File size: 2,427 Bytes
437e081
539be38
 
437e081
 
539be38
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
437e081
 
539be38
 
 
 
 
 
 
437e081
79de66f
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
52
53
54
55
56
57
58
59
60
61
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("""
            <div align='center'>Tumor segmentations
            </div>
            <div align='center'>
                   > You could segment you mri image. I hope it will find you well       
            </div>
             """)
        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("""
        <div align='center'>
        Brain Tumor Image classification
        </div>
        <div align='center'>
            >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("""
                    <div align='center'>Chest X-ray classifications
                    </div>
                    <div align='center'>
                       > We COVID19, NORMAL, PNEUMONIA,TURBERCULOSIS from your chest x-ray image
                    </div>
                          """)

        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(
        """
        <div align='center'>
           These model is trained on the Kaggle dataset:
           </div>
           <div align='center'>
                  > Only for the educational purpose
                  > Play with that and Have fun.
            </div>      
        """)
demo.launch()