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classification's Introduction

Structure of the repo:

  • data

    Datasets and all data-related stuff is here (could be symbolic link to the real data location)

  • experiments

    Folder contains

    • [cfgs] param (config) files for experiments;
    • [logs] all intermediate results from different experiments (param files, checkpoints, logs, ...);
    • [scripts] scripts to run specific experiments;
  • notebooks

    Place for jupyter notebooks. Notebooks could contain some analysis (dataset analysis, evalution results), demo, some ongoing work

  • material

    Data, which include additional images, results, model weights, ...

    • [results] useful results are stored here;
    • [images] images for demo, readme, ...;
    • [weights] weights of the models (e.g. pretrained backbones )
  • src

    Codebase.

Requirements

Tested with

  • python 3.6
  • pytorch 1.1+
  • tensorboard from (tf-nightly-2.0-preview)

How to use

  • load the data

(cifar10) go to the folder 'data' and run [YOU NEED ~ 300 MB]

./get_cifar10_dataset.sh

(dtd) go to the folder 'data' and run

./get_cifar10_dataset.sh

  • 'train'

Run from the $PROJECT$ directory:

(cifar)

python src/main_train.py --param_file experiments/cfgs/params_cifar10.yaml

(dtd)

python src/main_train.py --param_file experiments/cfgs/params_dtd.yaml

classification's People

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