Data

Tools

Indexes

Applications

Experiments

Open Source Science

https://github.com/cjing00923/estimating_the_number_of_sunspots

https://github.com/cjing00923/estimating_the_number_of_sunspots

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (7.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: cjing00923
  • Language: Python
  • Default Branch: master
  • Size: 5.02 MB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 1 year ago · Last pushed 11 months ago
Metadata Files
Readme

README.md

Sunspot Segmentation and Analysis Pipeline This project provides an automated pipeline for sunspot image analysis, including segmentation, umbra and penumbra separation, sunspot group detection, and butterfly diagram generation.

Project Structure and Functionality 1. Sunspot Segmentation Model Training and Inference UNetslicetrain.py Trains a U-Net model for semantic segmentation of sunspots from solar disk images.

predict_all.py Applies the trained U-Net model to segment sunspots in input images.

  1. Umbra and Penumbra Separation (UmbraandPenumbra folder) peak_all.py Detects intensity peaks in each segmented sunspot region to determine the presence of a penumbra.

k_all.py Applies KMeans clustering to sunspots with penumbrae to separate the umbra and penumbra regions, enabling single sunspot counting.

  1. Sunspot Group Detection Sunspot group detection is performed using a YOLOv5 model. The detection code is available at: cjing00923-sunspotgroupdetection_yolov5

  2. Butterfly Diagram Generation (Butterfly folder) find_box.py Extracts the bounding box coordinates of each sunspot group detected by YOLO.

box_erzhi.py Converts the detected bounding boxes into binary mask images.

mask.py Overlays the YOLO-detected binary masks onto the U-Net segmented sunspot results to obtain detailed contours of each sunspot group.

area.py Calculates the area of each sunspot group.

latitude_box.py Computes the latitude of each sunspot group.

merge.py Merges area and heliographic latitude/longitude information into a single output file.

draw.py Draws the sunspot butterfly diagram based on the area and latitude/longitude data of each sunspot group.

Usage Guide Train the sunspot segmentation model using UNetslicetrain.py.

Segment sunspots on solar images using predict_all.py.

In the UmbraandPenumbra/ folder, run peakall.py and kall.py to separate umbra and penumbra.

Detect sunspot groups using the YOLO model from the sunspot group detection repository.

In the Butterfly/ folder, run the following scripts sequentially to analyze sunspot groups and generate the butterfly diagram:

find_box.py

box_erzhi.py

mask.py

area.py

latitude_box.py

merge.py

draw.py

Owner

  • Login: cjing00923
  • Kind: user

GitHub Events

Total
  • Push event: 3
  • Create event: 2
Last Year
  • Push event: 3
  • Create event: 2