Update

2025-02-18 01:01:41 +08:00 · 2025-02-18 01:01:41 +08:00 · b805846fb7
commit b805846fb7
parent f385eda244
4 changed files with 51 additions and 43 deletions
--- a/download_resource.bat
+++ b/download_resource.bat
@ -32,6 +32,11 @@ REM 安装gdown
 python -m pip install --upgrade pip
 python -m pip install gdown

+REM 添加目录存在性检查
+if not exist "%PROJECT_DIR%\ext" mkdir "%PROJECT_DIR%\ext"
+if not exist "%PROJECT_DIR%\cache" mkdir "%PROJECT_DIR%\cache"
+if not exist "%PROJECT_DIR%\resource" mkdir "%PROJECT_DIR%\resource"
+
 REM 下载 NeuralHaircut 模型文件
 cd "%PROJECT_DIR%\resource\NeuralHaircut"
 python -m gdown --folder https://drive.google.com/drive/folders/1TCdJ0CKR3Q6LviovndOkJaKm8S1T9F_8
--- a/install.bat
+++ b/install.bat
@ -1,18 +1,18 @@
@echo off

-REM 设置环境变量
-SET CUDA_HOME="C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8"
-SET PATH="%CUDA_HOME%\bin;%PATH%"
-SET BLENDER_DIR="C:\Program Files\Blender Foundation\Blender 3.6"
-SET VS_DIR="C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools"
-SET VS_VCVARS="%VS_DIR%\VC\Auxiliary\Build\vcvars64.bat"
-SET PROJECT_DIR=%~dp0
-SET MICROMAMBA_EXE=%~dp0micromamba.exe
-SET MAMBA_ROOT_PREFIX=%PROJECT_DIR%\micromamba
-SET PYTHONDONTWRITEBYTECODE=1
-SET GDOWN_CACHE=cache\gdown
-SET TORCH_HOME=cache\torch
-SET HF_HOME=cache\huggingface
+REM 统一环境变量设置格式
+set "PROJECT_DIR=%~dp0"
+set "CUDA_HOME=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8"
+set "PATH=%CUDA_HOME%\bin;%PATH%"
+set "BLENDER_DIR=C:\Program Files\Blender Foundation\Blender 3.6"
+set "VS_DIR=C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools"
+set "VS_VCVARS=%VS_DIR%\VC\Auxiliary\Build\vcvars64.bat"
+set "MICROMAMBA_EXE=%PROJECT_DIR%micromamba.exe"
+set "MAMBA_ROOT_PREFIX=%PROJECT_DIR%micromamba"
+set "PYTHONDONTWRITEBYTECODE=1"
+set "GDOWN_CACHE=%PROJECT_DIR%\cache\gdown"
+set "TORCH_HOME=%PROJECT_DIR%\cache\torch"
+set "HF_HOME=%PROJECT_DIR%\cache\huggingface"

 REM 拉取所有外部库
 mkdir ext
@ -52,14 +52,11 @@ REM 创建 OpenPose 环境
 %MICROMAMBA_EXE% create -y -p %MAMBA_ROOT_PREFIX%\envs\openpose python=3.9
 CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\openpose
 pip install -r requirements_openpose.txt
-CALL %MICROMAMBA_EXE% deactivate
-
 REM 从resource文件夹拷贝Neural Haircut文件
 xcopy /E /I /Y %PROJECT_DIR%\resource\NeuralHaircut %PROJECT_DIR%\ext\NeuralHaircut
 xcopy /E /I /Y %PROJECT_DIR%\resource\hyperIQA\pretrained %PROJECT_DIR%\ext\hyperIQA\pretrained
 cd %PROJECT_DIR%
-
-REM 退出环境
+REM 退出 OpenPose 环境
 CALL %MICROMAMBA_EXE% deactivate

 REM Matte-Anything
@ -113,7 +110,6 @@ CALL %MICROMAMBA_EXE% deactivate
 REM PIXIE
 cd %PROJECT_DIR%\ext && git clone https://github.com/yfeng95/PIXIE
 cd %PROJECT_DIR%\ext\PIXIE
-
 REM 创建data目录
 mkdir data 2>nul
 cd data
--- a/requirements.txt
+++ b/requirements.txt
@ -37,4 +37,10 @@ resize-right==0.0.2
 -e ./ext/NeuralHaircut/npbgpp
 -e ./ext/simple-knn
 -e ./ext/diff_gaussian_rasterization_hair
-e ./ext/kaolin 
+-e ./ext/kaolin 
+
+# Development tools
+pytest
+black
+flake8
+ipython 
--- a/run.bat
+++ b/run.bat
@ -11,6 +11,7 @@ SET EXP_NAME_2=stage2
 SET EXP_NAME_3=stage3
 SET BLENDER_DIR="C:\Program Files\Blender Foundation\Blender 3.6"
 SET CUDA_HOME="C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8"
+set "PATH=%CUDA_HOME%\bin;%PATH%"

 REM 确保以下环境变量可用:
 REM PROJECT_DIR 和 DATA_PATH
@ -54,7 +55,7 @@ REM 添加进度显示
 echo [1/3] 预处理阶段开始...

