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README.md

@@ -10,16 +10,51 @@ pinned: false
 license: ecl-2.0
 ---
 
-# YOLOv5 Sunspot Hunter
+# YOLOv5 Sunspot Hunter 🌟
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Explore the dynamic solar surface with the YOLOv5 Sunspot Hunter! This application is designed to detect and analyze sunspots using state-of-the-art object detection technology.
 
-## Desenvolvedor
+## Developer
 
-Desenvolvido por Ramon Mayor Martins (2023)
+Developed by Ramon Mayor Martins (2023)
 
 - Email: [rmayormartins@gmail.com](mailto:rmayormartins@gmail.com)
 - Homepage: [https://rmayormartins.github.io/](https://rmayormartins.github.io/)
 - Twitter: [@rmayormartins](https://twitter.com/rmayormartins)
 - GitHub: [https://github.com/rmayormartins](https://github.com/rmayormartins)
+- my Radio Callsign (PU4MAY) Brazil
+
+## About the Project
+
+This tool using YOLOv5, an advanced neural network, for the detection and classification (hunting) of sunspots. The sunspot images were collected from several high-quality sources, including the SOHO satellite, and other NASA and ESA archives, under Creative Commons licenses. These images were then annotated with precision using Makesense.ai.
+
+## Key Features
+
+- **Image Source:** The sunspot images were sourced from SOHO satellite, NASA, and ESA archives.
+- **Labeling:** Annotations were done using Makesense.ai.
+- **Model Training:** The model was trained with YOLOv5, achieving satisfactory metrics including mAP (mean Average Precision).
+- **Model File:** The 'best.pt' file is used, which represents the model's optimal state after training.
+
+## How to Use
+
+- **Launch:** Start the YOLOv5 Sunspot Hunter by running the `app.py` script in Gradio.
+- **Image Upload:** Users can upload their own images of the sun or utilize current solar images from websites like [Space Weather Live](https://www.spaceweatherlive.com/en/solar-activity.html), [LMSAL](https://www.lmsal.com/solarsoft/latest_events/), [SOHO Realtime Images](https://soho.nascom.nasa.gov/data/realtime-images.html), and [The Sun Today](https://www.thesuntoday.org/sun/current-observations/).
+- **Detection:** The tool processes the uploaded image, identifying and highlighting sunspots with high precision.
+- **Results:** View the results instantly, with sunspots clearly marked and classified.
+
+## Feedback and Contributions
+
+Feel free to reach out or contribute to the project. Your feedback and contributions are highly appreciated!
+
+## License
+
+This project is released under the ECL-2.0 license.
+
+## Acknowledgments
+
+Special thanks to the teams at NASA, ESA, and SOHO for providing valuable solar data.
+
+---
+*Check out the configuration reference at [Hugging Face Spaces Config Reference](https://huggingface.co/docs/hub/spaces-config-reference).*
+
 

app.py

@@ -40,7 +40,7 @@ iface = gr.Interface(
     outputs=gr.Image(type="pil"),
     title="YOLOv5 Sun Spot Hunter",
     description="Object detector (solar spot/sunspot hunter) trained using YOLOv5 and labeled in Makesense.ai",
-    examples=[["example1.jpg"]]  
+    examples=[["example1.jpg"], ["example2.jpg"]]  
 )