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trashcan's Introduction

Оптимизация работы коммунальных служб 🗑️

Настройка окружения

pip install -r requirements.txt
pip install -e .

Запуск обучения

python trash/train.py

Конвертация в onnx

python trash/torch2onnx.py

Запуск фронта

python trash/webapp.py

Запуск фронта через докер

docker-compose up --build

Зайти на localhost:8989

Завершить работу

docker-compose down

Структура проекта

├── checkpoints
│   ├── 256_resnet50.onnx
│   └── 256_resnet50.pt
├── data
│   ├── sample_solution.csv
│   ├── test
│   ├── train
│   ├── train.csv
│   ├── Условие_задачи_Чемпионат_Республика_Башкортостан.pdf
│   └── Уфа_baseline.ipynb
├── docker-compose.yml
├── Dockerfile
├── LICENSE
├── README.md
├── requirements.txt
├── setup.py
└── trash
    ├── configs
    ├── dataset.py
    ├── engine.py
    ├── predict.py
    ├── torch2onnx.py
    ├── train.py
    └── webapp.py

С чем можно поэкспериментировать

  • В конфиге поменять модель на одну из моделей в бибилиотеке timm
  • Размеры изображения 256, 384, 512
  • Оптимайзер, шедьюлер, лернинг рейт

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