 REM 将原始图像整理成3D Gaussian Splatting格式
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python preprocess_raw_images.py --data_path %DATA_PATH%
@ -64,7 +65,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 运行COLMAP重建并去畸变图像和相机
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 pushd %PROJECT_DIR%\src
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python convert.py -s %DATA_PATH% --camera %CAMERA% --max_size 1024
@ -75,7 +76,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 运行Matte-Anything
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\matte_anything
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\matte_anything
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python calc_masks.py --data_path %DATA_PATH% --image_format png --max_size 2048
@ -85,7 +86,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 使用IQA分数过滤图像
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python filter_extra_images.py --data_path %DATA_PATH% --max_imgs 128
@ -95,7 +96,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 调整图像大小
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python resize_images.py --data_path %DATA_PATH%
@ -105,7 +106,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 计算方向图
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python calc_orientation_maps.py --img_path %DATA_PATH%\images_2 --mask_path %DATA_PATH%\masks_2\hair --orient_dir %DATA_PATH%\orientations_2\angles --conf_dir %DATA_PATH%\orientations_2\vars --filtered_img_dir %DATA_PATH%\orientations_2\filtered_imgs --vis_img_dir %DATA_PATH%\orientations_2\vis_imgs
@ -115,7 +116,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 运行OpenPose
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\openpose
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\openpose
 cd %PROJECT_DIR%\ext\openpose
 mkdir %DATA_PATH%\openpose
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
@ -126,7 +127,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 运行Face-Alignment
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python calc_face_alignment.py --data_path %DATA_PATH% --image_dir "images_4"
@ -136,7 +137,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 运行PIXIE
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\pixie-env
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\pixie-env
 cd %PROJECT_DIR%\ext\PIXIE
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python demos\demo_fit_face.py -i %DATA_PATH%\images_4 -s %DATA_PATH%\pixie --saveParam True --lightTex False --useTex False --rasterizer_type pytorch3d
@ -146,7 +147,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 合并所有PIXIE预测到单个文件
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python merge_smplx_predictions.py --data_path %DATA_PATH%
@ -156,7 +157,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 将COLMAP相机转换为txt
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 mkdir %DATA_PATH%\sparse_txt
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 colmap model_converter --input_path %DATA_PATH%\sparse\0 --output_path %DATA_PATH%\sparse_txt --output_type TXT
@ -166,7 +167,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 将COLMAP相机转换为H3DS格式
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python colmap_parsing.py --path_to_scene %DATA_PATH%
@ -195,7 +196,7 @@ echo [2/3] 重建阶段开始...
 set EXP_PATH_1=%DATA_PATH%\3d_gaussian_splatting\%EXP_NAME_1%

 REM 运行3D Gaussian Splatting重建
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python train_gaussians.py -s %DATA_PATH% -m "%EXP_PATH_1%" -r 1 --port "888%CUDA_VISIBLE_DEVICES%" --trainable_cameras --trainable_intrinsics --use_barf --lambda_dorient 0.1
@ -205,7 +206,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 运行FLAME网格拟合
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\ext\NeuralHaircut\src\multiview_optimization

