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Commit dfe72c5d authored by gushiqiao's avatar gushiqiao
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Update gradio

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app/run_gradio_win.bat 0 → 100644
View file @ dfe72c5d
@echo off
chcp 65001 >nul
echo 🎬 LightX2V Gradio Windows Startup Script
echo ==========================================
REM ==================== Configuration Area ====================
REM ⚠️ Important: Please modify the following paths according to your actual environment
REM 🚨 Storage Performance Tips 🚨
REM 💾 Strongly recommend storing model files on SSD solid-state drives!
REM 📈 SSD can significantly improve model loading speed and inference performance
REM 🐌 Using mechanical hard drives (HDD) may cause slow model loading and affect overall experience
REM LightX2V project root directory path
REM Example: D:\LightX2V
set lightx2v_path=/path/to/LightX2V
REM Model path configuration
REM Image-to-video model path (for i2v tasks)
REM Example: D:\models\Wan2.1-I2V-14B-480P-Lightx2v
set i2v_model_path=/path/to/Wan2.1-I2V-14B-480P-Lightx2v
REM Text-to-video model path (for t2v tasks)
REM Example: D:\models\Wan2.1-T2V-1.3B
set t2v_model_path=/path/to/Wan2.1-T2V-1.3B
REM Model size configuration
REM Default model size (14b, 1.3b)
set model_size=14b
REM Model class configuration
REM Default model class (wan2.1, wan2.1_distill)
set model_cls=wan2.1
REM Server configuration
set server_name=127.0.0.1
set server_port=8032
REM GPU configuration
set gpu_id=0
REM ==================== Environment Variables Setup ====================
set CUDA_VISIBLE_DEVICES=%gpu_id%
set PYTHONPATH=%lightx2v_path%;%PYTHONPATH%
set ENABLE_PROFILING_DEBUG=true
set PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
REM ==================== Parameter Parsing ====================
REM Default task type
set task=i2v
REM Default interface language
set lang=zh
REM Parse command line arguments
:parse_args
if "%1"=="" goto :end_parse
if "%1"=="--task" (
set task=%2
shift
shift
goto :parse_args
)
if "%1"=="--lang" (
set lang=%2
shift
shift
goto :parse_args
)
if "%1"=="--port" (
set server_port=%2
shift
shift
goto :parse_args
)
if "%1"=="--gpu" (
set gpu_id=%2
set CUDA_VISIBLE_DEVICES=%gpu_id%
shift
shift
goto :parse_args
)
if "%1"=="--model_size" (
set model_size=%2
shift
shift
goto :parse_args
)
if "%1"=="--model_cls" (
set model_cls=%2
shift
shift
goto :parse_args
)
if "%1"=="--help" (
echo 🎬 LightX2V Gradio Windows Startup Script
echo ==========================================
echo Usage: %0 [options]
echo.
echo 📋 Available options:
echo --task i2v^|t2v Task type (default: i2v)
echo i2v: Image-to-video generation
echo t2v: Text-to-video generation
echo --lang zh^|en Interface language (default: zh)
echo zh: Chinese interface
echo en: English interface
echo --port PORT Server port (default: 8032)
echo --gpu GPU_ID GPU device ID (default: 0)
echo --model_size MODEL_SIZE
echo Model size (default: 14b)
echo 14b: 14B parameter model
echo 1.3b: 1.3B parameter model
echo --model_cls MODEL_CLASS
echo Model class (default: wan2.1)
echo wan2.1: Standard model variant
echo wan2.1_distill: Distilled model variant for faster inference
echo --help Show this help message
echo.
echo 🚀 Usage examples:
echo %0 # Default startup for image-to-video mode
echo %0 --task i2v --lang zh --port 8032 # Start with specified parameters
echo %0 --task t2v --lang en --port 7860 # Text-to-video with English interface
echo %0 --task i2v --gpu 1 --port 8032 # Use GPU 1
echo %0 --task t2v --model_size 1.3b # Use 1.3B model
echo %0 --task i2v --model_size 14b # Use 14B model
echo %0 --task i2v --model_cls wan2.1_distill # Use distilled model
echo.
