🍎 Fruit Classifier

Custom CNN trained from scratch in PyTorch to classify 10 fruits from images. Achieves 61.3% validation accuracy on just 230 training images.

Usage

from predict import load_model, predict

model = load_model("fc_model_weights.pth")
fruit_name, confidence = predict(model, "your_image.jpg")
print(f"Predicted: {fruit_name} ({(100*confidence):>0.1f}%)")

Supported Fruits

Apple, Banana, Avocado, Cherry, Kiwi, Mango, Orange, Pineapple, Strawberries, Watermelon

Files

  • fc_model.pth β€” full model for inference
  • fc_model_weights.pth β€” weights for resuming training
  • fruit_benefits.json β€” nutritional knowledge base
  • predict.py β€” inference utility

Full Project

Training pipeline and RAG workflow available on GitHub: GitHub Repository

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