import gradio as gr from predict import makepredictions, xray_predict from tumorseg import make_segmentation with gr.Blocks() as demo: with gr.Tab('Brain Tumor | Tumor Segmentation'): gr.Markdown("""
Tumor segmentations
> You could segment you mri image. I hope it will find you well
""") with gr.Row(): image_input = gr.Image(label='Tumor Image', type='filepath', height=480, interactive=True) output_image = gr.Image(label='label Segmented Image', height=480, interactive=False) image_button = gr.Button("Segment image") image_button.click(make_segmentation, inputs=image_input, outputs=output_image) with gr.Tab('Brain Tumor | Tumor Classification'): gr.Markdown("""
Brain Tumor Image classification
>We detect 4 Types of Tumor with 99.12% Accuracy: >Glioma | Meningioma | No Tumor | Pituitary """) image_input = gr.Image(label='Tumor Image', type='filepath', height=480) with gr.Row(): image_button = gr.Button("Predict") y_pred = gr.Textbox(label="Tumor Type:") image_button.click(makepredictions, inputs=image_input, outputs=y_pred) with gr.Tab('Chest X-ray | COVID19, NORMAL, PNEUMONIA,TURBERCULOSIS'): gr.Markdown("""
Chest X-ray classifications
> We COVID19, NORMAL, PNEUMONIA,TURBERCULOSIS from your chest x-ray image
""") image_input = gr.Image(label='Chest X-ray', type='filepath', height=480) with gr.Row(): image_button = gr.Button("Predict") y_pred = gr.Textbox(label="Disease :") image_button.click(xray_predict, inputs=image_input, outputs=[y_pred]) gr.Markdown( """
These model is trained on the Kaggle dataset:
> Only for the educational purpose > Play with that and Have fun.
""") demo.launch()