Complete Smart Farm Photo Keyword Tagging AI System - All deliverables ready

2025-07-16 20:24:25 +01:00
parent d0668af517
commit 2134df2635
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+"""
+Smart Farm Photo Keyword Tagging AI - Main Processing Script
+"""
+
+import os
+import sys
+import pandas as pd
+from datetime import datetime
+import argparse
+
+# Add src to path for imports
+sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
+
+from src.data.image_processor import ImageProcessor
+from src.model.keyword_generator import AgricultureKeywordGenerator
+
+def process_agricultural_photos(input_dir: str = "data/raw", output_dir: str = "outputs"):
+    """Main function to process agricultural photos and generate keywords"""
+
+    print("🚜 Smart Farm Photo Keyword Tagging AI")
+    print("=" * 50)
+
+    # Initialize components
+    print("Initializing image processor...")
+    image_processor = ImageProcessor(input_dir)
+
+    print("Initializing AI keyword generator...")
+    keyword_generator = AgricultureKeywordGenerator()
+
+    # Process images
+    print(f"\nProcessing images from: {input_dir}")
+    image_df = image_processor.batch_process_images(input_dir)
+
+    if image_df.empty:
+        print("No images found to process!")
+        return
+
+    print(f"Found {len(image_df)} images to process")
+
+    # Generate keywords for each image
+    results = []
+    for idx, row in image_df.iterrows():
+        if 'error' in row:
+            print(f"Skipping {row['filename']} due to error: {row['error']}")
+            continue
+
+        print(f"Processing {row['filename']}...")
+
+        try:
+            # Generate keywords and title
+            ai_results = keyword_generator.generate_keywords(row['filepath'])
+
+            # Create result row
+            result = {
+                'filename': row['filename'],
+                'human_keywords': '',  # Placeholder for human keywords
+                'ai_keywords': ', '.join(ai_results['keywords']),
+                'ai_title': ai_results['title'],
+                'location': row.get('location', ''),
+                'caption': ai_results['caption']
+            }
+
+            results.append(result)
+            print(f"  ✓ Generated {len(ai_results['keywords'])} keywords")
+
+        except Exception as e:
+            print(f"  ✗ Error processing {row['filename']}: {e}")
+            continue
+
+    # Create output DataFrame
+    results_df = pd.DataFrame(results)
+
+    # Save to CSV
+    os.makedirs(output_dir, exist_ok=True)
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    output_file = os.path.join(output_dir, f"agricultural_keywords_{timestamp}.csv")
+
+    results_df.to_csv(output_file, index=False)
+
+    print(f"\n✅ Processing complete!")
+    print(f"Results saved to: {output_file}")
+    print(f"Processed {len(results_df)} images successfully")
+
+    # Display sample results
+    print("\n📊 Sample Results:")
+    print("-" * 80)
+    for idx, row in results_df.head(3).iterrows():
+        print(f"File: {row['filename']}")
+        print(f"Title: {row['ai_title']}")
+        print(f"Keywords: {row['ai_keywords']}")
+        print(f"Location: {row['location'] if row['location'] else 'Not available'}")
+        print("-" * 80)
+
+    return output_file
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description='Process agricultural photos for keyword tagging')
+    parser.add_argument('--input', '-i', default='data/raw', help='Input directory with images')
+    parser.add_argument('--output', '-o', default='outputs', help='Output directory for results')
+
+    args = parser.parse_args()
+
+    try:
+        output_file = process_agricultural_photos(args.input, args.output)
+        print(f"\n🎉 Success! Check your results in: {output_file}")
+    except Exception as e:
+        print(f"\n❌ Error: {e}")
+        sys.exit(1)