_yaml_path)
+    if result is None:
+        return
+    
+    image_path, label_path, calib_path = result
+    
+    # 获取配置参数
+    roi = data.get('roi')  # [width, height]
+    virtual_fx = data.get('virtual_fx')
+    ori_img_size = data.get('ori_img_size')  # [width, height]
+    
+    print(f"\n数据集配置:")
+    print(f"  ROI: {roi}")
+    print(f"  虚拟焦距: {virtual_fx}")
+    print(f"  原始图像尺寸: {ori_img_size}")
+    
+    # 类别名称
+    names = {
+        0: "vehicle",
+        1: "pedestrian",
+        2: "bicycle",
+        3: "rider",
+        13: "tricycle",
+    }
+    
+    print(f"\n开始可视化...")
+    
+    try:
+        # 测试1：不使用ROI
+        print("\n=== 测试1：原始图像可视化（不使用ROI）===")
+        visualize_single_frame(
+            image_path=image_path,
+            label_path=label_path,
+            output_dir=f"{output_dir}/no_roi",
+            calib_path=calib_path,
+            roi_size=None,
+            virtual_fx=None,
+            ori_img_size=None,
+            names=names,
+        )
+        print("✓ 测试1完成")
+        
+        # 测试2：使用ROI（如果配置了）
+        if use_roi and roi is not None and virtual_fx is not None:
+            print("\n=== 测试2：ROI变换后可视化 ===")
+            visualize_single_frame(
+                image_path=image_path,
+                label_path=label_path,
+                output_dir=f"{output_dir}/with_roi",
+                calib_path=calib_path,
+                roi_size=tuple(roi),
+                virtual_fx=virtual_fx,
+                ori_img_size=tuple(ori_img_size) if ori_img_size else None,
+                names=names,
+            )
+            print("✓ 测试2完成")
+        
+        print(f"\n✅ 所有测试完成！结果保存在: {output_dir}")
+        print("\n生成的文件:")
+        output_path = Path(output_dir)
+        for file in sorted(output_path.rglob("*.jpg")):
+            print(f"  {file.relative_to(output_path)}")
+        
+    except Exception as e:
+        print(f"\n❌ 测试失败: {e}")
+        import traceback
+        traceback.print_exc()
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description="快速测试真值可视化功能")
+    parser.add_argument("--data", type=str, default="data/mono3d.yaml",
+                       help="数据集YAML配置文件")
+    parser.add_argument("--output", type=str, default="./test_gt_viz",
+                       help="输出目录")
+    parser.add_argument("--no-roi", action="store_true",
+                       help="不测试ROI变换")
+    
+    return parser.parse_args()
+
+
+def main():
+    args = parse_args()
+    
+    test_visualization(
+        data_yaml_path=args.data,
+        output_dir=args.output,
+        use_roi=not args.no_roi,
+    )
+
+
+if __name__ == "__main__":
+    main()