hc-skadi/ascendc/mmdet

Claude Code and agent skill by hc-skadi/ascendc

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在昇腾NPU容器中安装mmdetection。适用于目标检测模型的开发。

Install

npx vskill@latest install hc-skadi/ascendc/mmdet

SKILL.md

The same SKILL.md was published earlier as ascend/agent-skills/mmdet.

ascend-mmdet-install

功能

在昇腾NPU容器中安装 mmdetection（2D目标检测库）

前置条件

  • mmcv 已安装
  • 容器中已安装 Ascend CANN 和 torch_npu
  • 工作目录已挂载

使用

步骤1：确认前置条件

确保 mmcv 已正确安装：

bash
python -c "import mmcv; print(mmcv.__version__)"
步骤2：克隆mmdetection仓库

根据网络情况选择：

服务器直连：

bash
git clone -b v2.24.0 https://github.com/open-mmlab/mmdetection.git

服务器网络超时：配置代理或本地克隆后scp传输

bash
# 方案1：配置代理
export http_proxy=http://proxy:port
export https_proxy=http://proxy:port
git clone -b v2.24.0 https://github.com/open-mmlab/mmdetection.git
 
# 方案2：本地克隆后传输（仍使用GitHub链接）
# 本地执行
git clone -b v2.24.0 https://github.com/open-mmlab/mmdetection.git
scp -r mmdetection user@server:/target/path/

重要：始终使用GitHub官方链接，不使用镜像站点。

步骤3：应用patch（如有）
bash
cd mmdetection
cp /path/to/DrivingSDK/model_examples/BEVFormer/mmdet_config.patch .
git apply --reject mmdet_config.patch
步骤4：安装
bash
source /opt/conda/bin/activate <conda-env-name>
pip install -e .
步骤5：验证安装
bash
python -c "import mmdet; print(mmdet.__version__)"

NPU验证：

bash
python -c "import site; print([p for p in site.getsitepackages() if 'cuda' in p.lower()])"
# 应输出空列表

常见问题

  • 依赖缺失：确保 mmcv 和 mmengine 已安装
  • patch失败：跳过非关键patch或手动处理

决策指引

向用户提问：

  1. mmcv 是否已安装？
  2. 服务器网络能否访问GitHub？
  3. 是否需要应用特定patch？

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