import cv2
import numpy as np
import os

def clean_pipe_stream_gentle():
    src_path = '/Users/davidkotnik/.gemini/antigravity/brain/07019d04-a214-43ab-9565-86f4e8f17e5b/uploaded_media_1769607894587.jpg'
    
    print(f"Loading {src_path}")
    img = cv2.imread(src_path)
    if img is None: return

    # 1. Standard Separation (GrabCut) - keeps everything (Pipe, Stream, Walls, Banks)
    mask = np.zeros(img.shape[:2], np.uint8)
    bgdModel = np.zeros((1,65),np.float64)
    fgdModel = np.zeros((1,65),np.float64)
    h, w = img.shape[:2]
    cv2.grabCut(img, mask, (10, 10, w-20, h-20), bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)
    mask_final = np.where((mask==2)|(mask==0),0,1).astype('uint8') 
    
    # Not doing any aggressive "Wall Removal" logic now, because it ate the banks.
    # Instead, we rely on the fact that GrabCut should just remove the GRAY background.
    # The walls will remain. To fit them better, we can manually crop the BOTTOM few pixels if needed.
    
    # 2. Fix Drain Hole (Make Black if it's transparent)
    # Actually, let's just make the hole Area Opaque regardless.
    # Assuming drain is separate dark region? No, it's connected.
    # Let's clean up small holes in the mask so the drain grate isn't see-through.
    kernel = np.ones((5,5),np.uint8)
    mask_final = cv2.morphologyEx(mask_final, cv2.MORPH_CLOSE, kernel)
    
    # 3. Create Alpha
    b, g, r = cv2.split(img)
    alpha = mask_final * 255
    img_rgba = cv2.merge([b, g, r, alpha])

    # Crop
    coords = cv2.findNonZero(alpha)
    if coords is not None:
        x, y, cw, ch = cv2.boundingRect(coords)
        img_rgba = img_rgba[y:y+ch, x:x+cw]

    # Save
    targets = [
        '/Users/davidkotnik/repos/novafarma/main/assets/stream_pipe.png',
        '/Users/davidkotnik/repos/novafarma/assets/DEMO_FAZA1/Environment/stream_pipe.png'
    ]
    for t in targets:
        cv2.imwrite(t, img_rgba)
        print(f"Saved {t}")

if __name__ == "__main__":
    clean_pipe_stream_gentle()