 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
@ -228,7 +229,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 裁剪重建的场景
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python scale_scene_into_sphere.py --path_to_data %DATA_PATH% -m "%DATA_PATH%\3d_gaussian_splatting\%EXP_NAME_1%" --iter 30000
@ -238,7 +239,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 移除与FLAME头部网格相交的头发高斯体
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python filter_flame_intersections.py --flame_mesh_dir %DATA_PATH%\flame_fitting\%EXP_NAME_1% -m "%DATA_PATH%\3d_gaussian_splatting\%EXP_NAME_1%" --iter 30000 --project_dir %PROJECT_DIR%\ext\NeuralHaircut
@ -248,7 +249,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 为训练视图运行渲染
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python render_gaussians.py -s %DATA_PATH% -m "%DATA_PATH%\3d_gaussian_splatting\%EXP_NAME_1%" --skip_test --scene_suffix "_cropped" --iteration 30000 --trainable_cameras --trainable_intrinsics --use_barf
@ -258,7 +259,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 获取FLAME网格头皮图
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python extract_non_visible_head_scalp.py --project_dir %PROJECT_DIR%\ext\NeuralHaircut --data_dir %DATA_PATH% --flame_mesh_dir %DATA_PATH%\flame_fitting\%EXP_NAME_1% --cams_path %DATA_PATH%\3d_gaussian_splatting\%EXP_NAME_1%\cameras\30000_matrices.pkl -m "%DATA_PATH%\3d_gaussian_splatting\%EXP_NAME_1%"
@ -268,7 +269,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 运行潜在头发股线重建
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python train_latent_strands.py -s %DATA_PATH% -m "%DATA_PATH%\3d_gaussian_splatting\%EXP_NAME_1%" -r 1 --model_path_hair "%DATA_PATH%\strands_reconstruction\%EXP_NAME_2%" --flame_mesh_dir "%DATA_PATH%\flame_fitting\%EXP_NAME_1%" --pointcloud_path_head "%EXP_PATH_1%\point_cloud_filtered\iteration_30000\raw_point_cloud.ply" --hair_conf_path "%PROJECT_DIR%\src\arguments\hair_strands_textured.yaml" --lambda_dmask 0.1 --lambda_dorient 0.1 --lambda_dsds 0.01 --load_synthetic_rgba --load_synthetic_geom --binarize_masks --iteration_data 30000 --trainable_cameras --trainable_intrinsics --use_barf --iterations 20000 --port "800%CUDA_VISIBLE_DEVICES%"
@ -278,7 +279,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 运行头发股线重建
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python train_strands.py -s %DATA_PATH% -m "%DATA_PATH%\3d_gaussian_splatting\%EXP_NAME_1%" -r 1 --model_path_curves "%DATA_PATH%\curves_reconstruction\%EXP_NAME_3%" --flame_mesh_dir "%DATA_PATH%\flame_fitting\%EXP_NAME_1%" --pointcloud_path_head "%EXP_PATH_1%\point_cloud_filtered\iteration_30000\raw_point_cloud.ply" --start_checkpoint_hair "%DATA_PATH%\strands_reconstruction\%EXP_NAME_2%\checkpoints\20000.pth" --hair_conf_path "%PROJECT_DIR%\src\arguments\hair_strands_textured.yaml" --lambda_dmask 0.1 --lambda_dorient 0.1 --lambda_dsds 0.01 --load_synthetic_rgba --load_synthetic_geom --binarize_masks --iteration_data 30000 --position_lr_init 0.0000016 --position_lr_max_steps 10000 --trainable_cameras --trainable_intrinsics --use_barf --iterations 10000 --port "800%CUDA_VISIBLE_DEVICES%"
@ -301,7 +302,7 @@ REM 添加进度显示
 echo [3/3] 可视化阶段开始...

 REM 导出结果的股线为pkl和ply格式
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\preprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python export_curves.py --data_dir %DATA_PATH% --model_name %EXP_NAME_3% --iter 10000 --flame_mesh_path "%DATA_PATH%\flame_fitting\%EXP_NAME_1%\stage_3\mesh_final.obj" --scalp_mesh_path "%DATA_PATH%\flame_fitting\%EXP_NAME_1%\scalp_data\scalp.obj" --hair_conf_path "%PROJECT_DIR%\src\arguments\hair_strands_textured.yaml"
@ -311,7 +312,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 渲染可视化
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\postprocessing
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python render_video.py --blender_path "%BLENDER_DIR%" --input_path "%DATA_PATH%" --exp_name_1 "%EXP_NAME_1%" --exp_name_3 "%EXP_NAME_3%"
@ -321,7 +322,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 渲染股线
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%
 python render_strands.py -s %DATA_PATH% --data_dir "%DATA_PATH%" --data_device 'cpu' --skip_test -m "%DATA_PATH%\3d_gaussian_splatting\%EXP_NAME_1%" --iteration 30000 --flame_mesh_dir "%DATA_PATH%\flame_fitting\%EXP_NAME_1%" --model_hair_path "%DATA_PATH%\curves_reconstruction\%EXP_NAME_3%" --hair_conf_path "%PROJECT_DIR%\src\arguments\hair_strands_textured.yaml" --checkpoint_hair "%DATA_PATH%\strands_reconstruction\%EXP_NAME_2%\checkpoints\20000.pth" --checkpoint_curves "%DATA_PATH%\curves_reconstruction\%EXP_NAME_3%\checkpoints\10000.pth" --pointcloud_path_head "%EXP_PATH_1%\point_cloud\iteration_30000\raw_point_cloud.ply" --interpolate_cameras
@ -331,7 +332,7 @@ IF %ERRORLEVEL% NEQ 0 (
 )

 REM 制作视频
-CALL "%MICROMAMBA_EXE%" activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
+CALL %MICROMAMBA_EXE% activate -p %MAMBA_ROOT_PREFIX%\envs\gaussian_splatting_hair
 cd %PROJECT_DIR%\src\postprocessing
 echo 正在生成最终视频...
 set CUDA_VISIBLE_DEVICES=%CUDA_VISIBLE_DEVICES%