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detection'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 1.2, torchvision 0.4
  • tensorboard from (tf-nightly-2.0-preview)

How to use

  • load the data

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

./penn_fudan.sh

  • 'demo' (output will be stored in $ROOT$/materials/images)

python demo.py

  • 'train'

run inside folder $ROOT$/src

python train.py --param_file ../experiments/cfgs/penn_train.yaml

  • 'test'

python test.py --param_file ../experiments/cfgs/penn_test.yaml

detection's People

Contributors

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Watchers

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