MobileNet v2网络是由google团队在2018年提出的,相比MobileNet V1网络,准确率更高,模型更小。 MobileNet v2 模型的特点: 如上图,mobileNet v2在V1基础上进行了改进。 刚刚说了MobileNet v1网络中的亮点是DW卷积,那么在MobileNet v2中的亮点就是Inverted residual block(倒残差结构),同时分析了v1的几个缺点并针对...
shufflenet = models.shufflenet_v2_x1_0() mobilenet_v2 = models.mobilenet_v2() mobilenet_v3_large = models.mobilenet_v3_large() mobilenet_v3_small = models.mobilenet_v3_small() resnext50_32x4d = models.resnext50_32x4d() wide_resnet50_2 = models.wide_resnet50_2() mnasnet = models.mn...
shufflenet= models.shufflenet_v2_x1_0(pretrained=True) mobilenet_v2= models.mobilenet_v2(pretrained=True) mobilenet_v3_large= models.mobilenet_v3_large(pretrained=True) mobilenet_v3_small= models.mobilenet_v3_small(pretrained=True) resnext50_32x4d= models.resnext50_32x4d(pretrained=True) wide_resn...
shufflenet = models.shufflenet_v2_x1_0(pretrained=True) mobilenet_v2 = models.mobilenet_v2(pretrained=True) mobilenet_v3_large = models.mobilenet_v3_large(pretrained=True) mobilenet_v3_small = models.mobilenet_v3_small(pretrained=True) resnext50_32x4d = models.resnext50_32x4d(pretrained=True) wi...
shufflenet = models.shufflenet_v2_x1_0(pretrained=True) mobilenet_v2 = models.mobilenet_v2(pretrained=True) mobilenet_v3_large = models.mobilenet_v3_large(pretrained=True) mobilenet_v3_small = models.mobilenet_v3_small(pretrained=True) resnext50_32x4d = models.resnext50_32x4d(pretrained=True) ...
For mobilenet_v2, it's 1280 # so we need to add it here backbone.out_channels = 1280 # let's make the RPN generate 5 x 3 anchors per spatial # location, with 5 different sizes and 3 different aspect # ratios. We have a Tuple[Tuple[int]] because each feature # map could ...
综述解读:【嵌入式AI部署&基础网络篇】轻量化神经网络精述--MobileNet V1-3、ShuffleNet V1-2、NasNet - **MobileNets:** - **MobileNetV2:** - **MobileNetV3:** - **ShuffleNet:** - **ShuffleNet V2:** - **SqueezeNet** - **Xception** - **MixNet** - **GhostNet** 4.4 生成对抗网络GAN...
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet,
1600+ pytorch-image-models: PyTorch图像模型、脚本、与训练权重—— (SE)ResNet/ResNeXT, DPN, EfficientNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet等等。 1000- CIFAR-ZOO:以CIFAR为基准的多种CNN架构的PyTorch实现。 1000- d2l-pytorch: 本项目尝试复制《动手深度学习(Dive into Deep Lear...
2600+ pytorch-image-models: PyTorch图像模型、脚本、与训练权重—— (SE)ResNet/ResNeXT, DPN, EfficientNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet等等。 1000- CIFAR-ZOO:以CIFAR为基准的多种CNN架构的PyTorch实现。 2700+ d2l-pytorch: 本项目尝试复制《动手深度学习(Dive into Deep Lear...