echo 📝 Notes:
echo - Edit script to configure model paths before first use
echo - Ensure required Python dependencies are installed
echo - Recommended to use GPU with 8GB+ VRAM
echo - 🚨 Strongly recommend storing models on SSD for better performance
pause
exit /b 0
)
echo Unknown parameter: %1
echo Use --help to see help information
pause
exit /b 1
:end_parse
REM ==================== Parameter Validation ====================
if "%task%"=="i2v" goto :valid_task
if "%task%"=="t2v" goto :valid_task
echo Error: Task type must be 'i2v' or 't2v'
pause
exit /b 1
:valid_task
if "%lang%"=="zh" goto :valid_lang
if "%lang%"=="en" goto :valid_lang
echo Error: Language must be 'zh' or 'en'
pause
exit /b 1
:valid_lang
if "%model_size%"=="14b" goto :valid_size
if "%model_size%"=="1.3b" goto :valid_size
echo Error: Model size must be '14b' or '1.3b'
pause
exit /b 1
:valid_size
if "%model_cls%"=="wan2.1" goto :valid_cls
if "%model_cls%"=="wan2.1_distill" goto :valid_cls
echo Error: Model class must be 'wan2.1' or 'wan2.1_distill'
pause
exit /b 1
:valid_cls
REM Select model path based on task type
if "%task%"=="i2v" (
set model_path=%i2v_model_path%
echo 🎬 Starting Image-to-Video mode
) else (
set model_path=%t2v_model_path%
echo 🎬 Starting Text-to-Video mode
)
REM Check if model path exists
if not exist "%model_path%" (
echo ❌ Error: Model path does not exist
echo 📁 Path: %model_path%
echo 🔧 Solutions:
echo 1. Check model path configuration in script
echo 2. Ensure model files are properly downloaded
echo 3. Verify path permissions are correct
echo 4. 💾 Recommend storing models on SSD for faster loading
pause
exit /b 1
)
REM Select demo file based on language
if "%lang%"=="zh" (
set demo_file=gradio_demo_zh.py
echo 🌏 Using Chinese interface
) else (
set demo_file=gradio_demo.py
echo 🌏 Using English interface
)
REM Check if demo file exists
if not exist "%demo_file%" (
echo ❌ Error: Demo file does not exist
echo 📄 File: %demo_file%
echo 🔧 Solutions:
echo 1. Ensure script is run in the correct directory
echo 2. Check if file has been renamed or moved
echo 3. Re-clone or download project files
pause
exit /b 1
)
REM ==================== System Information Display ====================
echo ==========================================
echo 🚀 LightX2V Gradio Starting...
echo ==========================================
echo 📁 Project path: %lightx2v_path%
echo 🤖 Model path: %model_path%
echo 🎯 Task type: %task%
echo 🤖 Model size: %model_size%
echo 🤖 Model class: %model_cls%
echo 🌏 Interface language: %lang%
echo 🖥️ GPU device: %gpu_id%
echo 🌐 Server address: %server_name%:%server_port%
echo ==========================================
REM Display system resource information
echo 💻 System resource information:
wmic OS get TotalVisibleMemorySize,FreePhysicalMemory /format:table
REM Display GPU information
nvidia-smi --query-gpu=name,memory.total,memory.free --format=csv,noheader,nounits 2>nul
if errorlevel 1 (
echo 🎮 GPU information: Unable to get GPU info
) else (
echo 🎮 GPU information:
nvidia-smi --query-gpu=name,memory.total,memory.free --format=csv,noheader,nounits
)
REM ==================== Start Demo ====================
echo 🎬 Starting Gradio demo...
echo 📱 Please access in browser: http://%server_name%:%server_port%
echo ⏹️ Press Ctrl+C to stop service
echo 🔄 First startup may take several minutes to load resources...
echo ==========================================
REM Start Python demo
python %demo_file% ^
--model_path "%model_path%" ^
--model_cls %model_cls% ^
--task %task% ^
--server_name %server_name% ^
--server_port %server_port% ^
--model_size %model_size%
REM Display final system resource usage
echo.
echo ==========================================
echo 📊 Final system resource usage:
wmic OS get TotalVisibleMemorySize,FreePhysicalMemory /format:table
pause
\ No newline at end of file
scripts/win/run_wan_i2v.bat 0 → 100644
View file @ dfe72c5d
@echo off
chcp 65001 >nul
echo 启动LightX2V I2V推理...
