From 531a16d385ee352320aaae951cd61145f7dece88 Mon Sep 17 00:00:00 2001 From: zhangchenrui Date: Thu, 11 Sep 2025 11:19:08 +0800 Subject: [PATCH] delete -no-check-certificate --- model_examples/GameFormer/README.md | 2 +- model_examples/HPTR/README.md | 2 +- model_examples/LaneSegNet/README.md | 5 ++--- model_examples/MapTR/README.md | 5 ++--- model_examples/PivotNet/README.md | 11 +++++------ model_examples/QCNet/README.md | 2 +- model_examples/Sparse4D/README.md | 2 +- model_examples/SparseDrive/README.md | 2 +- model_examples/StreamPETR/README.md | 5 ++--- 9 files changed, 16 insertions(+), 20 deletions(-) diff --git a/model_examples/GameFormer/README.md b/model_examples/GameFormer/README.md index 52071d28..04cc0b39 100644 --- a/model_examples/GameFormer/README.md +++ b/model_examples/GameFormer/README.md @@ -89,7 +89,7 @@ ``` 对于arm64架构Linux系统，waymo官方并没有提供预先编译好whl包。为了方便用户使用，我们提供arm64系统编译的whl包，可以直接在华为云OBS上进行下载。 ``` - wget --no-check-certificate https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/DrivingSDK/packages/waymo_open_dataset_tf_2.11.0-1.5.0-py3-none-any.whl + wget https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/DrivingSDK/packages/waymo_open_dataset_tf_2.11.0-1.5.0-py3-none-any.whl pip install -r requirements_waymo.txt pip install waymo_open_dataset_tf_2.11.0-1.5.0-py3-none-any.whl ``` diff --git a/model_examples/HPTR/README.md b/model_examples/HPTR/README.md index cf7858ed..9fabab94 100644 --- a/model_examples/HPTR/README.md +++ b/model_examples/HPTR/README.md @@ -96,7 +96,7 @@ HPTR 是一种用于自动驾驶实时运动预测的层次化Transformer模型 ``` 对于 arm64 架构 Linux 系统，waymo 官方并没有提供预先编译好 whl 包。为了方便用户使用，我们提供 arm64 系统编译的 whl 包，可以直接在华为云 OBS 上进行下载： ``` - wget --no-check-certificate https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/DrivingSDK/packages/waymo_open_dataset_tf_2.11.0-1.5.0-py3-none-any.whl + wget https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/DrivingSDK/packages/waymo_open_dataset_tf_2.11.0-1.5.0-py3-none-any.whl pip install waymo_open_dataset_tf_2.11.0-1.5.0-py3-none-any.whl ``` diff --git a/model_examples/LaneSegNet/README.md b/model_examples/LaneSegNet/README.md index f24d1f95..c82aeb31 100644 --- a/model_examples/LaneSegNet/README.md +++ b/model_examples/LaneSegNet/README.md @@ -143,9 +143,8 @@ code_path=DrivingSDK/model_examples/LaneSegNet - 安装毕昇编译器 - 将CANN包安装目录记为cann_root_dir，执行下列命令安装毕昇编译器。 + 将CANN包安装目录记为cann_root_dir，执行下列命令安装毕昇编译器， 官网下载毕昇编译器4.1.0版本：https://www.hikunpeng.com/zh/developer/devkit/download/bishengcompiler。 ``` - wget https://kunpeng-repo.obs.cn-north-4.myhuaweicloud.com/BiSheng%20Enterprise/BiSheng%20Enterprise%20203.0.0/BiShengCompiler-4.1.0-aarch64-linux.tar.gz tar -xvf BiShengCompiler-4.1.0-aarch64-linux.tar.gz export PATH=$(pwd)/BiShengCompiler-4.1.0-aarch64-linux/bin:$PATH export LD_LIBRARY_PATH=$(pwd)/BiShengCompiler-4.1.0-aarch64-linux/lib:$LD_LIBRARY_PATH @@ -154,7 +153,7 @@ code_path=DrivingSDK/model_examples/LaneSegNet - 安装依赖，将安装mpdecimal依赖包的目录记为mpdecimal_install_path。 ``` - wget --no-check-certificate https://www.bytereef.org/software/mpdecimal/releases/mpdecimal-2.5.1.tar.gz + wget https://www.bytereef.org/software/mpdecimal/releases/mpdecimal-2.5.1.tar.gz tar -xvf mpdecimal-2.5.1.tar.gz cd mpdecimal-2.5.1 bash ./configure --prefix=mpdecimal_install_path diff --git a/model_examples/MapTR/README.md b/model_examples/MapTR/README.md index 1cc5b83f..fd88b03e 100644 --- a/model_examples/MapTR/README.md +++ b/model_examples/MapTR/README.md @@ -158,9 +158,8 @@ MapTR是一种高效的端到端Transformer模型，用于在线构建矢量化 - 安装毕昇编译器 - 将CANN包安装目录记为cann_root_dir，执行下列命令安装毕昇编译器。 + 将CANN包安装目录记为cann_root_dir，执行下列命令安装毕昇编译器，官网下载毕昇编译器4.1.0版本：https://www.hikunpeng.com/zh/developer/devkit/download/bishengcompiler。 ``` - wget https://kunpeng-repo.obs.cn-north-4.myhuaweicloud.com/BiSheng%20Enterprise/BiSheng%20Enterprise%20203.0.0/BiShengCompiler-4.1.0-aarch64-linux.tar.gz tar -xvf BiShengCompiler-4.1.0-aarch64-linux.tar.gz export PATH=$(pwd)/BiShengCompiler-4.1.0-aarch64-linux/bin:$PATH export LD_LIBRARY_PATH=$(pwd)/BiShengCompiler-4.1.0-aarch64-linux/lib:$LD_LIBRARY_PATH @@ -169,7 +168,7 @@ MapTR是一种高效的端到端Transformer模型，用于在线构建矢量化 - 安装依赖，将安装mpdecimal依赖包的目录记为mpdecimal_install_path。 ``` - wget --no-check-certificate https://www.bytereef.org/software/mpdecimal/releases/mpdecimal-2.5.1.tar.gz + wget https://www.bytereef.org/software/mpdecimal/releases/mpdecimal-2.5.1.tar.gz tar -xvf mpdecimal-2.5.1.tar.gz cd mpdecimal-2.5.1 bash ./configure --prefix=mpdecimal_install_path diff --git a/model_examples/PivotNet/README.md b/model_examples/PivotNet/README.md index 2d624f39..4ab92a44 100644 --- a/model_examples/PivotNet/README.md +++ b/model_examples/PivotNet/README.md @@ -154,9 +154,8 @@ code_path=model_examples/PivotNet - 安装毕昇编译器 - 将CANN包安装目录记为cann_root_dir，执行下列命令安装毕昇编译器。 + 将CANN包安装目录记为cann_root_dir，执行下列命令安装毕昇编译器，官网下载毕昇编译器4.1.0版本：https://www.hikunpeng.com/zh/developer/devkit/download/bishengcompiler。 ``` - wget https://kunpeng-repo.obs.cn-north-4.myhuaweicloud.com/BiSheng%20Enterprise/BiSheng%20Enterprise%20203.0.0/BiShengCompiler-4.1.0-aarch64-linux.tar.gz tar -xvf BiShengCompiler-4.1.0-aarch64-linux.tar.gz export PATH=$(pwd)/BiShengCompiler-4.1.0-aarch64-linux/bin:$PATH export LD_LIBRARY_PATH=$(pwd)/BiShengCompiler-4.1.0-aarch64-linux/lib:$LD_LIBRARY_PATH @@ -165,7 +164,7 @@ code_path=model_examples/PivotNet - 安装依赖，将安装mpdecimal依赖包的目录记为mpdecimal_install_path。 ``` - wget --no-check-certificate https://www.bytereef.org/software/mpdecimal/releases/mpdecimal-2.5.1.tar.gz + wget https://www.bytereef.org/software/mpdecimal/releases/mpdecimal-2.5.1.tar.gz tar -xvf mpdecimal-2.5.1.tar.gz cd mpdecimal-2.5.1 bash ./configure --prefix=mpdecimal_install_path @@ -232,9 +231,9 @@ code_path=model_examples/PivotNet ``` cd /path/to/pivotnet cd assets/weights -wget --no-check-certificate https://github.com/wenjie710/PivotNet/releases/download/v1.0/efficientnet-b0-355c32eb.pth . -wget --no-check-certificate https://github.com/wenjie710/PivotNet/releases/download/v1.0/resnet50-0676ba61.pth . -wget --no-check-certificate https://github.com/wenjie710/PivotNet/releases/download/v1.0/upernet_swin_tiny_patch4_window7_512x512.pth . +wget https://github.com/wenjie710/PivotNet/releases/download/v1.0/efficientnet-b0-355c32eb.pth . +wget https://github.com/wenjie710/PivotNet/releases/download/v1.0/resnet50-0676ba61.pth . +wget https://github.com/wenjie710/PivotNet/releases/download/v1.0/upernet_swin_tiny_patch4_window7_512x512.pth . ``` - 生成模型训练数据 diff --git a/model_examples/QCNet/README.md b/model_examples/QCNet/README.md index 13dc4cff..0f332a54 100644 --- a/model_examples/QCNet/README.md +++ b/model_examples/QCNet/README.md @@ -132,7 +132,7 @@ code_path=model_examples/QCNet 5. 