| import gradio as gr | |
| import numpy as np | |
| import imageio | |
| def process_image(img): | |
| imageio.imwrite("output_image.png", img["composite"]) | |
| alpha_channel = img["layers"][0][:, :, 3] | |
| mask = np.where(alpha_channel == 0, 0, 255) | |
| # return img["background"], mask | |
| return mask | |
| # with gr.Blocks() as demo: | |
| # with gr.Row(): | |
| # img = gr.ImageMask(sources=["upload"], layers=False, transforms=[], format="png", label="base image", show_label=True) | |
| # img1 = gr.Image() | |
| # img2 = gr.Image(label="mask image", show_label=True) | |
| # btn = gr.Button() | |
| # btn.click(dummy, img, [img1, img2]) | |
| # Define the Gradio interface | |
| demo = gr.Interface( | |
| fn=process_image, | |
| inputs=gr.ImageMask(sources=["upload"], layers=False, transforms=[], format="png", label="base image", show_label=True, height = 600), | |
| outputs=[ | |
| # gr.Image(label="Background Image"), | |
| gr.Image(label="Mask Image"), | |
| ], | |
| ) | |
| demo.launch(debug=True) |