PyTorch的推理时间和功耗表现如上图所示,ESPNetv2比ShuffleNetv2稍慢,但是在ImageNet上的能耗表现更好,ESPNetv2具有在准确率、功耗、延迟方面更好的trade-off,在终端设备上运行效果更好。 如上图所示,ESPNetv2比ESPNet更高效,准确率更高。 三、总结 ESPNet和ESPNetv2基于卷积因子分解思想,构建了一种使用空洞卷积的方法...
3、论文提供的源码使用的框架是pytorch,需要注意不同框架模型转换的细节(尤其是部分函数的不同)。 复现结果 stepsoptimage_sizebatch_sizedatasetmemorycardmIouconfig ESPNetV2 120k adam 1024x512 8 CityScapes 32G 4 0.6956 espnet_cityscapes_1024_512_120k_x2.yml EESP代码简介 class EESP(nn.Layer): """ ...
3、论文提供的源码使用的框架是pytorch,需要注意不同框架模型转换的细节(尤其是部分函数的不同)。 复现结果 stepsoptimage_sizebatch_sizedatasetmemorycardmIouconfig ESPNetV2 120k adam 1024x512 8 CityScapes 32G 4 0.6956 espnet_cityscapes_1024_512_120k_x2.yml EESP代码简介 class EESP(nn.Layer): """ ...
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network (CVPR2019) https://arxiv.org/pdf/1811.11431.pdf PyTorch: https://github.com/sacmehta/ESPNetv2 主要在ESPNet的基础上改进, 特点: 为了计算更加高效,见Figure 1: 将原来...
conda install pytorch torchvision -c pytorch Once installed, run the following commands in your terminal to verify the version: import torch torch.__version__ This should print something like this 0.4.1.post2. If your version is different, then follow PyTorch website here for more details....
cnn pytorch object-detection semantic-segmentation pascal-voc cityscapes mscoco imagenet-classifier imagenet-dataset cnn-classification shufflenetv2 espnetv2 dicenet Updated Dec 19, 2022 Python robinhad / ukrainian-tts Star 104 Code Issues Pull requests Ukrainian TTS (text-to-speech) using ESPNET ...
3、论文提供的源码使用的框架是pytorch,需要注意不同框架模型转换的细节(尤其是部分函数的不同)。 复现结果 stepsoptimage_sizebatch_sizedatasetmemorycardmIouconfig ESPNetV2 120k adam 1024x512 8 CityScapes 32G 4 0.6956 espnet_cityscapes_1024_512_120k_x2.yml EESP代码简介 class EESP(nn.Layer): """ ...
3、论文提供的源码使用的框架是pytorch,需要注意不同框架模型转换的细节(尤其是部分函数的不同)。 复现结果 stepsoptimage_sizebatch_sizedatasetmemorycardmIouconfig ESPNetV2 120k adam 1024x512 8 CityScapes 32G 4 0.6956 espnet_cityscapes_1024_512_120k_x2.yml EESP代码简介 class EESP(nn.Layer): """ ...
Introduction PyTorch implementation of realtime semantic segmentation models, support multi-gpu training and validating, automatic mixed precision training, knowledge distillation, hyperparameter optimization using Optuna etc. Requirements torch == 1.8.1 ...
Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.) - xiaoyufenfei/Efficient-Segmentati