👀 Views: 425 💬 Answers: 1 📅 Created: 2025-06-13

opencv grabcut computer-vision Python

I'm attempting to set up I'm working through a tutorial and I'm migrating some code and I'm currently working on a project where I need to extract the foreground from a video stream using OpenCV's GrabCut algorithm... The scenario I'm working with is that the algorithm often fails to accurately segment the foreground, especially when there are overlapping colors in the scene. I'm using OpenCV version 4.5.3 with Python. My setup includes a webcam input, and I'm trying to process the frames in real-time. Here’s a snippet of the code I’m using to initialize the GrabCut: ```python import cv2 import numpy as np cap = cv2.VideoCapture(0) while True: ret, frame = cap.read() if not ret: break mask = np.zeros(frame.shape[:2], np.uint8) bgd_model = np.zeros((1, 65), np.float64) fgd_model = np.zeros((1, 65), np.float64) # Define a rectangle for the initial grabcut rect = (50, 50, frame.shape[1]-50, frame.shape[0]-50) cv2.grabCut(frame, mask, rect, bgd_model, fgd_model, 5, cv2.GC_INIT_WITH_RECT) # Create a binary mask where sure and likely foreground pixels are set to 1 mask2 = np.where((mask == 2) | (mask == 0), 0, 1).astype('uint8') result = frame * mask2[:, :, np.newaxis] cv2.imshow('Foreground', result) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows() ``` The rectangle I defined does not always encompass the entire object I want to segment, which leads to parts of the object being identified as background. I've tried adjusting the rectangle to include more of the object, but it still doesn't yield satisfactory results. Additionally, when the object moves too fast, the background model seems to get confused, resulting in flickering artifacts. Is there a way to improve the accuracy of the segmentation in such dynamic scenarios? Should I consider using a mask to specify known foreground points, or is there another approach in OpenCV that might yield better results? Any suggestions would be greatly appreciated! What would be the recommended way to handle this? The project is a mobile app built with Python. For context: I'm using Python on Debian. Is there a better approach?