Comments (6)
More details? Which toolkit/hardware did you use?
We test GhostNet on ARM with TFLite.
from efficient-ai-backbones.
Thanks for your reply!
I test the model on Intel i7 CPU with RTX 1080 Ti. The framework I am using is PyTorch(1.2), cuda10.1 is used by the way.
The basic model structure is ReCombinator network as https://github.com/SinaHonari/RCN
from efficient-ai-backbones.
Same question,I tested under the Darknet framework, and it will be faster when using the CPU, but it will be much slower when using the GPU.
from efficient-ai-backbones.
Same question,I tested under the Darknet framework, and it will be faster when using the CPU, but it will be much slower when using the GPU.
Your observation is normal. Ghost module is more suitable for ARM/CPU, and not friendly for GPU due to the Depthwise Conv.
from efficient-ai-backbones.
Same question,I tested under the Darknet framework, and it will be faster when using the CPU, but it will be much slower when using the GPU.
Your observation is normal. Ghost module is more suitable for ARM/CPU, and not friendly for GPU due to the Depthwise Conv.
thanks!
from efficient-ai-backbones.
Thank you for your answer. After using GhostMoudle, I found that the detection speed has slowed down. This has troubled me for a long time.
from efficient-ai-backbones.
Related Issues (20)
- 关于GhostNetv2不能下载
- 移动端测试问题 HOT 2
- 找不到mixup_batch函数
- RuntimeError: Error(s) in loading state_dict for DeepGCN: size mismatch for pos_embed: copying a param with shape torch.Size([1, 192, 14, 14]) from checkpoint, the shape in current model is torch.Size([1, 80, 56, 56]). HOT 1
- 使用ghostconv代替普通卷积,实例分割任务精度下降问题 HOT 3
- 关于K参数的选取问题 HOT 2
- BN层 HOT 1
- vig for segmentation HOT 1
- 可以提供下p-vig在coco数据集上的训练的模型代码以及参数设置嘛 HOT 1
- 请问这个代码要在多机多卡上进行训练的话,训练命令应该是什么样的呢?以及参数要怎么设置呢? HOT 1
- ViG模型获取
- 使用vig实现检测任务 HOT 1
- VIG中使用的KNN dilation HOT 8
- G-GhostNet中的Mix操作,原论文的描述和代码实现一致吗? HOT 2
- About the waveMlp.PATM function.
- 关于在VIG中使用超像素作为patch输入 HOT 2
- The code implementation of ParameterNet is not completely consistent with the paper description HOT 2
- 关于在VIG中设置patch的尺寸 HOT 1
- 官方模型权重怎样在非imagenet数据集上继续运行? HOT 4
- about FLOPs calculation HOT 2
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