train_loader = DataLoader(train_ds,batch_size=2,shuffle=True,num_workers=4,...) model = monai.networks.nets.UNet(spatial_dims=2,in_channels=1,out_channels=1, channels=(16, 32, 64, 128, 256),strides=(2, 2, 2, 2),num_res_units=2,).to(device) loss_function = monai.losses.Di...
import torch import torch.nn as nn import torch.nn.functional as F from torchsummaryX import summary from torchinfo import summary as info_summary from torchviz import make_dot from monai.networks.nets import GlobalNet # Example usage device = torch.device("cuda" if torch.cuda.is_available(...
LinkedIn is an internet platform company focused on connecting the world's professionals. The company has a diversified business model with revenues driven from user subscriptions, advertising sales, and software licensing. The LinkedIn website was launched in 2003 and is the largest professional networ...
已有帐号?立即登录 此仓库是为了提升国内下载速度的镜像仓库,每日同步一次。 原始仓库:https://github.com/Project-MONAI/MONAI dev 克隆/下载 git config --global user.name userName git config --global user.email userEmail 分支7 标签111 monai-botAuto3DSeg algo_template hash update (#8406)4986d7f6...
networks Resolved issue with loading pre-trained weights in ResNet (#7924) Fixed error where torch.device object had no attribute gpu_id during TensorRT export (#8019) Corrected function for loading older weights in DiffusionModelUNet (#8031) Switched to torch_tensorrt.Device instead of torch.dev...
GenerativeModelsis moved to monai core. We plan to refactor three MAISI networks, including AutoencoderKlMaisi, DiffusionModelUNetMaisi, and ControlNetMaisi and use monai core components. Public Describe the solution you'd like A clear and concise description of what you want to happen. ...
model = monai.networks.nets.UNet( spatial_dims=2, in_channels=1, out_channels=1, channels=(16, 32, 64, 128), strides=(2, 2, 2), num_res_units=2, ).to(device) loss_function = monai.losses.DiceLoss(sigmoid=True) optimizer = torch.optim.Adam(model.parameters(), 5e-3) ...
importmonaifrommonai.networks.netsimportUNet# 创建模型model=UNet(dimensions=2,in_channels=1,out_channels=2,kernel_size=3)print(model)# 打印模型结构 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 这里的UNet是医学影像处理中常见的深度学习模型。
model = monai.networks.nets.DenseNet121( spatial_dims=3, in_channels=1, out_channels=2).to(device) loss_function = torch.nn.CrossEntropyLoss() optimizer = torch.optim.Adam(model.parameters(), 1e-5) # start a typical PyTorch training ...
model = monai.networks.nets.UNet().to(device) model = nn.DataParallel(model) 通过两种方式可以指定需要使用的GPU,第一种是在代码里设置os.environ, 第二种是在终端运行代码前,加一句export CUDA_VISIBLE_DEVICES=0,1。按照自...