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License: CC BY-NC 4.0

PhotoVoltaicPanelDetection

This repository contains solution for automatic detection of solar modules. Main aim was to prepare a tool that can be configured and based on that configuration produce detected modules in to be defined formats, commonly used in machine learning but not only.

Running in docker container

Build Docker Image from source

docker build -t pvpd:0.0.1 -t pvpd  .

Try running:

docker run pvpd:0.1.0 -h 

Example run from docker

docker run -v ${PWD}/data:/usr/data pvpd:0.1.0  -c PlasmaConfig -o /usr/data --f /usr/data/raw/3.JPG -t raw -cm plasma -l LabelMeLabeler 
  • -v ${PWD}/data:/usr/data shares directory data from repository to /usr/data
  • pvpd:0.1.0 version of docker image
  • -c PlasmaConfig which config will be used for image annotation
  • -o /usr/data/ data will be saved in the shared directory data
  • -f /usr/data/plasma/1.JPG file 1.JPG is going to be analyzing
  • -t raw file 1.JPG is in a raw format. There is a need to extract thermal information
  • -cm plasma which color map will be used for thermal image values

Local installation

Prerequisites

  • Required Python > 3.7. Check python version
python --version
  • For extraction exif data (thermal data) from raw images: exiftool

Installation

Install the needed python packages commands below:

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

First run

./detector_cli.py

Configs

Configs are parts of this project that every user adjust for private images. All config can be found those in config directory. Using them requires some knowledge about classic image processing methods.

Whole detection is split into distinct steps that could be configured using each step Param. It is highly suggested taking a look at those.

For now available Configs can be found using ./detector_cli.py -h

Labelers

Labeler is an entity that can be selected to generate a file containing data and metadata from detection process. New labelers can be easily created to meet individual needs. All labelers can be found in labelers directory

For now available Labelers can be found using ./detector_cli.py -h

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