elif dataset == 'cityscapes': return '/path/to/datasets/cityscapes/' # foler that contains leftImg8bit/ elif dataset == 'coco': return '/path/to/datasets/coco/' #添加我自己制作的Abyssinian数据集 elif dataset == 'Abyssinian': return '/home/yuxin/pytorch-deeplab-xception-master/VOCdevkit/A...
parser.add_argument('--backbone', type=str, default='resnet', choices=['resnet', 'xception', 'drn', 'mobilenet'], help='backbone name (default: resnet)') parser.add_argument('--ckpt', type=str, default='deeplab-resnet.pth', help='saved model') parser.add_argument('--out-stride...
有看到一个，不知是否可行https://github.com/lizhengwei1992/mobilenetv2_deeplabv3_pytorch/blob/maste...
THCudaCheck FAILfile=/opt/conda/conda-bld/pytorch_1532581333611/work/aten/src/THC/THCCachingHostAllocator.cppline=271error=59: device-sideasserttriggered Traceback (most recent call last):File"/data_2/tmp_paper/image-segmentation/DeepLab/v3+/pytorch0.41/pytorch-deeplab-xception-master/train.py",li...
DeepLabv1 模型结构很容易理解: 首先它是个VGG-16 然后为了使图像语义分割更准确,5 个 max-pooling 层 skip 了后两个(具体实现上,看G站上的代码,似乎没有去除,而是保留了后两个 max-pooling ,只是将 stride = 2 改为 stride = 1,kernal = 3),最后卷积层的输出整体 stride 从 32x 下降至 8x。
This is a PyTorch(0.4.1) implementation ofDeepLab-V3-Plus. It can use Modified Aligned Xception and ResNet as backbone. Currently, we train DeepLab V3 Plus using Pascal VOC 2012, SBD and Cityscapes datasets. Installation The code was tested with Anaconda and Python 3.6. After installing the ...
This branch is up to date with VainF/DeepLabV3Plus-Pytorch:master.Folders and files Latest commit VainF Update README.md 4e1087d· Oct 11, 2022 History149 Commits datasets Delete cityscapes Jun 20, 2022 metrics DeepLabV3 & DeepLabV3+ Dec 3, 2019 network [VainF#85]: Xception backbone for...
2019.01.21 - Updata the code for paper performance achieved! Now deeplabv3+res101 achieve 79.155% and deeplabv3+xception achieve 79.945% on PASCAL VOC 2012 val set. The main bug is the missing ofpatch_replication_callback()function of Synchronized Batch Normalization. ...
功能和待办事项 支持不同的细分模型,例如DeepLabv3,DeepLabv3 +,PSPNet 多GPU训练 多GPU同步BatchNorm 支持不同的骨干网,例如Mobilenet,Xception 在MS-COCO上预训练的模型 分布式培训 我们愿意提出要求。 安装 安装依赖项 请安装PyTorch-1.1.0和Python3.6.5。 我们强烈建议您使用我们已建立的PyTor ...
ShuffleNet是由2017年07月发布的轻量级网络,设计用于移动端设备,在MobileNet之后的网络架构。主要的创新点在于使用了分组卷积(group convolution)和通道打乱(channel shuffle)。 分组卷积和通道打乱 分组卷积分组卷积最早由AlexNet中使用。由于当时的硬件资源有限,训练AlexNet时卷积操作不能全部放在同一个GPU处理,因此作者把特...