app.py

from read_whole_sliding_images import *
from stain_normalization import *
import gradio as gr
wsi2png = gr.Interface(fn=wsi2png, inputs=gr.inputs.File(), outputs=gr.outputs.Image(type='numpy'),
                       examples=wsi2png_examples)
bound_png = gr.Interface(fn=read_bounds_of_image, inputs=gr.inputs.Image(type='numpy'),
                         outputs=gr.outputs.Image(type='numpy'), examples=read_bounds_examples)


inp1 = gr.inputs.File()
inp2 = gr.Slider(1, 10, 4, step=0.25, label="Resolution")
mask_wsi = gr.Interface(fn=mask_image, inputs=[inp1, inp2], outputs=gr.outputs.Image(type='numpy'), examples=[mask_wsi_examples])

normalize_wsi = gr.Interface(fn=normalize_stain, inputs=gr.inputs.File(), outputs=gr.outputs.Image(type='numpy'),
                               examples=[stain_normalization_wsi_examples])


demo = gr.TabbedInterface([wsi2png, bound_png, mask_wsi, normalize_wsi], ["WSI2PNG", "Bound Image", "Mask WSI",
                                                                          "Normalize Stain"])

if __name__ == "__main__":
    demo.launch(show_api=True, auth=("patho", "vis"))