NOTE
要复现论文的github：aerial-d

下载并安装 Miniconda#

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sudo apt update

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cd ~

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wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh

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bash Miniconda3-latest-Linux-x86_64.sh

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Do you wish the installer to initialize Miniconda3? yes

创建干净环境（Python 3.12）#

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conda create -n aerial python=3.12

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conda activate aerial

安装 RTX5090 必须的 PyTorch（Nightly cu128）#

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pip install --pre torch torchvision torchaudio \
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  --index-url https://download.pytorch.org/whl/nightly/cu128

验证 GPU 是否正确支持#

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python - <<'PY'
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import torch
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print("torch:", torch.__version__)
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print("cuda runtime:", torch.version.cuda)
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print("gpu available:", torch.cuda.is_available())
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print("gpu name:", torch.cuda.get_device_name(0))
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PY

拉取 SAMWISE 工程#

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cd ~

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git clone https://github.com/luispl77/aerial-d.git

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cd aerial-d

安装依赖#

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pip install -U pip

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这两句添加注释
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# torch==2.7.1
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# torchvision==0.22.1

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pip install -i https://pypi.org/simple -r requirements.txt

快速 check#

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python -c "import torch; print(torch.__version__); print(torch.cuda.is_available()); print(torch.cuda.get_device_name(0)); print(torch.cuda.get_device_capability(0))"

下载数据集#

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cd ~/aerial-d

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huggingface-cli download luisml77/aerial-d --repo-type dataset --local-dir datagen/dataset

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cd ~/aerial-d/datagen/dataset

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sudo apt install unzip

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unzip aeriald.zip

下载 checkpoint#

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cd ~/aerial-d/rsrefseg

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huggingface-cli download luisml77/rsrefseg \
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  --repo-type model \
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  --local-dir models

验证实验数据#

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cd ~/aerial-d

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python test.py \
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  --model_name rsrefseg_combined \
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  --dataset_type aeriald \
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  --sam_model facebook/sam-vit-large