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import gradio as gr | |
from backend import visualize_image | |
# gradio inputs | |
image_input = gr.inputs.Image(type="pil", label="Input Image") | |
mode_dropdown = gr.inputs.Dropdown(["Trees", "Buildings", "Both"]) | |
tree_threshold_slider = gr.inputs.Slider(0, 1, 0.1, 0.7, label='Set confidence threshold % for trees') | |
building_threshold_slider = gr.inputs.Slider(0, 1, 0.1, 0.7, label='Set confidence threshold % for buildings') | |
color_mode_select = gr.inputs.Radio(["Black/white", "Random", "Segmentation"]) | |
# gradio outputs | |
output_image = gr.outputs.Image(type="pil", label="Output Image") | |
title = "Building Segmentation" | |
description = "An instance segmentation demo for identifying boundaries of buildings in aerial images using DETR (End-to-End Object Detection) model with MaskRCNN-101 backbone" | |
# gradio interface | |
interface = gr.Interface( | |
fn=visualize_image, | |
inputs=[image_input, mode_dropdown, tree_threshold_slider, building_threshold_slider, color_mode_select], | |
outputs=output_image, | |
title=title, | |
description=description | |
) | |
interface.launch(debug=True) | |