安装 tcmalloc 高效内存资源分配库 ``` mkdir gperftools && cd gperftools - wget --no-check-certificate https://github.com/gperftools/gperftools/releases/download/gperftools-2.16/gperftools-2.16.tar.gz + wget https://github.com/gperftools/gperftools/releases/download/gperftools-2.16/gperftools-2.16.tar.gz tar -zvxf gperftools-2.16.tar.gz cd gperftools-2.16 ./configure diff --git a/model_examples/Sparse4D/README.md b/model_examples/Sparse4D/README.md index 295eb27d..51ffa437 100644 --- a/model_examples/Sparse4D/README.md +++ b/model_examples/Sparse4D/README.md @@ -152,7 +152,7 @@ ``` mkdir gperftools cd gperftools -wget https://github.com/gperftools/gperftools/releases/download/gperftools-2.16/gperftools-2.16.tar.gz --no-check-certificate +wget https://github.com/gperftools/gperftools/releases/download/gperftools-2.16/gperftools-2.16.tar.gz tar -zvxf gperftools-2.16.tar.gz cd gperftools-2.16 ./configure --prefix=/usr/local/lib --with-tcmalloc-pagesize=64 diff --git a/model_examples/SparseDrive/README.md b/model_examples/SparseDrive/README.md index 831f8295..8e827875 100644 --- a/model_examples/SparseDrive/README.md +++ b/model_examples/SparseDrive/README.md @@ -155,7 +155,7 @@ SparseDrive是一种基于稀疏化表征的端到端自动驾驶模型，基于 bash test/train_8p_full.sh # (option) downloading the stage1 weights to test the stage2 performance - wget https://github.com/swc-17/SparseDrive/releases/download/v1.0/sparsedrive_stage1.pth --no-check-certificate -O ckpt/sparsedrive_stage1.pth + wget https://github.com/swc-17/SparseDrive/releases/download/v1.0/sparsedrive_stage1.pth -O ckpt/sparsedrive_stage1.pth # performance bash test/train_8p_performance.sh diff --git a/model_examples/StreamPETR/README.md b/model_examples/StreamPETR/README.md index 1220c3bb..4ee3675d 100644 --- a/model_examples/StreamPETR/README.md +++ b/model_examples/StreamPETR/README.md @@ -231,10 +231,9 @@ chmod 777 StreamPETR/backfunc.sh 10. 编译优化 (1)python编译优化 -源码下载毕昇编译器： +官网下载毕昇编译器4.1.0版本：https://www.hikunpeng.com/zh/developer/devkit/download/bishengcompiler： ``` ulimit -n 4096 -wget --no-check-certificate https://kunpeng-repo.obs.cn-north-4.myhuaweicloud.com/BiSheng%20Enterprise/BiSheng%20Enterprise%20203.0.0/BiShengCompiler-4.1.0-aarch64-linux.tar.gz tar -xvf BiShengCompiler-4.1.0-aarch64-linux.tar.gz export PATH=$(pwd)/BiShengCompiler-4.1.0-aarch64-linux/bin:$PATH export LD_LIBRARY_PATH=$(pwd)/BiShengCompiler-4.1.0-aarch64-linux/lib:$LD_LIBRARY_PATH @@ -243,7 +242,7 @@ source {cann_root_dir}/set_env.sh 下载所需依赖： ``` -wget --no-check-certificate https://www.bytereef.org/software/mpdecimal/releases/mpdecimal-2.5.1.tar.gz +wget https://www.bytereef.org/software/mpdecimal/releases/mpdecimal-2.5.1.tar.gz tar -xvf mpdecimal-2.5.1.tar.gz cd mpdecimal-2.5.1 bash ./configure --prefix=/path/to/install/mpdecimal -- Gitee