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| import gradio as gr | |
| import cv2 | |
| import numpy as np | |
| # Function to perform image segmentation using OpenCV Watershed Algorithm | |
| def watershed_segmentation(input_image, scribble_image): | |
| # Load the input image and scribble image | |
| image = cv2.cvtColor(input_image.astype('uint8'), cv2.COLOR_RGBA2BGR) | |
| scribble = cv2.cvtColor(scribble_image.astype('uint8'), cv2.COLOR_RGBA2GRAY) | |
| # Convert scribble to markers (0 for background, 1 for unknown, 2 for foreground) | |
| markers = np.zeros_like(scribble) | |
| markers[scribble == 0] = 0 | |
| markers[scribble == 255] = 1 | |
| markers[scribble == 128] = 2 | |
| # Apply watershed algorithm | |
| cv2.watershed(image, markers) | |
| # Create a segmented mask | |
| segmented_mask = np.zeros_like(image, dtype=np.uint8) | |
| segmented_mask[markers == 2] = [0, 0, 255] # Red color for segmented regions | |
| return segmented_mask | |
| # Gradio interface | |
| input_image = gr.inputs.Image(type='pil', label="Upload an image") | |
| scribble_image = gr.inputs.Image(type='pil', label="Scribble on the image") | |
| output_image = gr.outputs.Image(type='pil', label="Segmented Image") | |
| gr.Interface( | |
| fn=watershed_segmentation, | |
| inputs=[input_image, scribble_image], | |
| outputs=output_image, | |
| title="Image Segmentation using Watershed Algorithm", | |
| description="Upload an image and scribble on it to perform segmentation using the Watershed Algorithm.", | |
| ).launch() |