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| import gradio as gr | |
| import numpy as np | |
| def custom_composite(im): | |
| # Get image dimensions and check the number of channels | |
| h, w, c = im["background"].shape # c could be 3 (RGB) or 4 (RGBA) | |
| # Create a black background with 3 channels (RGB) | |
| black_bg = np.zeros((h, w, 3), dtype=np.uint8) | |
| # Extract layers, ensuring they have 3 channels (RGB) | |
| def to_rgb(layer): | |
| return ( | |
| layer[:, :, :3] if layer.shape[2] == 4 else layer | |
| ) # Drop alpha if present | |
| layer1 = to_rgb(im["layers"][0]) if len(im["layers"]) > 0 else black_bg | |
| layer2 = to_rgb(im["layers"][1]) if len(im["layers"]) > 1 else black_bg | |
| # Merge layers onto the black background | |
| final_composite = np.where(layer1 > 0, layer1, black_bg) | |
| final_composite = np.where(layer2 > 0, layer2, final_composite) | |
| return final_composite | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| im = gr.ImageEditor( | |
| type="numpy", crop_size="1:1", brush=gr.Brush(default_color="white") | |
| ) | |
| im_preview = gr.Image(format="png") | |
| im.change(custom_composite, outputs=im_preview, inputs=im, show_progress="hidden") | |
| if __name__ == "__main__": | |
| demo.launch() | |