Pretrained model that can be used to classify objects from squirrels up to military planes. Full list of classes: https://image-net.org/challenges/LSVRC/2014/browse-synsets
├── README.md <- The top-level README for developers using this project.
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├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
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├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
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├── Animals_classification_VGG16 <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
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│ ├── data <- Scripts to handle data
│ │ └── extract_dataset.py <- Unzips dataset
│ │ └── get_images.py <- Gets list of all .jpeg, .jpg or .png files in dir
│ │ └── parse_data.py <- Data parser
│ │ └── split_folders.py <- Splits data into training and validation dirs
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│ ├── features <- Scripts to turn raw data into features for modeling
│ │ └── handle_input.py <- Used to choose between training and loading model
│ │ └── image_folder.py <- Custom ImageFolder class for data validation
│ │ └── predict_custom_image.py <- Used to validate model on a custom data
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│ ├── model <- Scripts to train/load/save model
│ │ │── create_model.py <- Initialize new model
│ │ ├── load_model.py <- Load existing weights to the model
│ │ └── save_model.py <- Save trained model's weights to file
│ │ └── training.py <- Training pipeline
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└── tox.ini <- tox file with settings for running tox
Project based on the cookiecutter data science project template. #cookiecutterdatascience