Added main.py

.gitignore

@@ -0,0 +1 @@
+2class_98.0.h5

15class_99.8.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c2766c6c89e510b22653077e844530f15a61adffc2801a1a7b84135be4250664
+size 121419384

17class_98.1.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3b0ee74f9ed304d6c528717e7fd2b1385a6df761b2d3a79d7c1a665b2a68df48
+size 121425528

2calss_lagre_dataset_99.1.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:70801ee2d35a41c8de8385b525d676294598239554d255e492f8ac0323a7f8ce
+size 121378648

44class_96.5.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:050a428ad49f450b0baa6a7bf6689e61d6877af23289dfd7dfb816ca8e4b7b54
+size 117140352

alzheimer_99.5.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:278c4b20e67ce5bc2235c389b6bc96b6ab2708e087ff91114743fbbcc88b29e8
+size 117136616

main.py

@@ -0,0 +1,126 @@
+import streamlit as st
+from streamlit_option_menu import option_menu
+import streamlit.components.v1 as components
+from tensorflow import keras
+import tensorflow as tf
+import numpy as np
+import cv2
+import io
+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()
+        })
+        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)
+        radio=st.radio("Model",options=('Brain Tumor Detection','Alzheimer Detection'),key='radio',on_change=update_radio)
+        check=st.checkbox('Show Prediction Scores',key='check',on_change=update_check)
+        if radio =='Brain Tumor Detection':
+            selbox=st.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=st.radio("choose a number of Classes",options=(['4 Classes']),index=0,key='box1',on_change=update_selbox)
+        state =st.button('Get Result')
+        if state:
+            f=open(st.session_state.image.name, 'wb') 
+            f.write(st.session_state.image.getbuffer())
+            f.close()
+            
+            st.write(pred(st.session_state.image.name,radio,selbox,check))
+
+
+
+def About_page():
+    st.write("Soon")
+
+def main():
+    spr_sidebar()        
+    if st.session_state.app_mode == 'Home':
+        home_page()
+    if st.session_state.app_mode == 'About' :
+        About_page()
+# Run main()
+if __name__ == '__main__':
+    main()