LAE-DINO
3
license:mit
by
jaychempan
Image Model
OTHER
New
0 downloads
Early-stage
Edge AI:
Mobile
Laptop
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Unknown
Mobile
Laptop
Server
Quick Summary
AI model with specialized capabilities.
Code Examples
text
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_subtext
python LAE-Label/crop_huge_images.py --input_folder ./LAE_data/DATASET --output_folder ./LAE_data/DATASET_sub开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.git开发并直接运行 mmdettext
conda create --name lae python=3.8 -y
conda activate lae
cd LAE-DINO/mmdetection_lae
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install -U openmim
mim install mmengine
mim install "mmcv>=2.0.0"
# 开发并直接运行 mmdet
pip install -v -e .
pip install -r requirements/multimodal.txt
pip install emoji ddd-dataset
pip install git+https://github.com/lvis-dataset/lvis-api.gittext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
cd LAE-DINO
huggingface-cli download --resume-download google-bert/bert-base-uncased --local-dir weights/bert-base-uncasedtext
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