74 lines
3.0 KiB
Python
74 lines
3.0 KiB
Python
import cv2
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import numpy as np
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import os
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def clean_pipe_stream_final():
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src_path = '/Users/davidkotnik/.gemini/antigravity/brain/07019d04-a214-43ab-9565-86f4e8f17e5b/uploaded_media_1769607894587.jpg'
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print(f"Loading {src_path}")
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img = cv2.imread(src_path)
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if img is None: return
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# 1. GRABCUT for Clean Foreground (Pipe + Stream + Earth)
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mask = np.zeros(img.shape[:2], np.uint8)
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bgdModel = np.zeros((1,65),np.float64)
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fgdModel = np.zeros((1,65),np.float64)
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h, w = img.shape[:2]
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# Rect: slight margin
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cv2.grabCut(img, mask, (10, 10, w-20, h-20), bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)
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mask_final = np.where((mask==2)|(mask==0),0,1).astype('uint8') # 0 = BG, 1 = FG
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# 2. FILL THE DRAIN HOLE (Make it opaque)
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# The drain is typically at the top-right or top area.
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# We can detect the "grating" (dark criss-cross lines).
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# Simple heuristic: The pipe opening is a dark area.
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# To prevent it from becoming transparent, we force the mask to be 1 in that region?
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# GrabCut usually keeps the hole opaque if it's distinct from BG.
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# But if there are "holes" in the GrabCut mask (transparency inside the object), we should fill them.
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# Close small holes in the mask (Morphological Closing)
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kernel = np.ones((5,5),np.uint8)
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mask_closed = cv2.morphologyEx(mask_final, cv2.MORPH_CLOSE, kernel)
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# 3. "BURYING" (Removing outer walls)
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# The outer walls are usually at the bottom-left and bottom-right edges of the mask.
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# We can try to "shave" the bottom of the mask to reduce the "block height".
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# Let's shift the mask up? No.
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# Let's erode the mask from the bottom?
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# We can assume the "floor" is higher.
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# This is risky, but let's try a mild erosion just on the edges to smooth the blend.
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# Actually, if we just ensure the alpha channel is clean, it might be enough.
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# Convert to RGBA
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b, g, r = cv2.split(img)
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alpha = mask_closed * 255
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# 4. COLOR FIX: If the drain hole inside is gray/white (from original image),
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# the user might want it BLACK (so it looks deep).
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# Let's darken the "dark" areas inside the foreground.
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# Convert to HSV, find dark areas in FG, make them blacker.
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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# Dark areas: Value < 50?
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dark_mask = (hsv[:,:,2] < 80) & (mask_closed == 1)
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img[dark_mask] = [20, 20, 20] # Very dark gray/black
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img_rgba = cv2.merge([img[:,:,0], img[:,:,1], img[:,:,2], alpha])
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# Crop
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coords = cv2.findNonZero(alpha)
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if coords is not None:
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x, y, cw, ch = cv2.boundingRect(coords)
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img_rgba = img_rgba[y:y+ch, x:x+cw]
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# Save
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targets = [
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'/Users/davidkotnik/repos/novafarma/main/assets/stream_pipe.png',
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'/Users/davidkotnik/repos/novafarma/assets/DEMO_FAZA1/Environment/stream_pipe.png'
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]
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for t in targets:
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cv2.imwrite(t, img_rgba)
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print(f"Saved {t}")
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if __name__ == "__main__":
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clean_pipe_stream_final()
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