import cv2
import numpy as np
import os
import shutil

def process_and_replace_assets():
    # Paths to the newly generated artifacts
    # NOTE: In a real scenario, I would validly know these paths. 
    # Since I am an AI, I generated them into specific locations in the previous turn.
    # I will assume they are available in a temporary location or I will use the paths returned by the generation tool.
    
    # Based on previous output:
    # Campfire: .../campfire_simple_1769580346960.png
    # Tent: .../tent_new_color_1769580361961.png
    # Sleeping Bag: .../sleeping_bag_asset_1769580261243.png
    
    # I need to find them or use the strings directly.
    # Let's search for them in the artifacts directory or assume I can access them.
    # For this script to work on the USER's machine, the files must be there.
    # But wait, 'generate_image' saves to the agent's brain artifact folder, which might be accessible via absolute path.
    
    # Let's map the artifact paths (I'll use the filenames from the previous turn logs).
    # Since I cannot magically know the absolute path structure without 'find', I will try to find them in the .gemini artifacts folder.
    
    artifacts_dir = '/Users/davidkotnik/.gemini/antigravity/brain/07019d04-a214-43ab-9565-86f4e8f17e5b'
    
    mapping = {
        'campfire_simple': 'campfire.png',
        'tent_new_color': 'tent.png',
        'sleeping_bag_asset': 'sleeping_bag.png'
    }
    
    # Targets
    target_repo = '/Users/davidkotnik/repos/novafarma/main/assets'
    target_project = '/Users/davidkotnik/nova farma/main/assets'
    
    for key_pattern, dest_name in mapping.items():
        # Find the file in artifacts
        found_path = None
        for f in os.listdir(artifacts_dir):
            if key_pattern in f and f.endswith('.png'):
                found_path = os.path.join(artifacts_dir, f)
                break # Take the first match (most recent usually if unique names)
        
        if not found_path:
            print(f"Error: Could not find generated image for {key_pattern}")
            continue
            
        print(f"Processing {found_path} -> {dest_name}")
        
        img = cv2.imread(found_path, cv2.IMREAD_UNCHANGED)
        
        # 1. Remove Background (Simple Gray/Solid removal)
        # The generated images usually have a solid background (gray or greenish).
        # Best approach: Grab corner color and remove everything similar?
        if img.shape[2] == 3:
            img = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
            
        # Sampling corners
        corners = [img[0,0], img[0, -1], img[-1, 0], img[-1, -1]]
        # Take the most common color (usually bg)
        bg_color = corners[0] # Naive approach
        
        # Tolerance
        tol = 30
        lower = np.clip(bg_color[:3] - tol, 0, 255)
        upper = np.clip(bg_color[:3] + tol, 0, 255)
        
        mask = cv2.inRange(img[:,:,:3], lower, upper)
        # Invert mask: we want to KEEP the foreground
        # Set alpha=0 where mask is true (background)
        img[mask > 0, 3] = 0
        
        # 2. Resize
        # Campfire: 128x128
        # Sleeping Bag: 128x128
        # Tent: 256x256
        target_size = (128, 128)
        if 'tent' in dest_name:
            target_size = (256, 256)
            
        # Resize maintaining aspect ratio? Or just fit?
        # Isometric assets often square-ish. Let's just resize to fit box.
        img = cv2.resize(img, target_size, interpolation=cv2.INTER_AREA)
        
        # Save
        local_dest = os.path.join(target_repo, dest_name)
        cv2.imwrite(local_dest, img)
        print(f"Saved cleaned {dest_name} to {local_dest}")
        
        # Copy to project
        proj_dest = os.path.join(target_project, dest_name)
        shutil.copy2(local_dest, proj_dest)
        print(f"Synced to {proj_dest}")

if __name__ == "__main__":
    process_and_replace_assets()