Update README.md

README.md

@@ -1,83 +0,0 @@
-import numpy as np
-import pickle
-import pandas as pd
-#import streamlit as st 
-import gradio as gr
-
-
-with open("DTHabitatClassifier.pkl","rb") as pickle_in:
-  classifier=pickle.load(pickle_in)
-
-
-def welcome():
-    return "Welcome All"
-
-def habitat(species, processid,	marker_code, gb_acs, nucraw	, levenshtein_distance):
-    
-    """Let's load in the features as argument 
-    This is using docstrings for specifications.
-    ---
-    parameters:  
-      - name: species
-        in: query
-        type: number
-        required: true
-      - name: processid
-        in: query
-        type: number
-        required: true
-      - name: marker_code
-        in: query
-        type: number
-        required: true
-      - name: gb_acs
-        in: query
-        type: number
-        required: true
-      - name: nucraw
-        in: query
-        type: number
-        required: true
-        - name: levenshtein_distance
-        in: query
-        type: number
-        required: true
-    responses:
-        200:
-            description: The output values
-        
-    """
-   
-    prediction=classifier.predict([[species, processid,	marker_code, gb_acs, nucraw, levenshtein_distance]])
-    print(prediction)
-    return prediction
-
-
-
-def main():
-    st.title("eDNA Habitat Classification")
-    html_temp = """
-    <div style="background-color:tomato;padding:10px">
-    <h2 style="color:white;text-align:center;">eDNA Habitat Classification App </h2>
-    </div>
-    """
-        
-    """Proudly, Team SpaceM!"""
-
-
-    st.markdown(html_temp,unsafe_allow_html=True)
-    species = st.text_input("Species")
-    processid = st.text_input("Processid")
-    marker_code = st.text_input("Marker Code")
-    gb_acs = st.text_input("GB_ACS")
-    nucraw = st.text_input("Nucraw")
-    levenshtein_distance = st.text_input("Levenshtein Distance")
-    result=""
-    if st.button("Classify"):
-        result=habitat(species, processid,	marker_code, gb_acs, nucraw, levenshtein_distance)
-    st.success(f'The output is {result}')
-    if st.button("About"):
-        st.text("Many thanks")
-
-if __name__=='__main__':
-    main()