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import gradio as gr | |
from predict import predict_masks, get_mask_for_label | |
import glob | |
def wrapper_func(input_img_path, selected_label): | |
output_result, output_heading, labels = predict_masks(input_img_path) | |
mask = get_mask_for_label(output_result, selected_label) | |
return mask | |
demo = gr.Blocks() | |
with demo: | |
gr.Markdown("# **<p align='center'>FurnishAI</p>**") | |
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.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(wrapper_func, inputs=[input_image, labels_dropdown], outputs=[selected_mask]) | |
gr.Markdown('\n Demo created by: <a href=\"https://www.linkedin.com/in/theo-belen-halimi/">Théo Belen-Halimi</a>') | |
demo.launch(debug=True) |