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feat:maintainance for better startup speed #21

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5 changes: 4 additions & 1 deletion .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -151,4 +151,7 @@ data/
.serena
onnx_model_tha4/fp16
onnx_model_tha4/fp32
onnx_model_tha4/
onnx_model_tha4/

# Tensorrt temporary files
*.pch
2 changes: 1 addition & 1 deletion 01A.启动器.bat
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@@ -1,7 +1,7 @@
@echo on
cd /D "%~dp0"

SET PATH=%~dp0envs\TensorRT-RTX-1.3.0.35_cu129\bin;%~dp0envs\python_embedded;%~dp0envs\python_embedded\Scripts;%~dp0envs\python_embedded\Library\bin;%PATH%
SET PATH=%~dp0envs\TensorRT-RTX\bin;%~dp0envs\python_embedded;%~dp0envs\python_embedded\Scripts;%~dp0envs\python_embedded\Library\bin;%PATH%

start "" pythonw launcher2.py
exit
2 changes: 1 addition & 1 deletion 01B.启动器（调试输出）.bat
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@@ -1,7 +1,7 @@
@echo on
cd /D "%~dp0"

SET PATH=%~dp0envs\TensorRT-RTX-1.3.0.35_cu129\bin;%~dp0envs\python_embedded;%~dp0envs\python_embedded\Scripts;%~dp0envs\python_embedded\Library\bin;%PATH%
SET PATH=%~dp0envs\TensorRT-RTX\bin;%~dp0envs\python_embedded;%~dp0envs\python_embedded\Scripts;%~dp0envs\python_embedded\Library\bin;%PATH%

python launcher2.py

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19 changes: 8 additions & 11 deletions README.md
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Expand Up @@ -165,14 +165,6 @@ conda 24.11.3
```
以上方式可以保证conda环境被你选定的Ananconda统一管理。若没有此需求可以忽略直接运行下一步。

### 下载 TensorRT-RTX （Nvidia开发必选）
```
curl -L -o trt_rtx.zip https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.3/TensorRT-RTX-1.3.0.35-win10-amd64-cuda-12.9-Release-external.zip
tar -xf trt_rtx.zip "TensorRT-RTX-1.3.0.35" && ren "TensorRT-RTX-1.3.0.35" "TensorRT-RTX-1.3.0.35_cu129" && del trt_rtx.zip
# Adding the bin folder to PATH
cd TensorRT-RTX-1.3.0.35_cu129\bin && set PATH=%CD%;%PATH%
```
也可以在Window 环境变量管理器 GUI中将`TensorRT-RTX-1.3.0.35_cu129\bin`在`PATH`环境变量中添加来持久化

### 准备Conda 环境
```
Expand All @@ -182,10 +174,15 @@ conda install conda-forge::pycuda
conda install -c nvidia/label/cuda-12.9.1 cuda-nvcc-dev_win-64 cudnn cuda-runtime
```

### 安装 TensorRT-RTX 的 Python Binding
```
pip install TensorRT-RTX-1.3.0.35_cu129\python\tensorrt_rtx-1.3.0.35-cp310-none-win_amd64.whl
### 下载 TensorRT-RTX （Nvidia开发必选）
1. Go to https://developer.nvidia.com/tensorrt-rtx download for windows cuda129
2. Unzip downloaded folder
3. Add bin folder to environment PATH
4. Activate your python environment and install like below:
```bash
pip install D:\TensorRT-RTX-1.4.0.76_cu129\python\tensorrt_rtx-1.4.0.76-cp310-none-win_amd64.whl
```
也可以在Window 环境变量管理器 GUI中将`TensorRT-RTX-1.4.0.76_cu129\bin`在`PATH`环境变量中添加来持久化

### 克隆项目和子项目
```
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2 changes: 1 addition & 1 deletion ezvtuber-rt
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Submodule ezvtuber-rt updated 6 files
+5 −5 INSTALL.md
+3 −29 ezvtb_rt/core_ort.py
+8 −33 ezvtb_rt/core_trt.py
+28 −0 ezvtb_rt/frame_mark.py
+28 −10 ezvtb_rt/trt_engine.py
+21 −5 ezvtb_rt/trt_utils.py
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