Forest Fire Prediction

Learning Objectives:

• Apply Intel Extension for PyTorch to convert model and data to xpu
• Apply fine tuning to satellite images to predict fire fires 2 years in advance
• Generate synthetic satellite images using Stable Diffusion
• Optimize a four-stage Stable Diffusion pipeline using Intel(r) Extensions for PyTorch*

First - a No Code approach: Stable Diffusion

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• Run all cells
• When for an image url try: https://github.com/intelsoftware/ForestFirePrediction/blob/main/data/real_USGS_NAIP/train/Fire/m_3912105_sw_10_h_20160713.png?raw=true
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• For text prompt, try: similar aerial photo just translate location

To Access via Intel(R) Developer Cloud:

1. Go to the Intel Developer Cloud by scanning the QR code or by visiting https://cloud.intel.com/

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2. Click “Get Started”
3. Subscribe to the “Standard – Free” service tier and complete your cloud registration.

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4. To start up a free and quick Jupyter notebook session with the latest 4th Gen Intel Xeon CPU and Intel Data Center GPU Max 1100, click the “Training and Workshops” icon and then “Launch JupyterLab”, or one of the specific training materials launches.

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5. Navigate using the Jupyter Hub folder in the left pane and Launch a terminal

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6. Git Clone the repo

• git clone https://github.com/IntelSoftware/ForestFirePrediction.git

7. cd to ForestFirePrediction
8. conda activate pytorch-gpu
9. pip install -r requirements.txt
10. Open and run each Jupyter Notebook in sequence

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