|
import streamlit as st |
|
from streamlit_option_menu import option_menu |
|
from tensorflow import keras |
|
import tensorflow as tf |
|
import numpy as np |
|
import pandas as pd |
|
import os |
|
os.environ['CUDA_VISIBLE_DEVICES'] = '-1' |
|
|
|
if 'model' not in st.session_state: |
|
st.session_state.model = 'Brain Tumor Detection' |
|
def update_radio(): |
|
st.session_state.model =st.session_state.radio |
|
|
|
if 'clas' not in st.session_state: |
|
st.session_state.clas = '2 Classes' |
|
def update_selbox(): |
|
st.session_state.clas =st.session_state.box |
|
|
|
if 'check' not in st.session_state: |
|
st.session_state.check1 = False |
|
def update_check(): |
|
st.session_state.check1 =st.session_state.check |
|
|
|
def update_photo(): |
|
st.session_state.photo =st.session_state.image |
|
|
|
def pred(img,radio,selbox,check): |
|
img = tf.keras.utils.load_img( |
|
img, |
|
grayscale=False, |
|
color_mode='rgb', |
|
target_size=(224,224), |
|
interpolation='nearest', |
|
keep_aspect_ratio=False |
|
) |
|
os.remove(st.session_state.image.name) |
|
img = np.array(img).reshape(-1, 224, 224, 3) |
|
if radio =='Alzheimer Detection': |
|
model = keras.models.load_model('alzheimer_99.5.h5') |
|
result=['Mild_Demented', 'Moderate_Demented', 'Non_Demented', 'Very_Mild_Demented'] |
|
else: |
|
if selbox == '44 Classes': |
|
model = keras.models.load_model('44class_96.5.h5') |
|
result=['Astrocitoma T1','Astrocitoma T1C+','Astrocitoma T2','Carcinoma T1','Carcinoma T1C+','Carcinoma T2','Ependimoma T1','Ependimoma T1C+','Ependimoma T2','Ganglioglioma T1','Ganglioglioma T1C+', |
|
'Ganglioglioma T2','Germinoma T1','Germinoma T1C+','Germinoma T2','Glioblastoma T1','Glioblastoma T1C+','Glioblastoma T2','Granuloma T1','Granuloma T1C+','Granuloma T2','Meduloblastoma T1', |
|
'Meduloblastoma T1C+','Meduloblastoma T2','Meningioma T1','Meningioma T1C+','Meningioma T2','Neurocitoma T1','Neurocitoma T1C+','Neurocitoma T2','Oligodendroglioma T1','Oligodendroglioma T1C+', |
|
'Oligodendroglioma T2','Papiloma T1','Papiloma T1C+','Papiloma T2','Schwannoma T1','Schwannoma T1C+','Schwannoma T2','Tuberculoma T1','Tuberculoma T1C+','Tuberculoma T2','_NORMAL T1','_NORMAL T2'] |
|
if selbox == '17 Classes': |
|
model = keras.models.load_model('17class_98.1.h5') |
|
result=['Glioma (Astrocitoma, Ganglioglioma, Glioblastoma, Oligodendroglioma, Ependimoma) T1','Glioma (Astrocitoma, Ganglioglioma, Glioblastoma, Oligodendroglioma, Ependimoma) T1C+','Glioma (Astrocitoma, Ganglioglioma, Glioblastoma, Oligodendroglioma, Ependimoma) T2', |
|
'Meningioma (de Baixo Grau, Atípico, Anaplásico, Transicional) T1','Meningioma (de Baixo Grau, Atípico, Anaplásico, Transicional) T1C+','Meningioma (de Baixo Grau, Atípico, Anaplásico, Transicional) T2','NORMAL T1','NORMAL T2','Neurocitoma (Central - Intraventricular, Extraventricular) T1','Neurocitoma (Central - Intraventricular, Extraventricular) T1C+', |
|
'Neurocitoma (Central - Intraventricular, Extraventricular) T2','Outros Tipos de Lesões (Abscessos, Cistos, Encefalopatias Diversas) T1','Outros Tipos de Lesões (Abscessos, Cistos, Encefalopatias Diversas) T1C+','Outros Tipos de Lesões (Abscessos, Cistos, Encefalopatias Diversas) T2','Schwannoma (Acustico, Vestibular - Trigeminal) T1', |
|
'Schwannoma (Acustico, Vestibular - Trigeminal) T1C+','Schwannoma (Acustico, Vestibular - Trigeminal) T2'] |
|
if selbox == '15 Classes': |
|
model = keras.models.load_model('15class_99.8.h5') |
|
result=['Astrocitoma','Carcinoma','Ependimoma','Ganglioglioma','Germinoma','Glioblastoma','Granuloma','Meduloblastoma','Meningioma','Neurocitoma','Oligodendroglioma','Papiloma','Schwannoma','Tuberculoma','_NORMAL'] |
|
if selbox == '2 Classes': |
|
model = keras.models.load_model('2calss_lagre_dataset_99.1.h5') |
|
result=['no', 'yes'] |
|
pred= model.predict(img) |
|
if check: |
|
pred=pd.DataFrame({ |
|
'class_name' : result, |
|
'pred_score' : pred.flatten()*100 |
|
}) |
|
return pred |
|
pred = np.argmax(pred, axis=1) |
|
return result[pred[0]] |
|
|
|
def spr_sidebar(): |
|
menu=option_menu( |
|
menu_title=None, |
|
options=['Home','About'], |
|
icons=['house','info-square'], |
|
menu_icon='cast', |
|
default_index=0, |
|
orientation='horizontal' |
|
) |
|
if menu=='Home': |
|
st.session_state.app_mode = 'Home' |
|
elif menu=='About': |
|
st.session_state.app_mode = 'About' |
|
|
|
def home_page(): |
|
st.session_state.check=st.session_state.check1 |
|
st.session_state.radio=st.session_state.model |
|
st.session_state.box=st.session_state.clas |
|
if 'photo' in st.session_state: |
|
st.session_state.image=st.session_state.photo |
|
|
|
st.title('Brain Tumor Detection') |
|
st.session_state.image=st.file_uploader('Upload MRI Image',accept_multiple_files=False,type=['png', 'jpg','jpeg'],key="upload",on_change=update_photo) |
|
if st.session_state.image != None: |
|
st.image(st.session_state.image,width=300) |
|
col,col2=st.columns([2,3]) |
|
radio=col.radio("Model",options=('Brain Tumor Detection','Alzheimer Detection'),key='radio',on_change=update_radio) |
|
check=col.checkbox('Show Prediction Scores',key='check',on_change=update_check) |
|
if radio =='Brain Tumor Detection': |
|
selbox=col2.selectbox("choose a number of Classes",options=('44 Classes','17 Classes' ,'15 Classes','2 Classes'),index=0,key='box',on_change=update_selbox) |
|
else: |
|
selbox=col2.radio("choose a number of Classes",options=(['4 Classes']),index=0,key='box1',on_change=update_selbox) |
|
|
|
state =col.button('Get Result') |
|
if state: |
|
f=open(st.session_state.image.name, 'wb') |
|
f.write(st.session_state.image.getbuffer()) |
|
f.close() |
|
|
|
col2.write(pred(st.session_state.image.name,radio,selbox,check)) |
|
|
|
|
|
|
|
def About_page(): |
|
st.error("Nothing Here yet") |
|
|
|
def main(): |
|
spr_sidebar() |
|
if st.session_state.app_mode == 'Home': |
|
home_page() |
|
if st.session_state.app_mode == 'About' : |
|
About_page() |
|
|
|
if __name__ == '__main__': |
|
main() |
