https://github.com/jahongir7174/mobileone
MobileOne: An Improved One millisecond Mobile Backbone
https://github.com/jahongir7174/mobileone
classification imagenet mobileone pretrained python pytorch
Last synced: 12 days ago
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MobileOne: An Improved One millisecond Mobile Backbone
- Host: GitHub
- URL: https://github.com/jahongir7174/mobileone
- Owner: jahongir7174
- Created: 2023-04-10T03:41:10.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2024-03-07T05:40:45.000Z (over 1 year ago)
- Last Synced: 2025-06-03T11:33:56.780Z (5 months ago)
- Topics: classification, imagenet, mobileone, pretrained, python, pytorch
- Language: Python
- Homepage: https://arxiv.org/abs/2206.04040
- Size: 89.8 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
[MobileOne: An Improved One millisecond Mobile Backbone](https://arxiv.org/abs/2206.04040)
### Installation
```
conda create -n PyTorch python=3.8
conda activate PyTorch
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch-lts
pip install opencv-python==4.5.5.64
pip install tqdm
```
### Note
* The default training configuration is for `mobile_one-s0`
* The test results including accuracy, params and FLOP are obtained by using fused model
### Parameters and FLOPS
```
Number of parameters: 2078504
Time per operator type:
15.0684 ms. 91.0851%. Conv
1.20933 ms. 7.3101%. Relu
0.242441 ms. 1.4655%. FC
0.0117301 ms. 0.0709057%. AveragePool
0.00421935 ms. 0.025505%. Reshape
0.00261659 ms. 0.0158167%. Gather
0.00200163 ms. 0.0120994%. ExpandDims
0.00170158 ms. 0.0102857%. Concat
0.0007769 ms. 0.00469618%. Shape
16.5432 ms in Total
FLOP per operator type:
0.548173 GFLOP. 99.6276%. Conv
0.002049 GFLOP. 0.372395%. FC
0 GFLOP. 0%. Concat
0 GFLOP. 0%. Relu
0.550222 GFLOP in Total
Feature Memory Read per operator type:
19.7686 MB. 50.6551%. Conv
15.1532 MB. 38.8285%. Relu
4.1041 MB. 10.5164%. FC
1.2e-05 MB. 3.07489e-05%. Concat
39.0258 MB in Total
Feature Memory Written per operator type:
15.1532 MB. 49.9934%. Conv
15.1532 MB. 49.9934%. Relu
0.004 MB. 0.0131968%. FC
8e-06 MB. 2.63937e-05%. Concat
30.3103 MB in Total
Parameter Memory per operator type:
4.1801 MB. 50.4837%. Conv
4.1 MB. 49.5163%. FC
0 MB. 0%. Concat
0 MB. 0%. Relu
8.2801 MB in Total
```
### Train
* Configure your `IMAGENET` dataset path in `main.py` for training
* Run `bash main.sh $ --train` for training, `$` is number of GPUs
### Test
* Configure your `IMAGENET` path in `main.py` for testing
* Run `python main.py --test` for testing
### Results
| Version | Epochs | Top-1 Acc | Top-5 Acc | Params (M) | FLOP (G) | Download |
|:--------------:|:------:|----------:|----------:|-----------:|---------:|----------------------------------------------------------------------------------:|
| mobile_one-s0 | 300 | - | - | 2.08 | 0.550 | - |
| mobile_one-s0* | 300 | 71.4 | 89.9 | 2.08 | 0.550 | [model](https://github.com/jahongir7174/MobileOne/releases/download/v0.0.1/s0.pt) |
| mobile_one-s1* | 300 | 75.8 | 92.8 | 4.76 | 1.650 | [model](https://github.com/jahongir7174/MobileOne/releases/download/v0.0.1/s1.pt) |
| mobile_one-s2* | 300 | 77.4 | 93.2 | 7.80 | 2.596 | [model](https://github.com/jahongir7174/MobileOne/releases/download/v0.0.1/s2.pt) |
| mobile_one-s3* | 300 | 77.9 | 93.9 | 10.07 | 3.791 | [model](https://github.com/jahongir7174/MobileOne/releases/download/v0.0.1/s3.pt) |
| mobile_one-s4* | 300 | 79.3 | 94.4 | 14.83 | 5.960 | [model](https://github.com/jahongir7174/MobileOne/releases/download/v0.0.1/s4.pt) |
* `*` means that weights are ported from original repo, see reference
#### Reference
* https://github.com/apple/ml-mobileone