import gradio as gr from predict import predict_masks, get_mask_for_label import glob demo = gr.Blocks() with demo: gr.Markdown("# **
FurnishAI
**") with gr.Box(): with gr.Row(): with gr.Column(): gr.Markdown("**Inputs**") input_image = gr.Image(type='filepath',label="Input Image", show_label=True) labels_dropdown = gr.Dropdown(label="Labels", show_label=True) with gr.Column(): gr.Markdown("**Outputs**") output_heading = gr.Textbox(label="Output Type", show_label=True) output_mask = gr.Image(label="Predicted Masks", show_label=True) selected_mask = gr.Image(label="Selected Mask", show_label=True) gr.Markdown("**Predict**") with gr.Box(): with gr.Row(): submit_button = gr.Button("Submit") generate_mask_button = gr.Button("Generate Mask") gr.Markdown("**Examples:**") submit_button.click(predict_masks, inputs=[input_image], outputs=[output_mask, output_heading, labels_dropdown]) generate_mask_button.click(get_mask_for_label, inputs=[predict_masks(input_image), labels_dropdown], outputs=[selected_mask]) gr.Markdown('\n Demo created by: Théo Belen-Halimi') demo.launch(debug=True)