--- a
+++ b/hemorrhage.py
@@ -0,0 +1,93 @@
+import streamlit as st
+from streamlit_discourse import st_discourse
+import os 
+import pydicom 
+import cv2
+import numpy as np
+from fastai.vision.all import * 
+learner = load_learner("/home/tkrsh/Projects/Hemorrhage/model_b_1.pkl")
+
+hide_streamlit_style = """
+            <style>
+            #MainMenu {visibility: hidden;}
+            footer {visibility: hidden;}
+            </style>
+            """
+st.markdown(hide_streamlit_style, unsafe_allow_html=True) 
+
+import time
+from PIL import Image
+
+from streamlit_disqus import st_disqus
+from streamlit_echarts import st_echarts
+
+
+def return_options():
+    pass
+     
+    
+st.write(""" # Intracranial Hemorrhage Classification""")
+st.write(""" ### In this Demo Version of our model we estimate whether the patient has Hemorrhage or the CT Scan is Normal """)
+st.write(""" #### Generated Result will show a bar graph with probabilities of the cases""")
+
+
+st.write("Source https://hemorrhage.tkrsh.com")
+    
+showWarningOnDirectExecution = False
+
+@st.cache
+def load_image(image_file):
+    img = Image.open(image_file)
+    return img
+
+
+image_file = st.file_uploader("Upload Image Here ", type="jpg", accept_multiple_files=False, key=None, help=None, on_change=None, args=None, kwargs=None)
+
+
+if image_file is not None:
+    file_details = {"FileName":image_file.name,"FileType":image_file.type}
+    # st.write(file_details)
+    img = load_image(image_file)
+    st.image(img,caption=f"Uploaded Image :  {image_file.name}",)
+    with open(os.path.join("/home/tkrsh/Projects/Hemorrhage",image_file.name),"wb") as f: 
+      f.write(image_file.getbuffer())         
+    prediction = learner.predict(f"/home/tkrsh/Projects/Hemorrhage/{image_file.name}")
+    p_1 = round(float(prediction[-1][0]),1)
+    p_2 = round(float(prediction[-1][1]),1)
+     
+    options = {
+        "xAxis": {
+            "type": "category",
+            "data": ["Hemorrhage ", "Normal "]
+        },
+        "yAxis": {"type": "value"},
+        "series": [
+            {"data":[p_1,p_2] , "type": "bar"}
+        ],
+    }
+    
+    st.success("Image Uploaded To The Server")
+    time.sleep(1)
+    st.success("Computing Predictions Please Wait")
+    time.sleep(4)
+    if int(prediction[1]) == 0:
+        st.write("#### Your Diagnosis: Hemorrhage is present """)
+    if int(prediction[1]) == 1:
+        st.write(""" #### Your Diagnosis: Scan Is Normal """)
+    
+    
+    
+    
+    st_echarts(options=options, height=400, width=700)
+    time.sleep(6)
+    
+    st.write("##### Please reach out to clear you concerns we are here to help tkrsh@tkrsh.com")
+   # st_disqus("Tkrsh",url="https://tkrsh.disqus.com/")
+
+    
+
+
+
+
+
+