#!/usr/bin/env python3
"""
Script to test the Marine Species API and save annotated images for viewing.
"""

import requests
import base64
import json
import time
from pathlib import Path
import sys
from PIL import Image
import io


def encode_image_to_base64(image_path: str) -> str:
    """Encode an image file to base64 string."""
    try:
        with open(image_path, "rb") as image_file:
            return base64.b64encode(image_file.read()).decode('utf-8')
    except Exception as e:
        print(f"Error encoding image {image_path}: {e}")
        return None


def save_base64_image(base64_string: str, output_path: str) -> bool:
    """Save a base64 encoded image to a file."""
    try:
        # Decode base64 to bytes
        image_bytes = base64.b64decode(base64_string)
        
        # Open with PIL and save
        image = Image.open(io.BytesIO(image_bytes))
        image.save(output_path)
        
        print(f"✅ Saved annotated image: {output_path}")
        return True
        
    except Exception as e:
        print(f"❌ Failed to save image: {e}")
        return False


def test_and_save_annotated_image(api_url: str, image_path: str, output_dir: str):
    """Test API with an image and save the annotated result."""
    
    image_name = Path(image_path).stem
    print(f"\n🐟 Processing {Path(image_path).name}")
    print("-" * 50)
    
    # Encode input image
    print("📷 Encoding image...")
    image_b64 = encode_image_to_base64(image_path)
    if not image_b64:
        return False
    
    # Prepare API request
    detection_request = {
        "image": image_b64,
        "confidence_threshold": 0.25,
        "iou_threshold": 0.45,
        "image_size": 640,
        "return_annotated_image": True
    }
    
    try:
        print("🔍 Sending detection request...")
        start_time = time.time()
        
        response = requests.post(
            f"{api_url}/api/v1/detect",
            json=detection_request,
            timeout=60
        )
        
        request_time = time.time() - start_time
        print(f"⏱️  Request completed in {request_time:.2f}s")
        
        if response.status_code == 200:
            result = response.json()
            
            detections = result.get('detections', [])
            processing_time = result.get('processing_time', 0)
            annotated_image_b64 = result.get('annotated_image')
            
            print(f"✅ SUCCESS!")
            print(f"   Processing Time: {processing_time:.3f}s")
            print(f"   Detections Found: {len(detections)}")
            
            # Show top detections
            if detections:
                print(f"   🎯 Top Detections:")
                for i, detection in enumerate(detections[:3]):
                    species = detection.get('class_name', 'Unknown')
                    confidence = detection.get('confidence', 0)
                    print(f"      {i+1}. {species} (confidence: {confidence:.3f})")
            
            # Save annotated image
            if annotated_image_b64:
                output_path = Path(output_dir) / f"{image_name}_annotated.jpg"
                success = save_base64_image(annotated_image_b64, str(output_path))
                
                if success:
                    print(f"   🖼️  View annotated image: {output_path}")
                    return str(output_path)
            else:
                print("   ❌ No annotated image returned")
                
        else:
            print(f"❌ Request failed with status {response.status_code}")
            print(f"   Response: {response.text}")
            
    except Exception as e:
        print(f"❌ Request failed: {e}")
    
    return None


def main():
    """Main function."""
    # API URL
    api_url = sys.argv[1] if len(sys.argv) > 1 else "https://seamo-ai-fishapi.hf.space"
    
    print("🐟 Marine Species API - Annotated Image Viewer")
    print("=" * 60)
    print(f"API URL: {api_url}")
    
    # Create output directory
    output_dir = Path("annotated_results")
    output_dir.mkdir(exist_ok=True)
    print(f"Output directory: {output_dir.absolute()}")
    
    # Find test images
    image_dir = Path("docs/gradio/images")
    if not image_dir.exists():
        print(f"\n❌ Image directory not found: {image_dir}")
        return
    
    # Get image files
    image_files = []
    for ext in ['*.png', '*.jpg', '*.jpeg']:
        image_files.extend(image_dir.glob(ext))
    
    if not image_files:
        print(f"\n❌ No image files found in {image_dir}")
        return
    
    print(f"\n📁 Found {len(image_files)} test images")
    
    # Process each image
    saved_images = []
    for image_path in sorted(image_files):
        result_path = test_and_save_annotated_image(api_url, str(image_path), str(output_dir))
        if result_path:
            saved_images.append(result_path)
        time.sleep(1)  # Small delay between requests
    
    # Summary
    print("\n" + "=" * 60)
    print(f"🎯 Summary:")
    print(f"   Processed: {len(image_files)} images")
    print(f"   Saved: {len(saved_images)} annotated images")
    
    if saved_images:
        print(f"\n🖼️  Annotated images saved to:")
        for img_path in saved_images:
            print(f"   - {img_path}")
        
        print(f"\n💡 To view the images:")
        print(f"   - Open the files in any image viewer")
        print(f"   - Or run: open {output_dir}")  # macOS
        print(f"   - Or run: xdg-open {output_dir}")  # Linux
        print(f"   - Or navigate to: {output_dir.absolute()}")


if __name__ == "__main__":
    main()