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Automatic Detection and Classification of Rock Microstructures through Machine Learning

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Made withJupyter made-with-python commit activity repo size Binder

This project participates the 2021 Earth Cube Annual Meeting

Please see the abstract here.

Current progress

Models:
Transfer leaning model
YOLO model

Visualization:
Automatic Detection and Classification of Rock Microstructures through Machine Learning

All of the models and visualization are in notebooks folders. Please see the instruction below to use.

Usage

We provide requirements.txt for usage together with Binder, as well as exact replica of conda environment in env.yml

git clone https://github.com/drizzle98/sigma-clast-project

Go to your cloned directory

cd ../github/sigma-clast-project

Install the required packages Using pip:

pip install -r requirements.txt

Using conda:

conda env create -f env.yml
conda activate microstructures

Go to notebook folder:

cd notebooks

Run Jupyter lab:

jupyter lab

For YOLO model specifically, please also download the support material inside the folder YOLO_support_materials.

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