Spaces:
Runtime error
Runtime error
File size: 1,974 Bytes
e5a19d6 edf1278 e5a19d6 edf1278 e5a19d6 edf1278 e5a19d6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
import numpy as np
import gradio as gr
from utils import get_index_to_class_mapping
from load_data import generate_video_and_gradcam
from load_disease_info import disease_info
from PIL import Image
def display_name(pathology_str:str) -> str:
return disease_info(pathology_str)
def show_logo(path):
numpy_logo = np.asarray(Image.open(path))
return numpy_logo
with gr.Blocks() as demo:
with gr.Column():
gr.Markdown("# Latent diffusion model (LDM) for synthetic X-ray generation")
with gr.Row():
gr.HTML("<img width='200' height='200' src='/file/logos/FAU_TechFak_H_RGB_white.png' alt='FAU TechFak logo'>")
gr.HTML("<img width='200' height='200' src='/file/logos/LME_logo_english.png' alt='LME logo'>")
gr.HTML("<img width='200' height='200' src='/file/logos/MDD-logo-weiss.png' alt='Medical data donors logo'>")
with gr.Column():
gr.Markdown("To create a synthetic image select the pathology from the set below and click **Generate**.")
radio = gr.Radio(list(get_index_to_class_mapping().values()), label="Pathology")
btn = gr.Button("Generate")
with gr.Row():
with gr.Tab(label="Diffusion model"):
video = gr.Video(label="Diffusion steps & Generated X-ray")
with gr.Tab(label="GradCAM Overlay"):
gr_image = gr.Image()
with gr.Column():
gr.Markdown("## Description of the diseases")
disease_description = gr.HTML(label="Disease description")
def submit(radio_selection):
generated_video, generated_gradcam = generate_video_and_gradcam(radio_selection)
return {
video: generated_video,
gr_image: generated_gradcam,
disease_description: display_name(radio_selection)
}
btn.click(fn=submit, inputs=radio, outputs=[video, gr_image, disease_description])
demo.launch()
|