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#!/bin/bash
# Simple ConvNeXt training script for flower classification
# This script provides an easy way to train a flower classification model
echo "🌸 Flowerfy Simple Training Script"
echo "=================================="
# Check if training data exists
if [ ! -d "training_data/images" ]; then
echo "❌ Training data directory not found!"
echo "Please create 'training_data/images/' and organize your images by flower type."
echo ""
echo "Example structure:"
echo " training_data/images/roses/"
echo " training_data/images/tulips/"
echo " training_data/images/lilies/"
echo " training_data/images/orchids/"
exit 1
fi
# Count training images
total_images=0
echo "Found flower types:"
for dir in training_data/images/*/; do
if [ -d "$dir" ]; then
flower_type=$(basename "$dir")
count=$(find "$dir" -type f \( -iname "*.jpg" -o -iname "*.jpeg" -o -iname "*.png" -o -iname "*.webp" \) | wc -l)
if [ "$count" -gt 0 ]; then
echo " - $flower_type: $count images"
total_images=$((total_images + count))
fi
fi
done
if [ "$total_images" -lt 10 ]; then
echo "❌ Insufficient training data. Found $total_images images."
echo "You need at least 10 images to train the model."
exit 1
fi
echo ""
echo "Total images: $total_images"
echo ""
echo "Training Configuration:"
echo " - Method: Simple training (fast, lightweight)"
echo " - Epochs: 3 (default)"
echo " - Batch size: 4 (default)"
echo " - Learning rate: 1e-5 (default)"
echo ""
echo "Starting training..."
echo ""
# Run the training
cd training
uv run python simple_trainer.py "$@"
echo ""
echo "Training completed! Check the output above for results."
echo "Your trained model will be in: training_data/trained_models/simple_trained/"
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