:: 设置路径
set lightx2v_path=F:\project\code\lightx2v-main\LightX2V-main\LightX2V-main
set model_path=D:\Wan2.1-I2V-14B-480P-Lightx2v
:: 检查CUDA_VISIBLE_DEVICES
if "%CUDA_VISIBLE_DEVICES%"=="" (
set cuda_devices=0
echo Warn: CUDA_VISIBLE_DEVICES is not set, using default value: %cuda_devices%, change at shell script or set env variable.
set CUDA_VISIBLE_DEVICES=%cuda_devices%
)
:: 检查路径
if "%lightx2v_path%"=="" (
echo Error: lightx2v_path is not set. Please set this variable first.
exit /b 1
)
if "%model_path%"=="" (
echo Error: model_path is not set. Please set this variable first.
exit /b 1
)
:: 设置环境变量
set TOKENIZERS_PARALLELISM=false
set PYTHONPATH=%lightx2v_path%;%PYTHONPATH%
set ENABLE_PROFILING_DEBUG=true
set ENABLE_GRAPH_MODE=false
set DTYPE=BF16
echo 环境变量设置完成！
echo PYTHONPATH: %PYTHONPATH%
echo CUDA_VISIBLE_DEVICES: %CUDA_VISIBLE_DEVICES%
echo 模型路径: %model_path%
:: 切换到项目目录
cd /d %lightx2v_path%
:: 运行推理
python -m lightx2v.infer ^
--model_cls wan2.1 ^
--task i2v ^
--model_path %model_path% ^
--config_json %lightx2v_path%/configs/offload/disk/wan_i2v_phase_lazy_load_480p.json ^
--prompt "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside." ^
--negative_prompt "镜头晃动，色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走" ^
--image_path %lightx2v_path%/assets/inputs/imgs/img_0.jpg ^
--save_video_path %lightx2v_path%/save_results/output_lightx2v_wan_i2v.mp4
echo 推理完成！
pause
\ No newline at end of file
scripts/win/run_wan_t2v.bat 0 → 100644
View file @ dfe72c5d
@echo off
chcp 65001 >nul
echo 启动LightX2V T2V推理...
:: 设置路径
set lightx2v_path=F:\project\code\lightx2v-main\LightX2V-main\LightX2V-main
set model_path=D:\Wan2.1-T2V-1.3B-Lightx2v
:: 检查CUDA_VISIBLE_DEVICES
if "%CUDA_VISIBLE_DEVICES%"=="" (
set cuda_devices=0
echo Warn: CUDA_VISIBLE_DEVICES is not set, using default value: %cuda_devices%, change at shell script or set env variable.
set CUDA_VISIBLE_DEVICES=%cuda_devices%
)
:: 检查路径
if "%lightx2v_path%"=="" (
echo Error: lightx2v_path is not set. Please set this variable first.
exit /b 1
)
if "%model_path%"=="" (
echo Error: model_path is not set. Please set this variable first.
exit /b 1
)
:: 设置环境变量
set TOKENIZERS_PARALLELISM=false
set PYTHONPATH=%lightx2v_path%;%PYTHONPATH%
set ENABLE_PROFILING_DEBUG=true
set ENABLE_GRAPH_MODE=false
set DTYPE=BF16
echo 环境变量设置完成！
echo PYTHONPATH: %PYTHONPATH%
echo CUDA_VISIBLE_DEVICES: %CUDA_VISIBLE_DEVICES%
echo 模型路径: %model_path%
:: 切换到项目目录
cd /d %lightx2v_path%
:: 运行推理
python -m lightx2v.infer ^
--model_cls wan2.1 ^
--task t2v ^
--model_path %model_path% ^
--config_json %lightx2v_path%/configs/offload/block/wan_t2v_1_3b.json ^
--prompt "A beautiful sunset over a calm ocean, with golden rays of light reflecting on the water surface. The sky is painted with vibrant orange and pink clouds. A peaceful and serene atmosphere." ^
--negative_prompt "镜头晃动，色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走" ^
--save_video_path %lightx2v_path%/save_results/output_lightx2v_wan_t2v.mp4
echo 推理完成！
pause
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