======== Linux: conda activate pytorch2 git clone https://github.com/facebookresearch/detectron2.git cd detectron2 pip install -e . git clone https://github.com/facebookresearch/Mask2Former.git cd Mask2Former pip install -r requirements.txt # 为 MSDeformAttn 编译 CUDA 内核 cd mask2former/modeling/pixel_decoder/ops sh make.sh ======== ======== Windows: 设置环境变量： E:\dev\Qt5.14.2\Tools\mingw730_64\bin 修改D:\detectron2_windows\detectron2\layers\csrc\nms_rotated\nms_rotated_cuda.cu #include/*#ifdef WITH_CUDA #include "../box_iou_rotated/box_iou_rotated_utils.h" #endif // TODO avoid this when pytorch supports "same directory" hipification #ifdef WITH_HIP #include "box_iou_rotated/box_iou_rotated_utils.h" #endif*/ #include "box_iou_rotated/box_iou_rotated_utils.h" cd D:\detectron2_windows pip install -e . cd D:\Mask2Former_windows pip install -r requirements.txt Use git-bash: cd "E:\miniconda3\Scripts" source activate conda activate pytorch2 cd "D:\Mask2Former_windows\mask2former\modeling\pixel_decoder\ops" sh make.sh ======== 下载预训练模型 https://github.com/facebookresearch/Mask2Former/blob/main/MODEL_ZOO.md cd demo python demo.py --config-file ../configs/coco/instance-segmentation/maskformer2_R50_bs16_50ep.yaml --input input1.jpg --output ./output/ --opts MODEL.WEIGHTS ../model_final_3c8ec9.pkl python demo.py --config-file ../configs/coco/instance-segmentation/maskformer2_R50_bs16_50ep.yaml --input F:/mask/input_imgs/1000068_p4_upper.jpg --output ./output/ --opts MODEL.WEIGHTS ../output/model_0004999.pth python train_net.py --num-gpus 1 --config-file ./configs/coco/instance-segmentation/maskformer2_R50_bs16_50ep.yaml --resume SOLVER.IMS_PER_BATCH 3 SOLVER.BASE_LR 0.0001 python train_net.py --num-gpus 1 --config-file ./configs/coco/instance-segmentation/swin/maskformer2_swin_large_IN21k_384_bs16_100ep.yaml --resume SOLVER.IMS_PER_BATCH 3 SOLVER.BASE_LR 0.0001 python train_net.py --num-gpus 1 --config-file ./configs/coco/instance-segmentation/swin/maskformer2_swin_small_bs16_50ep.yaml --resume SOLVER.IMS_PER_BATCH 2 SOLVER.BASE_LR 0.0001