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A personal reimplementation of NowcastNet inference framework

Project description

Introduction

This project is a personal reimplementation of the NowcastNet inference framework. The original research, titled "Skilful nowcasting of extreme precipitation with NowcastNet," by Yuchen Zhang, Mingsheng Long et al., was published in Nature and can be accessed at https://www.nature.com/articles/s41586-023-06184-4. Additionally, the original code by Yuchen Zhang is available at https://doi.org/10.24433/CO.0832447.v1.

Getting Started

Begin by cloning the repository:

git clone https://github.com/VioletsOleander/nowcastnet-rewritten.git

Next, setup the environment:

conda create -n nowcastnet
conda activate nowcastnet
pip install -r requirements.txt

You may need to implementated your own code to read the dataset. Sample Code for reading the radar dataset is provided in the datasets directory.

To ensure compatibility with this reimplementation's architecture, weights have been modified by me and are available for downloading from Hugging Face.

Usage

To start inference, run inference.py with required arguments. To get an overview of the arguments, start with the basic command:

python inference.py -h

Here is an example shell script do_inference.sh to streamline the process. You can adjust it accordingly:

#!/bin/bash
python inference.py \
    --case_type normal \
    --device cuda:0 \
    "path_to_weights" \
    "path_to_data" \
    "path_to_result" \

Ensure that do_inference.sh has executable premissions:

chmod +x do_inference.sh

Then run the script using:

./do_inference.sh

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