semvec/pypi-packages huggingface dataset:
catnet-RedCatTeam 1.0.2
A package for simple machine learning (AI)
Requires Python: >=3.10

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#                                             This is package for simple machine learning                                                                                #
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# Example 1:                                                                                                                                                             #
# import catnet                                                                                                                                                          #
# import numpy as np                                                                                                                                                     #
# model=catnet.Model()                                                                                                                                                   #
# model.add(catnet.layers.MRELU(16))                                                                                                                                     #
# x = np.array([[1],[2]])  # Inputs (all in [])                                                                                                                          #
# y = np.array([[2],[3]])  # Outputs (all in [])                                                                                                                         #
# model.train(np.array([[1],[2]]),np.array([[2],[3]]),True,optim=catnet.optimize.Adam(0.01), loss=losses.MSE(),epochs=500,logging=True) # Disable logging for Python IDLE#
# answer=0                                                                                                                                                               #
# for pred in model(np.array([[1]])):                                                                                                                                    #
# 	 answer=pred[0]                                                                                                                                                      #
# print(answer)                                                                                                                                                          #
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opengis 3.1.6
An open source GIS tool.
Requires Python: >=3.9

# Open Source GIS Tool

Welcome to our **Open-Source GIS Tool**!  
This project aims to simplify and streamline **geospatial data processing** and **remote sensing analysis**, offering a practical, efficient, and user-friendly solution for researchers, analysts, and GIS enthusiasts.

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## 🌟 Features

### 1. **Batch MODIS Data Processing**
- Automate the handling of **MODIS satellite data** for large datasets.  
- Ideal for researchers needing consistent and efficient workflows when working with MODIS products.

### 2. **Batch Reprojection**
- Quickly reproject multiple geospatial datasets into different coordinate systems.  
- Ensure spatial consistency or prepare data for region-specific analysis.

### 3. **Batch Mosaic**
- Merge multiple remote sensing images into seamless mosaics.  
- Perfect for creating larger, unified datasets from smaller tiles.

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## 🚀 Future Plans

We're dedicated to expanding this tool's functionality. Upcoming features might include:  
- Advanced geospatial analysis tools  
- Support for additional satellite data formats  
- Interactive visualization capabilities  

Stay tuned for regular updates and improvements!

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## 🤝 Contributing

We warmly welcome contributions from the community! Whether it's new feature ideas, improvements, or bug fixes, here's how you can get involved:  
1. Fork the repository  
2. Make your changes  
3. Submit a pull request  

You can also open issues to suggest enhancements or report bugs. Let's build this tool together!

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## 📜 License

This project is licensed under the **MIT License**, allowing you to use, modify, and distribute it freely.

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Thank you for choosing our GIS tool!  
We hope it enhances your geospatial data processing workflows and makes your tasks more efficient.  

Feel free to reach out with feedback or suggestions. 🌍