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https://github.com/casperfibaek/garbage-in-out

https://github.com/casperfibaek/garbage-in-out

Science Score: 13.0%

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Repository

Basic Info
  • Host: GitHub
  • Owner: casperfibaek
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 2.93 KB
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Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

garbage-in-out

Garbage-In-Out Logo 🚀 **Turn Your Trash into Algorithmic Gold!** 🚀

🗑️ Garbage in - treasure out?

Welcome to the cutting-edge frontier of waste prediction! This revolutionary repository harnesses the power of neural networks to transform mundane waste data into precious insights. Like an alchemist of the digital age, our models transmute raw garbage metrics into golden predictions!

🤖 What's Inside This Treasure Chest?

This repository houses two sophisticated neural network models that predict recycling facility outputs: 1. The Total Oracle: Predicts the total output of useable materials 2. The Content Prophet: Forecasts the precise composition of output materials

🛠️ Magical Dependencies

  • 🔢 Numpy - For numerical sorcery
  • 🔥 Pytorch - Our neural enchantment engine
  • 📊 Seaborn - To visualize the transformation

Example

```python

Example usage - Total output prediction

from inference import predictoutput, createinput_tensor

input_ids = [ 11, # Old iron 656, # Old iron with impurities ]

input_amounts = [ 1435, # kg 2390, # kg ]

inputvector = createinputtensor(inputids, inputamounts) result = predictoutput(input_vector)

print(f"Predicted total output: {result[1]:.2f} tons of {result[0]:.2f}")

"Predicted total output: 3.825 tons of shredder material" ```

💻 Sleek Interface

Check out our intuitive interface that makes waste prediction a breeze! With simple input fields and real-time updates, you'll be analyzing waste patterns like a pro.

bash python app.py

Navigate to 'localhost:8080' and see the glory!

Interface Example

🔧 Installation

  1. Clone this repository bash git clone https://github.com/casperfibaek/garbage-in-out.git cd garbage-in-out

  2. Create and activate the environment bash conda env update -n garbage --file environment.yml conda activate garbage

  3. Verify installation bash python -c "import torch; print(torch.__version__)"

Owner

  • Name: cGeom
  • Login: casperfibaek
  • Kind: user

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