Delete render.py

render.py

@@ -1,124 +0,0 @@
-import os
-import torch
-import json
-import numpy as np
-from tqdm import tqdm
-from argparse import ArgumentParser
-import torchvision
-from pathlib import Path
-
-# 假设你已有这些模块
-from gaussian_renderer import render, GaussianModel
-from scene.cameras import Camera
-from utils.graphics_utils import getWorld2View2, getProjectionMatrix
-
-
-def load_cameras_from_json(json_path):
-    """从cameras.json加载相机参数"""
-    with open(json_path, 'r') as f:
-        camera_data = json.load(f)
-    
-    cameras = []
-    for cam in camera_data:
-        # 根据你的cameras.json格式构建Camera对象
-        # 这里需要根据实际的json结构调整
-        camera = Camera(
-            colmap_id=cam.get('id', 0),
-            R=np.array(cam['rotation']),
-            T=np.array(cam['position']),
-            FoVx=cam['fov_x'],
-            FoVy=cam['fov_y'],
-            image=None,  # 渲染时不需要GT图像
-            gt_alpha_mask=None,
-            image_name=cam.get('img_name', f"frame_{cam['id']:04d}"),
-            uid=cam['id'],
-            data_device='cuda'
-        )
-        cameras.append(camera)
-    
-    return cameras
-
-
-def load_gaussian_model(ply_path, sh_degree=3):
-    """加载训练好的高斯模型"""
-    gaussians = GaussianModel(sh_degree)
-    gaussians.load_ply(ply_path)
-    return gaussians
-
-
-def render_cameras(cameras, gaussians, output_dir, gpu_id=0, bg_color=[0, 0, 0]):
-    """渲染指定相机视角"""
-    # 设置GPU
-    device = f'cuda:{gpu_id}'
-    torch.cuda.set_device(device)
-    
-    # 创建输出目录
-    output_path = Path(output_dir)
-    output_path.mkdir(parents=True, exist_ok=True)
-    
-    # 设置背景颜色
-    background = torch.tensor(bg_color, dtype=torch.float32, device=device)
-    
-    # 渲染每个相机视角
-    rendered_images = []
-    for idx, camera in enumerate(tqdm(cameras, desc="Rendering")):
-        # 渲染
-        with torch.no_grad():
-            rendering = render(camera, gaussians, pipeline=None, background=background)["render"]
-        
-        # 保存图像
-        img_name = f"{camera.image_name}.png" if hasattr(camera, 'image_name') else f"render_{idx:04d}.png"
-        save_path = output_path / img_name
-        torchvision.utils.save_image(rendering, save_path)
-        
-        rendered_images.append(rendering)
-    
-    print(f"渲染完成！图像保存至: {output_path}")
-    return rendered_images
-
-
-def main():
-    parser = ArgumentParser(description="简化版3DGS渲染脚本")
-    
-    # 核心参数
-    parser.add_argument("--cameras_json", type=str, required=True, help="相机参数JSON文件路径")
-    parser.add_argument("--ply_file", type=str, required=True, help="训练好的PLY模型文件路径")
-    parser.add_argument("--output_dir", type=str, required=True, help="渲染结果保存路径")
-    parser.add_argument("--gpu_id", type=int, default=0, help="使用的GPU ID")
-    
-    # 可选参数
-    parser.add_argument("--sh_degree", type=int, default=3, help="球谐函数阶数")
-    parser.add_argument("--white_background", action="store_true", help="使用白色背景")
-    
-    args = parser.parse_args()
-    
-    # 设置背景颜色
-    bg_color = [1, 1, 1] if args.white_background else [0, 0, 0]
-    
-    print(f"加载相机参数: {args.cameras_json}")
-    cameras = load_cameras_from_json(args.cameras_json)
-    
-    print(f"加载高斯模型: {args.ply_file}")
-    gaussians = load_gaussian_model(args.ply_file, args.sh_degree)
-    
-    print(f"开始渲染，使用GPU {args.gpu_id}")
-    render_cameras(
-        cameras=cameras,
-        gaussians=gaussians,
-        output_dir=args.output_dir,
-        gpu_id=args.gpu_id,
-        bg_color=bg_color
-    )
-
-
-if __name__ == "__main__":
-    main()
-
-
-# 使用示例:
-# python render.py \
-#     --cameras_json /path/to/cameras.json \
-#     --ply_file /path/to/model.ply \
-#     --output_dir /path/to/output \
-#     --gpu_id 0 \
-#     --white_background