https://github.com/baophann/phone_advance
Science Score: 26.0%
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○Scientific vocabulary similarity
Low similarity (6.0%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: BaophanN
- License: mit
- Language: Python
- Default Branch: main
- Size: 44.9 KB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Quantized Distillation for Driver Activity Recognition
This is the official PyTorch implementation of our IROS 2023 paper:
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments
Setup
Add folder called model in the same directory as above code to save trained checkpoints. Before training, the folder structure should look like this
├── [path to your cloned repository]
├── architecture
├── config
├── framework_activity_recognition
├── model # add this
├── LICENSE
├── README.md
└── requirement.txt
Do not forget to install the requirement stated in the folder.
Dataset
Pretrained Model
Training
To train baseline RGB I3D model on Drive&Act, use the following command
python -m framework_activity_recognition config/train/i3dbaseline.yaml
To train other baseline or using knowledge distillation and/or quantization on Drive&Act, replace the yaml file in the command to one of the following yaml file in config/train folder
├── ./config
├── /train
├── i3dbaseline.yaml # RGB I3D baseline on Drive&Act
├── mobilenet_quant.yaml # MobileNet3D with PyTorch quantization on Drive&Act
├── mobilenetbaseline.yaml # MobileNet3D baseline on Drive&Act
├── studentteacher.yaml # MobileNet3D on Drive&Act with knowledge distillation from teacher RGB I3D
└── studentteacher_quant.yaml # MobileNet3D with PyTorch quantization and knowledge distillation from teacher RGB I3D on Drive&Act
Test
To test RGB I3D Model with test split of Drive&Act, use the following command
python -m framework_activity_recognition config/test/i3dtest.yaml
To test another model, replace the yaml file in the command with one of the following yaml file in config/test folder
├── ./config
├── /test
├── i3dtest.yaml # RGB I3D test on Drive&Act test split
├── mobilenetquanttest.yaml # MobileNet3D with PyTorch quantization test on Drive&Act test split
└── mobilenettest.yaml # MobileNet3D test on Drive&Act test split
Owner
- Name: Bao Phan
- Login: BaophanN
- Kind: user
- Repositories: 1
- Profile: https://github.com/BaophanN
Where there's a will, there's a way.
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- Push event: 4
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Dependencies
- Markdown ==3.3.6
- Pillow ==8.4.0
- PyYAML ==6.0
- Werkzeug ==2.0.3
- absl-py ==1.0.0
- cachetools ==4.2.4
- certifi ==2021.10.8
- charset-normalizer ==2.0.12
- dataclasses ==0.6
- google-auth ==2.6.0
- google-auth-oauthlib ==0.4.6
- grpcio ==1.43.0
- idna ==3.3
- imageio ==2.15.0
- importlib-metadata ==4.8.3
- numpy ==1.19.5
- oauthlib ==3.2.0
- opencv-python ==4.5.5.62
- pandas ==1.1.5
- protobuf ==3.19.4
- pyasn1 ==0.4.8
- pyasn1-modules ==0.2.8
- python-dateutil ==2.8.2
- pytz ==2021.3
- requests ==2.27.1
- requests-oauthlib ==1.3.1
- rsa ==4.8
- scipy ==1.5.4
- six ==1.16.0
- sk-video ==1.1.10
- tensorboard ==2.8.0
- tensorboard-data-server ==0.6.1
- tensorboard-plugin-wit ==1.8.1
- torch ==1.10.2
- torchaudio ==0.10.2
- torchvision ==0.11.3
- typing_extensions ==4.1.0
- urllib3 ==1.26.8
- zipp ==3.6.0