CNN for semantic and instance segmentation of leaves
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CNN
shells
License.txt
README.md

README.md

Learning to count leaves

Torch7 code for training a CNN for semantic and instance segmentation of leaves.

Directory structure

Directory Content
CNN Core CNN code
data Training data
shells various bash shells

Dependencies

install dependencies

> shells/dependencies.sh

Data

We used Plant Phenotyping DataSet for training. See Plant-phenotyping and how it was collected. Download the dataset and copy to

> $ROOT/data

see dataset CLI argument for adjusting the path to desired location.

Training

See opts.lua for CLI options.

> th -i main.lua

To start anew:

> rm -rf $ROOT/CNN/results/
> rm $ROOT/data/NLL_trainData.t7 and/or rm $ROOT/data/BCE_trainData.t7
> th main.lua

To generate data only:

> rm -rf $ROOT/CNN/results/
> rm $ROOT/data/NLL_trainData.t7 and/or rm $ROOT/data/BCE_trainData.t7
> th main.lua -genDataOnly

To see datasets:

> rm -rf $ROOT/CNN/results/
> rm $ROOT/data/NLL_trainData.t7 and/or rm $ROOT/data/BCE_trainData.t7
> qlua main.lua 

Inference

See inference.lua for CLI options.

> th -i inference.lua

Related (CNN-based) Efforts

TODO

  • patch-based
  • post process with CRF