efficientnet-pytorch
A PyTorch implementation of "EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks".
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Download Latest Version (.zip)- publish.yml
- python.yml
- dependabot.yml
- cifar10.yaml
- imagenet.yaml
- mnist.yaml
- __init__.py
- cifar.py
- imagenet.py
- mnist.py
- __init__.py
- efficientnet.py
- __init__.py
- rmsprop.py
- __init__.py
- utils.py
- __init__.py
- metric.py
- trainer.py
- convert.py
- efficientnet_builder.py
- efficientnet_model.py
- eval_ckpt_main.py
- preprocessing.py
- run.sh
- utils.py
- .dockerignore
- .gitignore
- Dockerfile
- efficientnet_test.py
- evaluate.py
- hubconf.py
- LICENSE
- pyproject.toml
- README.md
- train.py
- uv.lock
# Installation Guide
1. Get the code
git clone https://github.com/narumiruna/efficientnet-pytorch
Downloads the entire project code from GitHub to your computer.
cd efficientnet-pytorch
Moves into the project folder you just downloaded.
2. Docker
Easy RecommendedPrerequisites
- Git Needed to download the project code from GitHub.
- Docker Desktop Needed to build and run containers. Install it and keep it running in the background.
docker build -t efficientnet-pytorch .
Builds a runnable image based on the Dockerfile.
docker run -p 8080:80 efficientnet-pytorch
Runs the built image as an actual container.
Run docker compose ps to check the containers are Up. If the README mentions a port, open http://localhost:PORT in your browser.
3. Python
EasyPrerequisites
pip install .
Installs the package published on PyPI directly β no need to clone the source.
python <μ€νν νμΌλͺ
>.py # READMEμμ μ νν μ€ν νμΌλͺ
μ νμΈνμΈμ
Runs the Python script (or module).
If it runs without errors and prints output in the terminal, it worked.
// repository documentation
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