🌅 Should I Go See the Sunset?

Ever stared at the horizon two hours before sunset, wondering if you’ll be blessed by a glorious sky… or just catch smoggy orange mush? Worry no more! This highly scientific, probably overengineered project evaluates sunset potential using images taken at T−2h and T−1h. It predicts—on a 1-5 scale—whether it’s worth dropping everything and sprinting to your nearest west-facing beach.

What Is This?

A PyTorch-based dual-image classifier that consumes sunset images taken 2 hours and 1 hour before sunset, and predicts a sunset "glory score" (1-5).

Yes, it's trained on real data. Yes, there's a GUI. No, we don't guarantee enlightenment, but you might achieve it anyway.

Main Scripts

File	Purpose
create_sunset_model.py	Builds, trains, evaluates, and predicts sunset quality using a model.
order_images.py	Organizes raw images into a structured JSON file for training.
sunset_images_grouped.json	Output file that links image pairs and their manually assigned scores.
img/ob_hotel/	Directory where sunset image files live (not included here).
model/	Folder for saving/loading trained models.

Model Architecture

• Dual ResNet-18 backbones (shared or separate) 🤖
• Processes -2h and -1h images separately → feature concat → classification
• Outputs a score from 1 (💩) to 5 (🔥) based on sunset beauty

GUI Mode (Because Buttons > CLI)

Modes:

• Train
  • Train the model with one click
• Predict
  • Choose two images: one from -2h, one from -1h
  • Press "Predict Score"

🧪 Training

Make sure sunset_images_grouped.json is populated with:

• At least one pair of images for each date (type: "-2h" and "-1h")
• A score between 1 and 5

Training parameters:

• ResNet18 ×2
• 10 epochs
• 64×64 images
• Batch size: 32
• Optimizer: Adam
• Loss: CrossEntropy

🧙 Data Preparation

Run order_images.py to generate/update your training JSON file based on existing .jpg images named like:

25_07_24--18_45_00.jpg

🧙‍♂️ Why?

Fun excuse to play with:

• Paired-image classification
• PyTorch
• PyQt6
• Sunset FOMO

TODO

• Automatically grab data via some google cloud or PA or something
• Host somewhere and have it send a message that the sunset will be fire

License

MIT. Use it freely. Don’t sue if you miss the best sunset of your life.