# ShuffleNet-Series **Repository Path**: dengly/ShuffleNet-Series ## Basic Information - **Project Name**: ShuffleNet-Series - **Description**: https://github.com/megvii-model/ShuffleNet-Series 副本 - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2021-04-20 - **Last Updated**: 2021-04-20 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # ShuffleNet Series ShuffleNet Series by Megvii Research. ## Introduction This repository contains the following ShuffleNet series models: - ShuffleNetV1: [ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices](https://arxiv.org/abs/1707.01083) - ShuffleNetV2: [ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design](https://arxiv.org/abs/1807.11164) - ShuffleNetV2+: A strengthen version of ShuffleNetV2. - ShuffleNetV2.Large: A deeper version based on ShuffleNetV2 with 10G+ FLOPs. - ShuffleNetV2.ExLarge: A deeper version based on ShuffleNetV2 with 40G+ FLOPs. - OneShot: [Single Path One-Shot Neural Architecture Search with Uniform Sampling](https://arxiv.org/abs/1904.00420) - DetNAS: [DetNAS: Backbone Search for Object Detection](https://arxiv.org/abs/1903.10979) ## Trained Models - OneDrive download: [Link](https://1drv.ms/f/s!AgaP37NGYuEXhRfQxHRseR7eSxXo) - BaiduYun download: [Link](https://pan.baidu.com/s/1EUQVoFPb74yZm0JWHKjFOw) (extract code: mc24) ## Details ### ShuffleNetV2+ The following is the comparison between ShuffleNetV2+ and [MobileNetV3](https://arxiv.org/pdf/1905.02244). Details can be seen in [ShuffleNetV2+](https://github.com/megvii-model/ShuffleNet-Series/tree/master/ShuffleNetV2%2B). | Model | FLOPs | #Params | Top-1 | Top-5 | |:------------------------|:---------:|:---------:|:---------:|:---------:| ShuffleNetV2+ Large | 360M | 6.7M | **22.9** | 6.7 | MobileNetV3 Large 224/1.25 | 356M | 7.5M | 23.4 | - | ShuffleNetV2+ Medium | 222M | 5.6M | **24.3** | 7.4 | MobileNetV3 Large 224/1.0 | 217M | 5.4M | 24.8 | - | ShuffleNetV2+ Small | 156M | 5.1M | **25.9** | 8.3 | MobileNetV3 Large 224/0.75 | 155M | 4.0M | 26.7 | - | ### ShuffleNetV2 The following is the comparison between ShuffleNetV2 and [MobileNetV2](https://arxiv.org/abs/1801.04381). Details can be seen in [ShuffleNetV2](https://github.com/megvii-model/ShuffleNet-Series/tree/master/ShuffleNetV2). | Model | FLOPs | #Params | Top-1 | Top-5 | | :--------------------- | :---: | :------: | :----------: | :------: | | ShuffleNetV2 2.0x | 591M | 7.4M | **25.0** | 7.6 | | MobileNetV2 (1.4) | 585M | 6.9M | 25.3 | - | | ShuffleNetV2 1.5x | 299M | 3.5M | **27.4** | 9.4 | | MobileNetV2 | 300M | 3.4M | 28.0 | - | | ShuffleNetV2 1.0x | 146M | 2.3M | 30.6 | 11.1 | | ShuffleNetV2 0.5x | 41M | 1.4M | 38.9 | 17.4 | ### ShuffleNetV2.Large The following is the comparison between ShuffleNetV2.Large and [SENet](https://arxiv.org/abs/1709.01507). Details can be seen in [ShuffleNetV2.Large](https://github.com/megvii-model/ShuffleNet-Series/tree/master/ShuffleNetV2.Large). | Model | FLOPs | #Params | Top-1 | Top-5 | | :--------------------- | :---: | :------: | :---: | :---: | | ShuffleNetV2.Large | 12.7G | 140.7M | **18.56** | 4.48 | | SENet | 20.7G | - | 18.68 | 4.47 | ### ShuffleNetV2.ExLarge The following is the result of ShuffleNetV2.ExLarge. Details can be seen in [ShuffleNetV2.ExLarge](https://github.com/megvii-model/ShuffleNet-Series/tree/master/ShuffleNetV2.ExLarge). | Model | FLOPs | #Params | Top-1 | Top-5 | | :--------------------- | :---: | :------: | :---: | :---: | | ShuffleNetV2.ExLarge | 46.2G | 254.7M | 15.52 | 2.9 | ### ShuffleNetV1 The following is the comparison between ShuffleNetV1 and [MobileNetV1](https://arxiv.org/abs/1704.04861). Details can be seen in [ShuffleNetV1](https://github.com/megvii-model/ShuffleNet-Series/tree/master/ShuffleNetV1). | Model | FLOPs | #Params | Top-1 | Top-5 | |:------------------------|:---------:|:---------:|:---------:|:---------:| ShuffleNetV1 2.0x (group=3)| 524M | 5.4M | **25.9** | 8.6 | ShuffleNetV1 2.0x (group=8)| 522M | 6.5M | 27.1 | 9.2 | 1.0 MobileNetV1-224 | 569M | 4.2M | 29.4 | - | ShuffleNetV1 1.5x (group=3)| 292M | 3.4M | **28.4** | 9.8 | ShuffleNetV1 1.5x (group=8)| 290M | 4.3M | 29.0 | 10.4 | 0.75 MobileNetV1-224 | 325M | 2.6M | 31.6 | - | ShuffleNetV1 1.0x (group=3)| 138M | 1.9M | 32.2 | 12.3 | ShuffleNetV1 1.0x (group=8)| 138M | 2.4M | **32.0** | 13.6 | 0.5 MobileNetV1-224 | 149M | 1.3M | 36.3 | - | ShuffleNetV1 0.5x (group=3)| 38M | 0.7M | 42.7 | 20.0 | ShuffleNetV1 0.5x (group=8)| 40M | 1.0M | **41.2** | 19.0 | 0.25 MobileNetV1-224 | 41M | 0.5M | 49.4 | - | ### OneShot The following is the comparison between Single Path One-Shot NAS and other NAS counterparts. Details can be seen in [OneShot](https://github.com/megvii-model/ShuffleNet-Series/tree/master/OneShot). | Model | FLOPs | #Params | Top-1 | Top-5 | | :--------------------- | :---: | :------: | :---: | :---: | | OneShot | 328M | 3.4M | **25.1** | 8.0 | | NASNET-A| 564M | 5.3M | 26.0 | 8.4 | | PNASNET| 588M | 5.1M | 25.8 | 8.1 | | MnasNet| 317M | 4.2M | 26.0 | 8.2 | | DARTS| 574M| 4.7M | 26.7 | 8.7 | | FBNet-B| 295M| 4.5M | 25.9 | - | ### DetNAS The following is the performance of DetNAS backbones on ImageNet, compared with ResNet. Backbone details can be seen in [DetNAS](https://github.com/megvii-model/ShuffleNet-Series/tree/master/DetNAS). | Model | FLOPs| #Params| Top-1 | Top-5 | mAP* | | :------------ | :---:| :-----:| :---: | :---: | :--------------: | |300M (VOC, RetinaNet) | 300M | 3.5M | 25.4 | 8.1 | 80.1 | |300M (VOC, FPN) | 300M | 3.7M | 25.9 | 8.3 | 81.5 | |300M (COCO, RetinaNet) | 300M | 3.7M | 26.0 | 8.4 | 33.3 | |300M (COCO, FPN) | 300M | 3.5M | 26.2 | 8.4 | 36.4 | |1.3G (COCO, FPN) | 1.3G | 10.4M | **22.8** | 6.5 | 40.0 | |3.8G (COCO, FPN) | 3.8G | 29.5M | **21.6** | 6.3 | **42.0** | |ResNet50 (COCO, FPN) | 3.8G | - | 23.9 | 7.1 | 37.3 | |ResNet101 (COCO, FPN) | 7.6G | - | 22.6 | 6.4 | 40.0 | * More about DetNAS in [Link](https://github.com/megvii-model/DetNAS).