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README.md	适配FlashVSR-v1.1模型 Co-authored-by: socrahow1<suzihao4@h-partners.com> # message auto-generated for no-merge-commit merge: !7524 merge master into master 适配FlashVSR-v1.1模型 Created-by: socrahow1 Commit-by: socrahow1 Merged-by: ascend-robot Description: ## Motivation 适配FlashVSR-v1.1模型 ## Modification 适配FlashVSR-v1.1模型 ## Self-test (Optional) If modifications to this PR may cause/fix function/accuracy/performance DTSs/issues, a self-inspection record needs to be attached. ## BC-breaking (Optional) If there are compatibility issues, such as dependencies on cann/torch_npu versions, they need to be explained in the PR. ## Checklist Before PR: - [ ] The new code needs to comply with the Clean Code specification. - [ ] The PR content is self-checked, and the expression can be clear and the writing standardized After PR: - [ ] CLA has been signed and all committers have signed the CLA in this PR. - [ ] The ci-pipeline is passed, Code Check is passed. See merge request: Ascend/ModelZoo-PyTorch!7524	1 个月前
diff.patch	适配FlashVSR-v1.1模型 Co-authored-by: socrahow1<suzihao4@h-partners.com> # message auto-generated for no-merge-commit merge: !7524 merge master into master 适配FlashVSR-v1.1模型 Created-by: socrahow1 Commit-by: socrahow1 Merged-by: ascend-robot Description: ## Motivation 适配FlashVSR-v1.1模型 ## Modification 适配FlashVSR-v1.1模型 ## Self-test (Optional) If modifications to this PR may cause/fix function/accuracy/performance DTSs/issues, a self-inspection record needs to be attached. ## BC-breaking (Optional) If there are compatibility issues, such as dependencies on cann/torch_npu versions, they need to be explained in the PR. ## Checklist Before PR: - [ ] The new code needs to comply with the Clean Code specification. - [ ] The PR content is self-checked, and the expression can be clear and the writing standardized After PR: - [ ] CLA has been signed and all committers have signed the CLA in this PR. - [ ] The ci-pipeline is passed, Code Check is passed. See merge request: Ascend/ModelZoo-PyTorch!7524	1 个月前

FlashVSR-v1.1-推理指导

概述
推理环境准备
快速上手

概述

FlashVSR 是一个面向实时扩散模型的流式视频超分辨率框架，旨在通过实现高效性、可扩展性和实时性能，使基于扩散模型的视频超分辨率技术变得实用化。

本文的介绍了FlashVSR-v1.1模型的部署流程，包括推理环境准备、模型部署、功能验证，旨在帮助用户快速完成模型部署和验证。

版本说明：

url=https://github.com/OpenImagingLab/FlashVSR
commit_id=b527c6f285fb30df530f5febc8b45764a789c961

推理环境准备

该模型需要以下插件与驱动
表 1 版本配套表

配套	版本	环境准备指导
固件与驱动	25.5.2	Pytorch框架推理环境准备
CANN	8.5.0	-
Python	3.11	-
PyTorch	2.6.0	-
Ascend Extension PyTorch	2.6.0.post5	-
硬件	Atlas 800T A2, Atlas 800I A2	-

快速上手

获取源码

获取PyTotch源码

git clone https://gitcode.com/Ascend/ModelZoo-PyTorch.git
cd ModelZoo-PyTorch/MindIE/MultiModal/FlashVSR-v1.1
git clone https://github.com/OpenImagingLab/FlashVSR.git
cd FlashVSR
git reset --hard b527c6f285fb30df530f5febc8b45764a789c961
cd ..
git clone https://gitcode.com/Ascend/MindIE-SD.git
cd MindIE-SD
git reset --hard 4aa3014c21ea171c3255d2d2591debeaac9e5202
cd ..

修改第三方库

# 注：patch命令只能执行一次，第二次执行会报错
cd FlashVSR
git apply ../diff.patch
cd ..

安装依赖

# openeuler
yum update
yum -y install opencv ffmpeg
# ubuntu
apt-get update
apt-get install -y libgl1 libglib2.0-0 ffmpeg

cd FlashVSR
pip install -e .
pip install -r requirements.txt
cd ../MindIE-SD
python setup.py bdist_wheel
cd ..
pip install MindIE-SD/dist/xxx.whl #根据实际情况修改xxx

获取权重

cd FlashVSR/examples/WanVSR
git lfs install
git clone https://huggingface.co/JunhaoZhuang/FlashVSR-v1.1

环境变量

# 一级流水优化
export TASK_QUEUE_ENABLE=1
# combind标志，用于优化两个非连续算子组合类场景
export COMBIND_ENABLE=1
# CPU绑核
export CPU_AFFINITY_CONF=1

执行推理

# full模式
python infer_flashvsr_v1.1_full.py
# tiny模式
python infer_flashvsr_v1.1_tiny.py
# tiny_long模式
python infer_flashvsr_v1.1_tiny_long_video.py

具体推理文件以及结果保存路径可以在推理脚本中配置，默认从inputs文件夹中读取视频文件(warm_up和正式推理文件)，输出结果到results中

性能数据

注：为了获取真实性能数据，推理前需要先进行warm_up

机器	模式	输入尺寸	时长	放大倍率	输出	推理时长
Atlas 800T A2	full	384x384@30fps	2s	2.0	768x768@30fps	13.85s
Atlas 800T A2	full	672x384@30fps	3s	2.0	1280x768@30fps	25.60s
Atlas 800T A2	full	384x672@30fps	3s	2.0	768x1280@30fps	23.31s
Atlas 800T A2	full	640x480@30fps	2s	2.0	1280x896@30fps	23.35s
Atlas 800T A2	tiny	384x384@30fps	2s	2.0	768x768@30fps	11.25s
Atlas 800T A2	tiny	672x384@30fps	3s	2.0	1280x768@30fps	20.20s
Atlas 800T A2	tiny	384x672@30fps	3s	2.0	768x1280@30fps	19.99s
Atlas 800T A2	tiny	640x480@30fps	2s	2.0	1280x896@30fps	19.04s
Atlas 800T A2	tiny-long	768x416@30fps	54s	2.0	1536x768@30fps	498.74s