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TensorFlow CNN tools to build and evaluate image segmentation and classification models.

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Tensorflow CNN/FCNN architectures

Code to prepare datasets and do model training and evaluation, in the scope of this research project:

Deep-Learning Image Segmentation - Towards Tea Leaves Harvesting by Automomous Machine

Prerequisites

  • Python 3.x
  • Tensorflow >=1.8 (tested with 1.8 and 1.9)

How to run

python3 src/run.py

or by calling predefined tasks in root directory.

Apps

  • bake: create tf-record dataset from picture/mask/weight images
  • preview: read and display content of a tf-record dataset
  • train: train a single model with given parameters
  • trainmulti: train multiple models
  • eval: evaluate a model
  • predict: report and display model performance on unseen data

Topologies

Example of model topologies in YAML format are located in topologies sub-folder.

Bake/training configuration

Example of bake and training parameters for single and multiple session are located in config sub-folder.

license

GPLv3

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TensorFlow CNN tools to build and evaluate image segmentation and classification models.

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