Files
novafarma/scripts/clean_pipe_stream_grabcut.py

72 lines
2.2 KiB
Python

import cv2
import numpy as np
import os
def clean_pipe_stream_aggressive():
src_path = '/Users/davidkotnik/.gemini/antigravity/brain/07019d04-a214-43ab-9565-86f4e8f17e5b/uploaded_media_1769607894587.jpg'
print(f"Loading {src_path}")
img_bgr = cv2.imread(src_path)
if img_bgr is None:
print("Failed to load")
return
# Convert to HSV for better segmentation
hsv = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2HSV)
# The background is a "neutral gray".
# Gray means LOW Saturation.
# Light Gray means HIGH Value.
# Let's define "Background" as:
# Saturation < 20 (very gray)
# Value > 200 (very bright)
# But wait, the pipe is also gray! We risk deleting the pipe.
# Plan B: GrabCut.
# We initialize a mask where the center is "Probable Foreground" and edges are "Background".
mask = np.zeros(img_bgr.shape[:2], np.uint8)
bgdModel = np.zeros((1,65),np.float64)
fgdModel = np.zeros((1,65),np.float64)
h, w = img_bgr.shape[:2]
# Define rectangle: Cut off 10px from edges as "Definite Background"
# Everything else is "Probable Foreground"
rect = (10, 10, w-20, h-20)
print("Running GrabCut (this might take a second)...")
cv2.grabCut(img_bgr, mask, rect, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)
# Mask values: 0=BG, 1=FG, 2=Prob BG, 3=Prob FG
# We take 1 and 3 as mask
mask2 = np.where((mask==2)|(mask==0),0,1).astype('uint8')
img_bgr = img_bgr * mask2[:,:,np.newaxis]
# Now create Alpha channel
b, g, r = cv2.split(img_bgr)
alpha = mask2 * 255
img_rgba = cv2.merge([b, g, r, alpha])
# Crop to content
coords = cv2.findNonZero(alpha)
if coords is not None:
x, y, cw, ch = cv2.boundingRect(coords)
print(f"Cropping to: {x},{y} {cw}x{ch}")
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 to {t}")
if __name__ == "__main__":
clean_pipe_stream_aggressive()