This repository contains the code for a master's degree final project.

https://costa-rica-solar.uc.r.appspot.com

Optimized for screens of 1920x1080

Artificial Intelligence/ Full Stack Development.

• Web client: React, Typescript
• Model: Python, Pytorch.

Each folder contains instructions on how to execute the different pieces, since it's a full stack/machine learning combination there will be different steps required.

Main requisites will include a running version of Python and Node JS in your system.

Important! The API KEY's that appeagitr only works under an specific DNS. The website might not work fully unless a new API KEY is in place.

Includes classification dataset images, which contains solar panel and non solar panel satellite images.

Include model dictionaries, for both segmentation and classification inference capabilities.

https://drive.google.com/drive/folders/16zNzQDGhA06nSWuwwILTtzgOZ95DNBYA?usp=share_link

@misc{carlosan1708:2023,
  Author = {Carlos Rodriguez Trigueros},
  Title = {Costa Rica, Solar Panel Detector},
  Year = {2023},
  Publisher = {GitHub},
  Journal = {GitHub repository},
  Howpublished = {\url{https://github.com/carlosan1708/MasterTFM}}
}

Dr. Carlos Gaitan Poyatos.

Pavel Iakubovskii, Segmentation Models, (2019), Github Repository https://github.com/qubvel/segmentation_models

Takumi Karasawa, PyTorch Image Classification, (2022), Github Repository https://github.com/karasawatakumi/pytorch-image-classification

The code is provided as it is. It may work in your computer, it may not work. It may even crash it or create a paradox that could ultimately unravel the very fabric of the space-time continuum and destroy the entire universe. Just be careful and try to understand everything before using it. If you have questions, please carefully read the code. If this doesn't help, contact us. If you want to blame us for some reason, do not contact us.