Jagannath8/Lung_Disease_Classification

1import gradio as gr2 3import tensorflow as tf4import os5import numpy as np6 7model = tf.keras.models.load_model('model.hdf5')8 9LABELS = ['NORMAL', 'TUBERCULOSIS', 'PNEUMONIA', 'COVID19']10 11def predict_input_image(img):12  img_4d=img.reshape(-1,128,128,3)/255.013  print(img_4d.min())14  print(img_4d.max())15  prediction=model.predict(img_4d)[0]16  return {LABELS[i]: float(prediction[i]) for i in range(4)}17 18def k():19  return gr.update(value=None)20 21with gr.Blocks(title="Lung Disease Classification", css="") as demo:22  with gr.Row():23    textmd = gr.Markdown()24  with gr.Row():25    with gr.Column(scale=1, min_width=600):26      image = gr.inputs.Image(shape=(128,128))27      with gr.Row():28        clear_btn = gr.Button("Clear")29        submit_btn = gr.Button("Submit", elem_id="warningk", variant='primary')30      '''examples = gr.Examples(examples=["COVID19-0.jpg",31                                       "NORMAL-0.jpeg",32                                       "COVID19-1.jpg",33                                       "PNEUMONIA-0.jpeg"], inputs=image)'''34    label = gr.outputs.Label(num_top_classes=4)35    36    clear_btn.click(k, inputs=[], outputs=image)37    submit_btn.click(predict_input_image, inputs=image, outputs=label)38 39demo.launch()