Awesome

Pipelinex Image Processing

An example project using PipelineX, Kedro, OpenCV, Scikit-image, and TensorFlow/Keras for image processing.

Directories

• conf
  • YAML config files for PipelineX project
• data
  • empty folders (output files will be saved here)
• logs
  • empty folders (log files will be saved here)
• src
  • empty_area.py
    • The algorithm to estimate empty area ratio
  • roi.py
    • Supplementary algorithm to compute ROI (Region of Interest) from segmentation image
  • semantic_segmentation.py
    • Semantic segmentation using PSPNet model pretrained with ADE20K dataset

How to run the code

1. Install Python packages

$ pip install pipelinex opencv-python scikit-image ocrd-fork-pylsd Pillow pandas numpy requests kedro mlflow kedro-viz

Note: mlflow and kedro-viz are optional.

[Optional] To use the pretrained TensorFlow model:

Install tensorflow 1.x and keras-segmentation

$ pip install "tensorflow<2" keras-segmentation Keras 

If you want to use TensorFlow 2.x, install fork of keras-segmentation modified to work with TensorFlow 2.x

$ pip install "tensorflow>=2.0.0" Keras 
$ pip install git+https://github.com/Minyus/image-segmentation-keras.git

2. Clone https://github.com/Minyus/pipelinex_image_processing.git

$ git clone https://github.com/Minyus/pipelinex_image_processing.git
$ cd pipelinex_image_processing

3. Run main.py

$ python main.py

As configured in catalog.yml, the following 2 images will be downloaded by http requests and then processed using opencv-python, scikit-image, and ocrd-fork-pylsd packages.

4. [Optional] View the experiment logs in MLflow's UI

$ mlflow server --host 0.0.0.0 --backend-store-uri sqlite:///mlruns/sqlite.db --default-artifact-root ./mlruns/experiment_001

Tested environment

• Python 3.6.8

Simplified Kedro project template

This project was created from the GitHub template repository at https://github.com/Minyus/pipelinex_template

To use for a new project, fork the template repository and hit Use this template button next to Clone or download.