import cv2
import numpy as np
import os

def process_stream_image():
    # 1. Load the stream image
    img = cv2.imread("assets/environment/stream_reference.png", cv2.IMREAD_UNCHANGED)
    
    # If no alpha channel, add one
    if img.shape[2] == 3:
        img = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
    
    # Remove white/black background if present (assuming white based on typical reference images, or do refined masking)
    # The user image "uploaded_media_0" looks like an isometric block. It might have a white background.
    # Simple thresholding for white background removal:
    gray = cv2.cvtColor(img, cv2.COLOR_BGRA2GRAY)
    
    # Create mask for whiteish pixels
    _, mask = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)
    
    # Invert mask (keep non-white)
    mask_inv = cv2.bitwise_not(mask)
    
    # Apply to alpha channel
    # Note: This is a rough removal. Ideally we'd use the provided transparent asset if user gave PNG with alpha.
    # But often users upload screenshots. 
    # Let's check if the corners are white.
    
    # Actually, let's just use the image as is if it has alpha, else remove white.
    # But to be safe for "systematic" placement, let's resize it to a standard tile size or keep it prop-sized.
    # It looks like a big chunk. Let's keep resolution but ensure background is clean.
    
    img[:, :, 3] = cv2.bitwise_and(img[:, :, 3], mask_inv)
    
    # Save as the actual game asset
    cv2.imwrite("assets/environment/potok_segment.png", img)
    print("Stream segment processed and saved.")

def identify_and_remove_ugly_grass():
    # The user wants "the other grass image" removed. 
    # Reference saved at assets/vegetation/ugly_grass_ref.png
    # We don't need to process it, just know that we need to stop using the asset that looks like this.
    # The user said "jo odstrani iz igre".
    # I suspect it matches 'trava_rob.png' or similar. 
    # In the code, I will switch usage of 'trava_rob' to one of the better grasses.
    pass

process_stream_image()